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Robust correction of 3D geo-metadata in photo collections by forming a photo grid
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0003-3779-5647
2011 (English)In: Wireless Communications and Signal Processing (WCSP), 2011 International Conference on, IEEE , 2011, 1-5 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we present a technique for efficient and robust estimation of the exact location and orientation of a photo capture device in a large data set. The provided data set includes a set of photos and the associated information from GPS and orientation sensor. This attached metadata is noisy and lacks precision. Our strategy to correct this uncertain data is based on the data fusion between measurement model, derived from sensor data, and signal model given by the computer vision algorithms. Based on the retrieved information from multiple views of a scene we make a grid of images. Our robust feature detection and matching between images result in finding a reliable transformation. Consequently, relative location and orientation of the data set construct the signal model. On the other hand, information extracted from the single images combined with the measurement data make the measurement model. Finally, Kalman filter is used to fuse these two models iteratively and enhance the estimation of the ground truth(GT) location and orientation. Practically, this approach can help us to design a photo browsing system from a huge collection of photos, enabling 3D navigation and exploration of our huge data set.

Place, publisher, year, edition, pages
IEEE , 2011. 1-5 p.
Keyword [en]
Kalman filters, computer vision, feature extraction, image fusion, image matching, image retrieval, information retrieval, iterative methods, meta data, 3D geometadata, 3D navigation, GPS, GT orientation, Kalman filter, computer vision algorithms, data fusion, data set, ground truth location, image grid, information extraction, iterative fusion, measurement model, orientation sensor, photo browsing system, photo capture device, photo collections, photo grid, robust correction, robust estimation, robust feature detection, sensor data, signal model, Cameras, Computational modeling, Data models, Estimation, Noise, Noise measurement, Uncertainty
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-141823DOI: 10.1109/WCSP.2011.6096689Scopus ID: 2-s2.0-84555186863OAI: oai:DiVA.org:kth-141823DiVA: diva2:698785
Conference
WCSP 2011
Note

QC 20140226

Available from: 2014-02-25 Created: 2014-02-25 Last updated: 2016-04-26Bibliographically approved
In thesis
1. 3D Gesture Recognition and Tracking for Next Generation of Smart Devices: Theories, Concepts, and Implementations
Open this publication in new window or tab >>3D Gesture Recognition and Tracking for Next Generation of Smart Devices: Theories, Concepts, and Implementations
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The rