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  • 351.
    Panariello, Claudio
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Medieteknik och interaktionsdesign, MID.
    Sköld, Sköld
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Medieteknik och interaktionsdesign, MID. KMH Royal College of Music.
    Frid, Emma
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Medieteknik och interaktionsdesign, MID.
    Bresin, Roberto
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Medieteknik och interaktionsdesign, MID.
    From vocal sketching to sound models by means of a sound-based musical transcription system2019Ingår i: Proceedings of the 16th Sound and Music Computing Conference, Malaga, Spain, 2019, s. 1-7, artikel-id S2.5Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper explores how notation developed for the representation of sound-based musical structures could be used for the transcription of vocal sketches representing expressive robot movements. A mime actor initially produced expressive movements which were translated to a humanoid robot. The same actor was then asked to illustrate these movements using vocal sketching. The vocal sketches were transcribed by two composers using sound-based notation. The same composers later synthesized new sonic sketches from the annotated data. Different transcriptions and synthesized versions of these were compared in order to investigate how the audible outcome changes for different transcriptions and synthesis routines. This method provides a palette of sound models suitable for the sonification of expressive body movements.

  • 352. Patel, Mitesh
    et al.
    Miro, Jaime Valls
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ek, Carl Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Dissanayake, Gamini
    Learning object, grasping and manipulation activities using hierarchical HMMs2014Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 37, nr 3, s. 317-331Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents a probabilistic algorithm for representing and learning complex manipulation activities performed by humans in everyday life. The work builds on the multi-level Hierarchical Hidden Markov Model (HHMM) framework which allows decomposition of longer-term complex manipulation activities into layers of abstraction whereby the building blocks can be represented by simpler action modules called action primitives. This way, human task knowledge can be synthesised in a compact, effective representation suitable, for instance, to be subsequently transferred to a robot for imitation. The main contribution is the use of a robust framework capable of dealing with the uncertainty or incomplete data inherent to these activities, and the ability to represent behaviours at multiple levels of abstraction for enhanced task generalisation. Activity data from 3D video sequencing of human manipulation of different objects handled in everyday life is used for evaluation. A comparison with a mixed generative-discriminative hybrid model HHMM/SVM (support vector machine) is also presented to add rigour in highlighting the benefit of the proposed approach against comparable state of the art techniques.

  • 353. Patino-Saucedo, A.
    et al.
    Rostro-Gonzalez, H.
    Conradt, Jörg
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Beräkningsvetenskap och beräkningsteknik (CST). Technical University of Munich, Germany.
    Tropical fruits classification using an alexnet-type convolutional neural network and image augmentation2018Ingår i: 25th International Conference on Neural Information Processing, ICONIP 2018, Springer, 2018, Vol. 11304, s. 371-379Konferensbidrag (Refereegranskat)
    Abstract [en]

    AlexNet is a Convolutional Neural Network (CNN) and reference in the field of Machine Learning for Deep Learning. It has been successfully applied to image classification, especially in large sets such as ImageNet. Here, we have successfully applied a smaller version of the AlexNet CNN to classify tropical fruits from the Supermarket Produce dataset. This database contains 2633 images of fruits divided into 15 categories with high variability and complexity, i.e. shadows, pose, occlusion, reflection (fruits inside a bag), etc. Since few training samples are required for fruit classification and to prevent overfitting, the modified AlexNet CNN has fewer feature maps and fully connected neurons than the original one, and data augmentation of the training set is used. Numerical results show a top-1 classification accuracy of 99.56 %, and a top-2 accuracy of 100 % for the 15 classes, which outperforms previous works on the same dataset.

  • 354.
    Pauwels, Karl
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    SimTrack: A Simulation-based Framework for Scalable Real-time Object Pose Detection and Tracking2015Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), IEEE , 2015, s. 1300-1307Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose a novel approach for real-time object pose detection and tracking that is highly scalable in terms of the number of objects tracked and the number of cameras observing the scene. Key to this scalability is a high degree of parallelism in the algorithms employed. The method maintains a single 3D simulated model of the scene consisting of multiple objects together with a robot operating on them. This allows for rapid synthesis of appearance, depth, and occlusion information from each camera viewpoint. This information is used both for updating the pose estimates and for extracting the low-level visual cues. The visual cues obtained from each camera are efficiently fused back into the single consistent scene representation using a constrained optimization method. The centralized scene representation, together with the reliability measures it enables, simplify the interaction between pose tracking and pose detection across multiple cameras. We demonstrate the robustness of our approach in a realistic manipulation scenario. We publicly release this work as a part of a general ROS software framework for real-time pose estimation, SimTrack, that can be integrated easily for different robotic applications.

  • 355. Pauwels, Karl
    et al.
    Kragic Jensfelt, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Integrated On-line Robot-camera Calibration and Object Pose Estimation2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a novel on-line approach for extrinsic robot-camera calibration, a process often referred to as hand-eye calibration, that uses object pose estimates from a real-time model-based tracking approach. While off-line calibration has seen much progress recently due to the incorporation of bundle adjustment techniques, on-line calibration still remains a largely open problem. Since we update the calibration in each frame, the improvements can be incorporated immediately in the pose estimation itself to facilitate object tracking. Our method does not require the camera to observe the robot or to have markers at certain fixed locations on the robot. To comply with a limited computational budget, it maintains a fixed size configuration set of samples. This set is updated each frame in order to maximize an observability criterion. We show that a set of size 20 is sufficient in real-world scenarios with static and actuated cameras. With this set size, only 100 microseconds are required to update the calibration in each frame, and we typically achieve accurate robot-camera calibration in 10 to 20 seconds. Together, these characteristics enable the incorporation of calibration in normal task execution.

  • 356. Pavoni, Marco
    et al.
    Chang, Yongjun
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH).
    Park, Sang-Ho
    Smedby, Örjan
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Medicinsk avbildning.
    Convolutional neural network-based image enhancement for x-ray percutaneous coronary intervention2018Ingår i: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 5, nr 2, artikel-id 024006Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Percutaneous coronary intervention (PCI) uses x-ray images, which may give high radiation dose and high concentrations of contrast media, leading to the risk of radiation-induced injury and nephropathy. These drawbacks can be reduced by using lower doses of x-rays and contrast media, with the disadvantage of noisier PCI images with less contrast. Vessel-edge-preserving convolutional neural networks (CNN) were designed to denoise simulated low x-ray dose PCI images, created by adding artificial noise to high-dose images. Objective functions of the designed CNNs have been optimized to achieve an edge-preserving effect of vessel walls, and the results of the proposed objective functions were evaluated qualitatively and quantitatively. Finally, the proposed CNN-based method was compared with two state-of-the-art denoising methods: K-SVD and block-matching and 3D filtering. The results showed promising performance of the proposed CNN-based method for PCI image enhancement with interesting capabilities of CNNs for real-time denoising and contrast enhancement tasks.

  • 357. Pedicini, C.
    et al.
    Vasca, F.
    Iannelli, L.
    Jönsson, Ulf
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    An overview on averaging for pulse-modulated switched systems2011Ingår i: Proceedings of the IEEE Conference on Decision and Control, 2011, s. 1860-1865Konferensbidrag (Refereegranskat)
    Abstract [en]

    Averaging of fast switching systems is an effective technique used in many engineering applications. Practical stability and control design for a nonsmooth switched system can be inferred by analyzing the smooth averaged system. In this paper we overview the few formal approaches proposed in the literature to deal with the averaging of nonsmooth systems. The dithering, the phasor dynamics and the hybrid framework techniques are recast and compared by considering pulse-modulated switched linear systems as the common modeling platform.

  • 358.
    Persson, Lucas
    et al.
    KTH, Skolan för teknik och hälsa (STH), Medicinsk teknik, Data- och elektroteknik.
    Markström, Sebastian
    KTH, Skolan för teknik och hälsa (STH), Medicinsk teknik, Data- och elektroteknik.
    Indoor localization of hand-held Shopping Scanners2017Självständigt arbete på grundnivå (högskoleexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Denna avhandling undersöker tillämpliga inomhusnavigationssystem för nästa generations handhållna shopping terminaler, på uppdrag av företaget Virtual Stores. Avhandlingen undersöker och granskar tillämpliga inomhuslokaliseringsmetoder och sätt att kombinera och utvärdera mottagna lokaliseringsdata för att bistå med ackurat navigering utan att introducera någon ytterligare utrustning för en potentiell användare. Prototypnavigationssystem föreslogs, utvecklades och utvärderades användandes en kombination av väl utplacerade radiosändare användandes Bluetooth eller UltraWide Band (UWB) och tröghetssensorer i kombination med ett partikelfilter. Bluetooth-lösningen ansågs oförmögen att tillhandahålla någon exakt lokalisering medan prototypen som använde en kombination av UWB och tröghetssensorer visade sig vara en lovande lösnings med under 1m genomsnittligt fel under optimala förhållanden eller 2,0m genomsnittligt lokaliseringsfel i mer realistisk miljö. Systemet kräver emellertid att det undersökta området tillhandahåller 3 eller fler UWB-sändare inom synfältet för UWB-mottagaren hos användaren vid varje plats och riktning för att tillhandahålla ackurat lokalisering. Prototypen behöver skalas upp för att kunna bistå med lokalisering till mer än 1 radiomottagare innan den introduceras till detaljhandlen.

  • 359.
    Pettersson, Gustav M.
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Farkost och flyg. Univ Calif Santa Cruz, Elect & Comp Engn, Santa Cruz, CA 95064 USA..
    Dille, Michael
    NASA, Ames Res Ctr, Intelligent Robot Grp, Mountain View, CA USA..
    Abrahamsson, Sara
    Univ Calif Santa Cruz, Elect & Comp Engn, Santa Cruz, CA 95064 USA..
    Wong, Uland
    NASA, Ames Res Ctr, Intelligent Robot Grp, Mountain View, CA USA..
    Miniature 3D Microscope and Reflectometer for Space Exploration2019Ingår i: 2019 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL PHOTOGRAPHY (ICCP), IEEE , 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Characterization of objects in all dimensions at a microscopic level is important in numerous applications including surface analysis on planetary bodies. Existing microscopes fit for this task are large bench-top devices unsuitable for in-situ use, particularly in resource-constrained remote robotic exploration. Computational imaging techniques present a powerful means to overcome physical limitations in fielded sensors, but have seen especially little use in space applications. We present a miniature (150 gram) 3D microscopic imager without moving parts capable of providing 1-megapixel images at approximately 1 micron horizontal and 5 micron vertical resolution. This device combines light-field imaging and photometric stereo to provide both 3D reconstruction and reflectance characterization of individual soil grains. We thoroughly evaluate its performance by designing and nanofabricating a 3D-fiducial and further demonstrate its operation on a library of planetary soil simulants. This system opens vast opportunities for extension, demonstrating the potential of computational imaging to amplify sensing capabilities in space.

  • 360.
    Pham, M.-T.
    et al.
    Toshiba Research Europe Ltd..
    Woodford, O. J.
    Toshiba Research Europe Ltd..
    Perbet, F.
    Toshiba Research Europe Ltd..
    Maki, Atsuto
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Gherardi, R.
    Toshiba Research Europe Ltd..
    Stenger, B.
    Toshiba Research Europe Ltd..
    Cipolla, R.
    University of Cambridge.
    Distances and Means of Direct Similarities2014Ingår i: International Journal of Computer Vision, ISSN 0920-5691, E-ISSN 1573-1405, Vol. 112, nr 3, s. 285-306Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The non-Euclidean nature of direct isometries in a Euclidean space, i.e. transformations consisting of a rotation and a translation, creates difficulties when computing distances, means and distributions over them, which have been well studied in the literature. Direct similarities, transformations consisting of a direct isometry and a positive uniform scaling, present even more of a challenge—one which we demonstrate and address here. In this article, we investigate divergences (a superset of distances without constraints on symmetry and sub-additivity) for comparing direct similarities, and means induced by them via minimizing a sum of squared divergences. We analyze several standard divergences: the Euclidean distance using the matrix representation of direct similarities, a divergence from Lie group theory, and the family of all left-invariant distances derived from Riemannian geometry. We derive their properties and those of their induced means, highlighting several shortcomings. In addition, we introduce a novel family of left-invariant divergences, called SRT divergences, which resolve several issues associated with the standard divergences. In our evaluation we empirically demonstrate the derived properties of the divergences and means, both qualitatively and quantitatively, on synthetic data. Finally, we compare the divergences in a real-world application: vote-based, scale-invariant object recognition. Our results show that the new divergences presented here, and their means, are both more effective and faster to compute for this task.

  • 361.
    Pieropan, Alessandro
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Action Recognition for Robot Learning2015Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    This thesis builds on the observation that robots cannot be programmed to handle any possible situation in the world. Like humans, they need mechanisms to deal with previously unseen situations and unknown objects. One of the skills humans rely on to deal with the unknown is the ability to learn by observing others. This thesis addresses the challenge of enabling a robot to learn from a human instructor. In particular, it is focused on objects. How can a robot find previously unseen objects? How can it track the object with its gaze? How can the object be employed in activities? Throughout this thesis, these questions are addressed with the end goal of allowing a robot to observe a human instructor and learn how to perform an activity. The robot is assumed to know very little about the world and it is supposed to discover objects autonomously. Given a visual input, object hypotheses are formulated by leveraging on common contextual knowledge often used by humans (e.g. gravity, compactness, convexity). Moreover, unknown objects are tracked and their appearance is updated over time since only a small fraction of the object is visible from the robot initially. Finally, object functionality is inferred by looking how the human instructor is manipulating objects and how objects are used in relation to others. All the methods included in this thesis have been evaluated on datasets that are publicly available or that we collected, showing the importance of these learning abilities.

  • 362.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Bergstroem, Niklas
    Ishikawa, Masatoshi
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Robust and adaptive keypoint-based object tracking2016Ingår i: Advanced Robotics, ISSN 0169-1864, E-ISSN 1568-5535, Vol. 30, nr 4, s. 258-269Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Object tracking is a fundamental ability for a robot; manipulation as well as activity recognition relies on the robot being able to follow objects in the scene. This paper presents a tracker that adapts to changes in object appearance and is able to re-discover an object that was lost. At its core is a keypoint-based method that exploits the rigidity assumption: pairs of keypoints maintain the same relations over similarity transforms. Using a structured approach to learning, it is able to incorporate new appearances in its model for increased robustness. We show through quantitative and qualitative experiments the benefits of the proposed approach compared to the state of the art, even for objects that do not strictly follow the rigidity assumption.

  • 363.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Bergström, N.
    Ishikawa, M.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Robust tracking of unknown objects through adaptive size estimation and appearance learning2016Ingår i: Proceedings - IEEE International Conference on Robotics and Automation, IEEE conference proceedings, 2016, s. 559-566Konferensbidrag (Refereegranskat)
    Abstract [en]

    This work employs an adaptive learning mechanism to perform tracking of an unknown object through RGBD cameras. We extend our previous framework to robustly track a wider range of arbitrarily shaped objects by adapting the model to the measured object size. The size is estimated as the object undergoes motion, which is done by fitting an inscribed cuboid to the measurements. The region spanned by this cuboid is used during tracking, to determine whether or not new measurements should be added to the object model. In our experiments we test our tracker with a set of objects of arbitrary shape and we show the benefit of the proposed model due to its ability to adapt to the object shape which leads to more robust tracking results.

  • 364.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Bergström, Niklas
    Ishikawa, Masatoshi
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Robust 3D tracking of unknown objectsManuskript (preprint) (Övrigt vetenskapligt)
  • 365.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Bergström, Niklas
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ishikawa, Masatoshi
    Robust Tracking through Learning2014Ingår i: 32nd Annual Conference of the Robotics Society of Japan, 2014, 2014Konferensbidrag (Refereegranskat)
  • 366.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ek, Carl Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Functional Object Descriptors for Human Activity Modeling2013Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2013, s. 1282-1289Konferensbidrag (Refereegranskat)
    Abstract [en]

    The ability to learn from human demonstration is essential for robots in human environments. The activity models that the robot builds from observation must take both the human motion and the objects involved into account. Object models designed for this purpose should reflect the role of the object in the activity - its function, or affordances. The main contribution of this paper is to represent object directly in terms of their interaction with human hands, rather than in terms of appearance. This enables the direct representation of object affordances/function, while being robust to intra-class differences in appearance. Object hypotheses are first extracted from a video sequence as tracks of associated image segments. The object hypotheses are encoded as strings, where the vocabulary corresponds to different types of interaction with human hands. The similarity between two such object descriptors can be measured using a string kernel. Experiments show these functional descriptors to capture differences and similarities in object affordances/function that are not represented by appearance.

  • 367.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ek, Carl Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Recognizing Object Affordances in Terms of Spatio-Temporal Object-Object Relationships2014Ingår i: Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on, IEEE conference proceedings, 2014, s. 52-58Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we describe a probabilistic framework that models the interaction between multiple objects in a scene.We present a spatio-temporal feature encoding pairwise interactions between each object in the scene. By the use of a kernel representation we embed object interactions in a vector space which allows us to define a metric comparing interactions of different temporal extent. Using this metric we define a probabilistic model which allows us to represent and extract the affordances of individual objects based on the structure of their interaction. In this paper we focus on the presented pairwise relationships but the model can naturally be extended to incorporate additional cues related to a single object or multiple objects. We compare our approach with traditional kernel approaches and show a significant improvement.

  • 368.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Unsupervised object exploration using context2014Ingår i: The 23rd IEEE International Symposium on Robot and Human Interactive Communication, 2014 RO-MAN, IEEE conference proceedings, 2014, s. -506Konferensbidrag (Refereegranskat)
    Abstract [en]

    In order for robots to function in unstructured environments in interaction with humans, they must be able to reason about the world in a semantic meaningful way. An essential capability is to segment the world into semantic plausible object hypotheses. In this paper we propose a general framework which can be used for reasoning about objects and their functionality in manipulation activities. Our system employs a hierarchical segmentation framework that extracts object hypotheses from RGB-D video. Motivated by cognitive studies on humans, our work leverages on contextual information, e.g., that objects obey the laws of physics, to formulate object hypotheses from regions in a mathematically principled manner.

  • 369.
    Pieropan, Alessandro
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Salvi, Giampiero
    KTH, Skolan för datavetenskap och kommunikation (CSC), Tal, musik och hörsel, TMH.
    Pauwels, Karl
    Universidad de Granada, Spain.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Audio-Visual Classification and Detection of Human Manipulation Actions2014Ingår i: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), IEEE conference proceedings, 2014, s. 3045-3052Konferensbidrag (Refereegranskat)
    Abstract [en]

    Humans are able to merge information from multiple perceptional modalities and formulate a coherent representation of the world. Our thesis is that robots need to do the same in order to operate robustly and autonomously in an unstructured environment. It has also been shown in several fields that multiple sources of information can complement each other, overcoming the limitations of a single perceptual modality. Hence, in this paper we introduce a data set of actions that includes both visual data (RGB-D video and 6DOF object pose estimation) and acoustic data. We also propose a method for recognizing and segmenting actions from continuous audio-visual data. The proposed method is employed for extensive evaluation of the descriptive power of the two modalities, and we discuss how they can be used jointly to infer a coherent interpretation of the recorded action.

  • 370.
    Pokorny, Florian T.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Bekiroglu, Yasemin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Björkman, Mårten
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Exner, Johannes
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Grasp Moduli Spaces, Gaussian Processes and Multimodal Sensor Data2014Konferensbidrag (Refereegranskat)
  • 371.
    Pokorny, Florian T.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Bekiroglu, Yasemin
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Grasp Moduli Spaces and Spherical Harmonics2014Ingår i: 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014, s. 389-396Konferensbidrag (Refereegranskat)
  • 372.
    Pokorny, Florian T.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ek, Carl Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Persistent Homology for Learning Densities with Bounded Support2012Ingår i: Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012 / [ed] P. Bartlett, F.C.N. Pereira, C.J.C. Burges, L. Bottou and K.Q. Weinberger, Curran Associates, Inc., 2012, s. 1817-1825Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a novel method for learning densities with bounded support which enables us to incorporate 'hard' topological constraints. In particular, we show how emerging techniques from computational algebraic topology and the notion of persistent homology can be combined with kernel-based methods from machine learning for the purpose of density estimation. The proposed formalism facilitates learning of models with bounded support in a principled way, and - by incorporating persistent homology techniques in our approach - we are able to encode algebraic-topological constraints which are not addressed in current state of the art probabilistic models. We study the behaviour of our method on two synthetic examples for various sample sizes and exemplify the benefits of the proposed approach on a real-world dataset by learning a motion model for a race car. We show how to learn a model which respects the underlying topological structure of the racetrack, constraining the trajectories of the car.

  • 373.
    Pokorny, Florian T.
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ek, Carl Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Topological Constraints and Kernel-Based Density Estimation2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    This extended abstract1 explores the question of how to estimate a probability distribution from a finite number of samples when information about the topology of the support region of an underlying density is known. This workshop contribution is a continuation of our recent work [1] combining persistent homology and kernel-based density estimation for the first time and in which we explored an approach capable of incorporating topological constraints in bandwidth selection. We report on some recent experiments with high-dimensional motion capture data which show that our method is applicable even in high dimensions and develop our ideas for potential future applications of this framework.

  • 374. Pousman, Zachary
    et al.
    Romero, Mario
    Georgia Institute of Technology, USA.
    Smith, Adam
    Mateas, Michael
    Living with Tableau Machine: A Longitudinal Investigation of a Curious Domestic Intelligence2008Ingår i: Proceedings of the 10th International Conference on Ubiquitous Computing, ACM Press, 2008, s. 370-379Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a longitudinal investigation of Tableau Machine, an intelligent entity that interprets and reflects the lives of occupants in the home. We created Tableau Machine (TM) to explore the parts of home life that are unrelated to accomplishing tasks. Task support for "smart homes" has inspired many researchers in the community. We consider design for experience, an orthogonal dimension to task-centric home life. TM produces abstract visualizations on a large LCD every few minutes, driven by a set of four overhead cameras that capture a sense of the social life of a domestic space. The openness and ambiguity of TM allow for a cycle of co-interpretation with householders. We report on three longitudinal deployments of TM for a period of six weeks. Participant families engaged with TM at the outset to understand how their behaviors were influencing the machine, and, while TM remained puzzling, householders interacted richly with TM and its images. We extract some key design implications for an experience-focused smart home.

  • 375.
    Pronobis, Andrzej
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Caputo, Barbara
    IDIAP Research Institute, Martigny, Switzerland.
    The robot vision task2010Ingår i: The Information Retrieval Series: ImageCLEF / [ed] H. Müller, P. Clough, T. Deselaers, B. Caputo, Springer Berlin/Heidelberg, 2010, 32, s. 185-198Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    In 2009, ImageCLEF expanded its tasks with the introduction of the first robot vision challenge. The overall focus of the challenge is semantic localization of a robot platform using visual place recognition. This is a key topic of research in the robotics community today. This chapter presents the goals and achievements of the first edition of the robot vision task. We describe the task, the method of data collection used and the evaluation procedure. We give an overview of the obtained results and briefly highlight the most promising approaches. We then outline how the task will evolve in the near and distant future.

  • 376.
    Pronobis, Andrzej
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Fornoni, M.
    Christensen, H. I.
    Caputo, B.
    The robot vision track at ImageCLEF 20102010Ingår i: CLEF2010 Working Notes: Working Notes for CLEF 2010 Conference, Padua, Italy, September 22-23, 2010 / [ed] Martin Braschler, Donna Harman, Emanuele Pianta, Nicola Ferro, CEUR-WS , 2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper describes the robot vision track that has been proposed to the ImageCLEF 2010 participants. The track addressed the problem of visual place classification, with a special focus on generalization. Participants were asked to classify rooms and areas of an office environment on the basis of image sequences captured by a stereo camera mounted on a mobile robot, under varying illumination conditions. The algorithms proposed by the participants had to answer the question "where are you?" (I am in the kitchen, in the corridor, etc) when presented with a test sequence, acquired within the same building but at a different oor than the training sequence. The test data contained images of rooms seen during training, or additional rooms that were not imaged in the training sequence. The participants were asked to solve the problem separately for each test image (obligatory task). Additionally, results could also be reported for algorithms exploiting the temporal continuity of the image sequences (optional task). A total of seven groups participated to the challenge, with 42 runs submitted to the obligatory task, and 13 submitted to the optional task. The best result in the obligatory task was obtained by the Computer Vision and Geometry Laboratory, ETHZ, Switzerland, with an overall score of 677. The best result in the optional task was obtained by the Idiap Research Institute, Martigny, Switzerland, with an overall score of 2052.

  • 377.
    Pronobis, Andrzej
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Jensfelt, Patric
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sjöö, Kristoffer
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Zender, Hendrik
    Kruijff, Geert-Jan M.
    Mozos, O. M.
    Burgard, Wolfram
    Semantic modelling of space2010Ingår i: Cognitive Systems Monographs: Cognitive Systems / [ed] H. I. Christensen, G.-J. M. Kruijff, J. L. Wyatt, Springer Berlin/Heidelberg, 2010, 8, s. 165-221Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    A cornerstone for robotic assistants is their understanding of the space they are to be operating in: an environment built by people for people to live and work in. The research questions we are interested in in this chapter concern spatial understanding, and its connection to acting and interacting in indoor environments. Comparing the way robots typically perceive and represent the world with findings from cognitive psychology about how humans do it, it is evident that there is a large discrepancy. If robots are to understand humans and vice versa, robots need to make use of the same concepts to refer to things and phenomena as a person would do. Bridging the gap between human and robot spatial representations is thus of paramount importance.  A spatial knowledge representation for robotic assistants must address the issues of human-robot communication. However, it must also provide a basis for spatial reasoning and efficient planning. Finally, it must ensure safe and reliable navigation control. Only then can robots be deployed in semi-structured environments, such as offices, where they have to interact with humans in everyday situations.  In order to meet the aforementioned requirements, i.e. robust robot control and human-like conceptualization, in CoSy, we adopted a spatial representation that contains maps at different levels of abstraction. This stepwise abstraction from raw sensory input not only produces maps that are suitable for reliable robot navigation, but also yields a level of representation that is similar to a human conceptualization of spatial organization. Furthermore, this model provides a richer semantic view of an environment that permits the robot to do spatial categorization rather than only instantiation.  This approach is at the heart of the Explorer demonstrator, which is a mobile robot capable of creating a conceptual spatial map of an indoor environment. In the present chapter, we describe how we use multi-modal sensory input provided by a laser range finder and a camera in order to build more and more abstract spatial representations.

  • 378.
    Qi, Peng
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Wang, Lu
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Experiments of GMM based speaker identification2011Ingår i: URAI 2011: 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence, 2011, s. 26-31Konferensbidrag (Refereegranskat)
    Abstract [en]

    In human-robot interaction areas, the robot is often expected to recognize the identity of the speaker in some specific scenarios. It is a kind of biometric modality, and in general using statistical model is a classical and powerful method dealing with speaker identification problem. In this paper, we apply the Gaussian mixture model (GMM) on the speech feature distribution modeling and build the speaker identification system under MATLAB platform. Experiments are conducted on practical speech database and we also further give some insights into feature extraction, different length input utterances analysis and the impostor situation.

  • 379.
    Qi, Peng
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Wang, Lu
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    On simulation and analysis of mobile robot SLAM using Rao-Blackwellized particle filters2011Ingår i: IEEE/SICE Int. Symp. Syst. Integr., SII, 2011, s. 1239-1244Konferensbidrag (Refereegranskat)
    Abstract [en]

    The simultaneous localization and mapping (SLAM) is considered as a crucial prerequisite for purely autonomous mobile robots. In this paper, we demonstrate the mobile robot SLAM using Rao-Blackwellized particle filters (RBPF) through computer simulations under MATLAB platform, while an analytical investigation into the involved algorithms is presented. Then we make further comparisons, not only in parallel between the FastSLAM 1.0 and FastSLAM 2.0, also in vertical between FastSLAM performance and EKF-SLAM performance which used to be the dominant approach to the SLAM problem. Vivid simulations and numerical analysis make the paper illustrated with clarity and perception.

  • 380.
    Qin, Chunxia
    et al.
    Shanghai Jiao Tong Univ, Sch Biomed Engn, Shanghai, Peoples R China.;Shanghai Jiao Tong Univ, Sch Mech Engn, Room 805,Dongchuan Rd 800, Shanghai 200240, Peoples R China..
    Cao, Zhenggang
    Shanghai Jiao Tong Univ, Sch Mech Engn, Room 805,Dongchuan Rd 800, Shanghai 200240, Peoples R China..
    Fan, Shengchi
    Shanghai Jiao Tong Univ, Shanghai Peoples Hosp 9, Sch Med, Shanghai, Peoples R China..
    Wu, Yiqun
    Shanghai Jiao Tong Univ, Shanghai Peoples Hosp 9, Sch Med, Shanghai, Peoples R China..
    Sun, Yi
    Katholieke Univ Leuven, Fac Med, Dept Imaging & Pathol, OMFS IMPATH Res Grp, Louvain, Belgium.;Univ Hosp Leuven, Dept Oral & Maxillofacial Surg, Louvain, Belgium..
    Politis, Constantinus
    Katholieke Univ Leuven, Fac Med, Dept Imaging & Pathol, OMFS IMPATH Res Grp, Louvain, Belgium.;Univ Hosp Leuven, Dept Oral & Maxillofacial Surg, Louvain, Belgium..
    Wang, Chunliang
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Medicinsk avbildning.
    Chen, Xiaojun
    Shanghai Jiao Tong Univ, Sch Mech Engn, Room 805,Dongchuan Rd 800, Shanghai 200240, Peoples R China..
    An oral and maxillofacial navigation system for implant placement with automatic identification of fiducial points2019Ingår i: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 14, nr 2, s. 281-289Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    PurposeSurgical navigation system (SNS) has been an important tool in surgery. However, the complicated and tedious manual selection of fiducial points on preoperative images for registration affects operational efficiency to large extent. In this study, an oral and maxillofacial navigation system named BeiDou-SNS with automatic identification of fiducial points was developed and demonstrated.MethodsTo solve the fiducial selection problem, a novel method of automatic localization for titanium screw markers in preoperative images is proposed on the basis of a sequence of two local mean-shift segmentation including removal of metal artifacts. The operation of the BeiDou-SNS consists of the following key steps: The selection of fiducial points, the calibration of surgical instruments, and the registration of patient space and image space. Eight cases of patients with titanium screws as fiducial markers were carried out to analyze the accuracy of the automatic fiducial point localization algorithm. Finally, a complete phantom experiment of zygomatic implant placement surgery was performed to evaluate the whole performance of BeiDou-SNS. Results and conclusionThe coverage of Euclidean distances between fiducial marker positions selected automatically and those selected manually by an experienced dentist for all eight cases ranged from 0.373 to 0.847mm. Four implants were inserted into the 3D-printed model under the guide of BeiDou-SNS. And the maximal deviations between the actual and planned implant were 1.328mm and 2.326mm, respectively, for the entry and end point while the angular deviation ranged from 1.094 degrees to 2.395 degrees. The results demonstrate that the oral surgical navigation system with automatic identification of fiducial points can meet the requirements of the clinical surgeries.

  • 381.
    Rasolzadeh, Babak
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Visual Attention in Active Vision Systems: Attending, Classifying and Manipulating Objects2011Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    This thesis has presented a computational model for the combination of bottom-up and top-down attentional mechanisms. Furthermore, the use for this model has been demonstrated in a variety of applications of machine and robotic vision. We have observed that an attentional mechanism is imperative in any active vision system, machine as well as biological, since it not only reduces the amount of information that needs to be further processed (for say recognition, action), but also by only processing the attended image regions, such tasks become more robust to large amounts of clutter and noise in the visual field.

    Using various feature channels such as color, orientation, texture, depth and symmetry, as input, the presented model is able with a pre-trained artificial neural network to modulate a saliency map for a particular top-down goal, e.g. visual search for a target object. More specifically it dynamically combines the unmodulated bottom-up saliency with the modulated top-down saliency, by means of a biologically and psychophysically motivated temporal differential equation. This way the system is for instance able to detect important bottom-up cues, even while in visual search mode (top-down) for a particular object.

    All the computational steps for yielding the final attentional map, that ranks regions in images according to their importance for the system, are shown to be biologically plausible. It has also been demonstrated that the presented attentional model facilitates tasks other than visual search. For instance, using the covert attentional peaks that the model returns, we can improve scene understanding and segmentation through clustering or scattering of the 2D/3D components of the scene, depending on the configuration of these attentional peaks and their relations to other attributes of the scene. More specifically this is performed by means of entropy optimization of the scence under varying cluster-configurations, i.e. different groupings of the various components of the scene.

    Qualitative experiments demonstrated the use of this attentional model on a robotic humanoid platform and in a real-time manner control the overt attention of the robot by specifying the saccadic movements of the robot head. These experiments also exposed another highly important aspect of the model; its temporal variability, as opposed to many other attentional (saliency) models that exclusively deal with static images. Here the dynamic aspects of the attentional mechanism proved to allow for a temporally varying trade-off between top-down and bottom-up influences depending on changes in the environment of the robot.

    The thesis has also lay forward systematic and quantitative large scale experiments on the actual benefits and uses of this kind of attentional model. To this end a simulated 2D environment was implemented, where the system could not “see” the entire environment and needed to perform overt shifts of attention (a simulated saccade) in order to perfom a visual search task for a pre-defined sought object. This allowed for a simple and rapid substitution of the core attentional-model of the system with comparative computational models designed by other researchers. Nine such contending models were tested and compared with the presented model, in a quantitative manner. Given certain asumptions these experiments showed that the attentional model presented in this work outperforms the other models in simple visualsearch tasks.

  • 382.
    Rasolzadeh, Babak
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Petersson, Lars
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Pettersson, Niklas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Response binning: Improved weak classifiers for boosting2006Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper demonstrates the value of improving the discriminating strength of weak classifiers in the context of boosting by using response binning. The reasoning is centered around, but not limited to, the well known Haar-features used by Viola & Jones in their face detection/pedestrian detection systems. It is shown that using a weak classifier based on a single threshold is sub-optimal and in the case of the Haar-feature inadequate. A more general method for features with multi-modal responses is derived that is easily used in boosting mechanisms that accepts a confidence measure, such as the RealBoost algorithm. The method is evaluated by boosting a single stage classifier and compare the performance to previous approaches.

  • 383.
    Razavian, Ali Sharif
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Sullivan, Josephine
    KTH.
    Carlsson, Stefan
    KTH.
    Maki, Atsuto
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Visual instance retrieval with deep convolutional networks2016Ingår i: ITE Transactions on Media Technology and Applications, ISSN 2186-7364, Vol. 4, nr 3, s. 251-258Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval. Besides the choice of convolutional layers, we present an efficient pipeline exploiting multi-scale schemes to extract local features, in particular, by taking geometric invariance into explicit account, i.e. positions, scales and spatial consistency. In our experiments using five standard image retrieval datasets, we demonstrate that generic ConvNet image representations can outperform other state-of-the-art methods if they are extracted appropriately.

  • 384. Roland, P
    et al.
    Svensson, Gert
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Risch, T
    Baumann, P
    Dehmel, A
    Fredriksson, Jesper
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Halldorson, Hjörleifur
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Forsberg, Lars
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Young, J
    Zilles, Karl
    A database generator for human brain imaging2001Ingår i: TINS - Trends in Neurosciences, ISSN 0166-2236, E-ISSN 1878-108X, Vol. 24, nr 10, s. 562-564Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogenous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.

  • 385. Romero, Javier
    et al.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ek, Carl Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Non-parametric hand pose estimation with object context2013Ingår i: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 31, nr 8, s. 555-564Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In the spirit of recent work on contextual recognition and estimation, we present a method for estimating the pose of human hands, employing information about the shape of the object in the hand. Despite the fact that most applications of human hand tracking involve grasping and manipulation of objects, the majority of methods in the literature assume a free hand, isolated from the surrounding environment. Occlusion of the hand from grasped objects does in fact often pose a severe challenge to the estimation of hand pose. In the presented method, object occlusion is not only compensated for, it contributes to the pose estimation in a contextual fashion; this without an explicit model of object shape. Our hand tracking method is non-parametric, performing a nearest neighbor search in a large database (.. entries) of hand poses with and without grasped objects. The system that operates in real time, is robust to self occlusions, object occlusions and segmentation errors, and provides full hand pose reconstruction from monocular video. Temporal consistency in hand pose is taken into account, without explicitly tracking the hand in the high-dim pose space. Experiments show the non-parametric method to outperform other state of the art regression methods, while operating at a significantly lower computational cost than comparable model-based hand tracking methods.

  • 386.
    Romero, Mario
    et al.
    Georgia Institute of Technology.
    Bobick, Aaron
    Tracking Head Yaw by Interpolation of Template Responses2004Ingår i: Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW’04) Volume 5 - Volume 05, Washington DC: IEEE Computer Society, 2004, Vol. 5, s. 83-Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose an appearance based machine learning architecturethat estimates and tracks in real time largerange head yaw given a single non-calibrated monoculargrayscale low resolution image sequence of the head. Thearchitecture is composed of five parallel template detectors,a Radial Basis Function Network and two Kalman filters.The template detectors are five view-specific images of thehead ranging across full profiles in discrete steps of 45 degrees.The Radial Basis Function Network interpolates theresponse vector from the normalized correlation of the inputimage and the 5 template detectors. The first Kalman filtermodels the position and velocity of the response vector infive dimensional space. The second is a running averagethat filters the scalar output of the network. We assume thehead image has been closely detected and segmented, that itundergoes only limited roll and pitch and that there are nosharp contrasts in illumination. The architecture is personindependentand is robust to changes in appearance, gestureand global illumination. The goals of this paper are,one, to measure the performance of the architecture, two,to asses the impact the temporal information gained fromvideo has on accuracy and stability and three, to determinethe effects of relaxing our assumptions.

  • 387.
    Romero, Mario
    et al.
    The Georgia Institute of Technology, USA.
    Mateas, Michael
    A preliminary investigation of Alien Presence2005Ingår i: Proceedings of Human-Computer Interaction International (HCII 2005), Las Vegas, NV, USA, July 2005, HCII , 2005, , s. 9Konferensbidrag (Refereegranskat)
    Abstract [en]

    Work in ubiquitous computing and ambient intelligence tends to focus on information access and task supportsystems informed by the office environment, which tend to view the whole world as an office, or on surveillancesystems that feature asymmetric information access, providing interpretations of activity to a central authority. Thealien presence provides an alternative model of ambient intelligence; an alien presence actively interprets abstractqualities of human activity (e.g. mood, social energy) and reports these interpretations, not to a central authority, butback to the user’s themselves in the form of ambient, possibly physical displays. The goal of an alien presence is nottask accomplishment and efficient access to information, but rather to open unusual viewpoints onto everydayhuman activity, create pleasure, and provide opportunities for contemplation and wonder. The design of an alienpresence is an interdisciplinary endeavor drawing on artificial intelligence techniques, art practices of creation andcritique, and HCI methods of design and evaluation. In this paper we present preliminary work on the TableauxMachine, an alien presence designed for the home environment, as well as discuss a number of general design issuesof alien presence including co-interpretation, authorship, richness of expression vs. system complexity, tensionsbetween viewing computation as a medium vs. as a model, issues of privacy, and evaluation.

  • 388.
    Romero, Mario
    et al.
    Georgia Institute of Technology, USA.
    Pousman, Zachary
    Mateas, Michael
    Alien Presence in the Home: The Design of Tableau Machine2008Ingår i: Personal and Ubiquitous Computing, ISSN 1617-4909, E-ISSN 1617-4917, Vol. 12, nr 5, s. 373-382Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We introduce a design strategy, alien presence, which combines work in human---computer interaction, artificial intelligence, and media art to create enchanting experiences involving reflection over and contemplation of daily activities. An alien presence actively interprets and characterizes daily activity and reflects it back via generative, ambient displays that avoid simple one-to-one mappings between sensed data and output. We describe the alien presence design strategy for achieving enchantment, and report on Tableau Machine, a concrete example of an alien presence design for domestic spaces. We report on an encouraging formative evaluation indicating that Tableau Machine does indeed support reflection and actively engages users in the co-construction of meaning around the display.

  • 389.
    Romero, Mario
    et al.
    Georgia Institute of Technology.
    Vialard, Alice
    Peponis, John
    Stasko, John
    Abowd, Gregory
    Evaluating Video Visualizations of Human Behavior2011Ingår i: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2011, s. 1441-1450Konferensbidrag (Refereegranskat)
    Abstract [en]

    Previously, we presented Viz-A-Vis, a VIsualiZation of Activity through computer VISion [17]. Viz-A-Vis visualizes behavior as aggregate motion over observation space. In this paper, we present two complementary user studies of Viz-A-Vis measuring its performance and discovery affordances. First, we present a controlled user study aimed at comparatively measuring behavioral analysis preference and performance for observation and search tasks. Second, we describe a study with architects measuring discovery affordances and potential impacts on their work practices. We conclude: 1) Viz-A-Vis significantly reduced search time; and 2) it increased the number and quality of insightful discoveries.

  • 390. Rosbacke, M.
    et al.
    Lindeberg, Tony
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Björkman, E.
    Roland, P. E.
    Evaluation of using absolute versus relative base level when analyzing brain activation images using the scale-space primal sketch2001Ingår i: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 5, nr 2, s. 89-110Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A dominant approach to brain mapping is to define functional regions in the brain by analyzing images of brain activation obtained from positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). This paper presents an evaluation of using one such tool, called the scale-space primal sketch, for brain activation analysis. A comparison is made concerning two possible definitions of a significance measure of blob structures in scale-space, where local contrast is measured either relative to a local or global reference level. Experiments on real brain data show that (i) the global approach with absolute base level has a higher degree of correspondence to a traditional statistical method than a local approach with relative base level, and that (ii) the global approach with absolute base level gives a higher significance to small blobs that are superimposed on larger scale structures, whereas the significance of isolated blobs largely remains unaffected. Relative to previously reported works, the following two technical improvements are also presented. (i) A post-processing tool is introduced for merging blobs that are multiple responses to image structures. This simplifies automated analysis from the scale-space primal sketch. (ii) A new approach is introduced for scale-space normalization of the significance measure, by collecting reference statistics of residual noise images obtained from the general Linear model.

  • 391. Rudinac, M.
    et al.
    Kootstra, Geert
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Jonker, P. P.
    Learning and recognition of objects inspired by early cognition2012Ingår i: Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, IEEE , 2012, s. 4177-4184Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we present a unifying approach for learning and recognition of objects in unstructured environments through exploration. Taking inspiration from how young infants learn objects, we establish four principles for object learning. First, early object detection is based on an attention mechanism detecting salient parts in the scene. Second, motion of the object allows more accurate object localization. Next, acquiring multiple observations of the object through manipulation allows a more robust representation of the object. And last, object recognition benefits from a multi-modal representation. Using these principles, we developed a unifying method including visual attention, smooth pursuit of the object, and a multi-view and multi-modal object representation. Our results indicate the effectiveness of this approach and the improvement of the system when multiple observations are acquired from active object manipulation.

  • 392. Sadeghian, A.
    et al.
    Lim, D.
    Karlsson, Johan Mikael
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    Li, J.
    Automatic target recognition using discrimination based on optimal transport2015Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, IEEE conference proceedings, 2015, s. 2604-2608Konferensbidrag (Refereegranskat)
    Abstract [en]

    The use of distances based on optimal transportation has recently shown promise for discrimination of power spectra. In particular, spectral estimation methods based on ℓ1 regularization as well as covariance based methods can be shown to be robust with respect to such distances. These transportation distances provide a geometric framework where geodesics corresponds to smooth transition of spectral mass, and have been useful for tracking. In this paper we investigate the use of these distances for automatic target recognition. We study the use of the Monge-Kantorovich distance compared to the standard ℓ2 distance for classifying civilian vehicles based on SAR images. We use a version of the Monge-Kantorovich distance that applies also for the case where the spectra may have different total mass, and we formulate the optimization problem as a minimum flow problem that can be computed using efficient algorithms.

  • 393.
    Salvado, Joao
    et al.
    Orebro Univ, AASS Res Ctr, Orebro, Sweden..
    Krug, Robert
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Robotik, perception och lärande, RPL.
    Mansouri, Masoumeh
    Orebro Univ, AASS Res Ctr, Orebro, Sweden..
    Pecora, Federico
    Orebro Univ, AASS Res Ctr, Orebro, Sweden..
    Motion Planning and Goal Assignment for Robot Fleets Using Trajectory Optimization2018Ingår i: 2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) / [ed] Maciejewski, AA Okamura, A Bicchi, A Stachniss, C Song, DZ Lee, DH Chaumette, F Ding, H Li, JS Wen, J Roberts, J Masamune, K Chong, NY Amato, N Tsagwarakis, N Rocco, P Asfour, T Chung, WK Yasuyoshi, Y Sun, Y Maciekeski, T Althoefer, K AndradeCetto, J Chung, WK Demircan, E Dias, J Fraisse, P Gross, R Harada, H Hasegawa, Y Hayashibe, M Kiguchi, K Kim, K Kroeger, T Li, Y Ma, S Mochiyama, H Monje, CA Rekleitis, I Roberts, R Stulp, F Tsai, CHD Zollo, L, IEEE , 2018, s. 7939-7946Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper is concerned with automating fleets of autonomous robots. This involves solving a multitude of problems, including goal assignment, motion planning, and coordination, while maximizing some performance criterion. While methods for solving these sub-problems have been studied, they address only a facet of the overall problem, and make strong assumptions on the use-case, on the environment, or on the robots in the fleet. In this paper, we formulate the overall fleet management problem in terms of Optimal Control. We describe a scheme for solving this problem in the particular case of fleets of non-holonomic robots navigating in an environment with obstacles. The method is based on a two-phase approach, whereby the first phase solves for fleet-wide boolean decision variables via Mixed Integer Quadratic Programming, and the second phase solves for real-valued variables to obtain an optimized set of trajectories for the fleet. Examples showcasing the features of the method are illustrated, and the method is validated experimentally.

  • 394. Sanmohan,
    et al.
    Krüger, V.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Unsupervised learning of action primitives2010Ingår i: 2010 10th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2010, IEEE , 2010, s. 554-559Konferensbidrag (Refereegranskat)
    Abstract [en]

    Action representation is a key issue in imitation learning for humanoids. With the recent finding of mirror neurons there has been a growing interest in expressing actions as a combination meaningful subparts called primitives. Primitives could be thought of as an alphabet for the human actions. In this paper we observe that human actions and objects can be seen as being intertwined: we can interpret actions from the way the body parts are moving, but as well from how their effect on the involved object. While human movements can look vastly different even under minor changes in location, orientation and scale, the use of the object can provide a strong invariant for the detection of motion primitives. In this paper we propose an unsupervised learning approach for action primitives that makes use of the human movements as well as the object state changes. We group actions according to the changes they make to the object state space. Movements that produce the same state change in the object state space are classified to be instances of the same action primitive. This allows us to define action primitives as sets of movements where the movements of each primitive are connected through the object state change they induce.

  • 395. Saponaro, Giovanni
    et al.
    Jamone, Lorenzo
    Bernardino, Alexandre
    Salvi, Giampiero
    KTH, Skolan för datavetenskap och kommunikation (CSC), Tal, musik och hörsel, TMH.
    Interactive Robot Learning of Gestures, Language and Affordances2017Ingår i: Grounding Language Understanding, 2017Konferensbidrag (Refereegranskat)
  • 396.
    Selin, Magnus
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Centra, Centrum för autonoma system, CAS. Linkoping Univ, Dept Comp & Informat Sci, S-58183 Linkoping, Sweden.
    Tiger, Maths
    Linkoping Univ, Dept Comp & Informat Sci, S-58183 Linkoping, Sweden..
    Duberg, Daniel
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Centra, Centrum för autonoma system, CAS.
    Heintz, Fredrik
    Linkoping Univ, Dept Comp & Informat Sci, S-58183 Linkoping, Sweden..
    Jensfelt, Patric
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Centra, Centrum för autonoma system, CAS.
    Efficient Autonomous Exploration Planning of Large-Scale 3-D Environments2019Ingår i: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, nr 2, s. 1699-1706Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Exploration is an important aspect of robotics, whether it is for mapping, rescue missions, or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this letter, we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries.

  • 397.
    Shao, Wen-Ze
    et al.
    NUPT, Coll Telecommun & Informat Engn, Nanjing, Jiangsu, Peoples R China.;NUPT, Natl Engn Res Ctr Commun & Networking, Nanjing, Jiangsu, Peoples R China..
    Ge, Qi
    NUPT, Coll Telecommun & Informat Engn, Nanjing, Jiangsu, Peoples R China..
    Wang, Li-Qian
    NUPT, Coll Telecommun & Informat Engn, Nanjing, Jiangsu, Peoples R China..
    Lin, Yun-Zhi
    Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA.;Southeast Univ, Sch Automat, Nanjing, Jiangsu, Peoples R China..
    Deng, Hai-Song
    Nanjing Audit Univ, Sch Sci, Nanjing, Jiangsu, Peoples R China..
    Li, Haibo
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Medieteknik och interaktionsdesign, MID. NUPT, Coll Telecommun & Informat Engn, Nanjing, Jiangsu, Peoples R China.
    Nonparametric Blind Super-Resolution Using Adaptive Heavy-Tailed Priors2019Ingår i: Journal of Mathematical Imaging and Vision, ISSN 0924-9907, E-ISSN 1573-7683, Vol. 61, nr 6, s. 885-917Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Single-image nonparametric blind super-resolution is a fundamental image restoration problem yet largely ignored in the past decades among the computational photography and computer vision communities. An interesting phenomenon is observed that learning-based single-image super-resolution (SR) has been experiencing a rapid development since the boom of the sparse representation in 2005s and especially the representation learning in 2010s, wherein the high-res image is generally blurred by a supposed bicubic or Gaussian blur kernel. However, the parametric assumption on the form of blur kernels does not hold in most practical applications because in real low-res imaging a high-res image can undergo complex blur processes, e.g., Gaussian-shaped kernels of varying sizes, ellipse-shaped kernels of varying orientations, curvilinear kernels of varying trajectories. The paper is mainly motivated by one of our previous works: Shao and Elad (in: Zhang (ed) ICIG 2015, Part III, Lecture notes in computer science, Springer, Cham, 2015). Specifically, we take one step further in this paper and present a type of adaptive heavy-tailed image priors, which result in a new regularized formulation for nonparametric blind super-resolution. The new image priors can be expressed and understood as a generalized integration of the normalized sparsity measure and relative total variation. Although it seems that the proposed priors are simple, the core merit of the priors is their practical capability for the challenging task of nonparametric blur kernel estimation for both super-resolution and deblurring. Harnessing the priors, a higher-quality intermediate high-res image becomes possible and therefore more accurate blur kernel estimation can be accomplished. A great many experiments are performed on both synthetic and real-world blurred low-res images, demonstrating the comparative or even superior performance of the proposed algorithm convincingly. Meanwhile, the proposed priors are demonstrated quite applicable to blind image deblurring which is a degenerated problem of nonparametric blind SR.

  • 398. Sharbafi, M. A.
    et al.
    Taleghani, S.
    Esmaeili, E.
    Haghighat, A. T.
    Aghazadeh, Omid
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    ICE matching, a novel approach for localization problem2010Ingår i: ICCAS 2010 - International Conference on Control, Automation and Systems, IEEE , 2010, s. 1904-1907Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a novel technique for scan matching. The method is based on the family of feature to feature matching approaches. Our innovative method named ICE matching leads to a fast and accurate solution to solve the challenges of localization problem. Novelty in defining new features, matching mechanism and new state estimation approach, congregated in this method, creates a robust practical technique in terms of accuracy and convergence rate. Furthermore, The Comparison with some high quality scan matching methods from different viewpoints illustrates the performance of ICE matching.

  • 399. Shin, Grace
    et al.
    Choi, Taeil
    Rozga, Agata
    Romero, Mario
    Georgia Institute of Technology.
    VizKid: A Behavior Capture and Visualization System of Adult-child Interaction2011Ingår i: Proceedings of the 1st International Conference on Human Interface and the Management of Information: Interacting with Information - Volume Part II, 2011, s. 190-198Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present VizKid, a capture and visualization system for supporting the analysis of social interactions between two individuals. The development of this system is motivated by the need for objective measures of social approach and avoidance behaviors of children with autism. VizKid visualizes the position and orientation of an adult and a child as they interact with one another over an extended period of time. We report on the design of VizKid and its rationale.

  • 400.
    Shirabe, Takeshi
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Samhällsplanering och miljö, Geoinformatik.
    Drawing with geography2015Ingår i: Lecture Notes in Geoinformation and Cartography, 2015, s. 327-341Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method is proposed to assist spatial planners in drawing with ‘geographic’ constraints. These constraints constrain graphic objects to have certain relationships that are not limited to be (Euclidean) geometric or topological but allowed to be dependent on the spatial variation of selected conditions (e.g., elevation and vegetation) characterizing an underlying geographic space. Just as in existing computer-aided design systems, the method accepts a manual change to a graphic object or constraint, and updates all affected graphic objects accordingly. The paper discusses how such a method is motivated and improves the graphic editing capability of geographic information systems, and identifies key issues for its implementation.

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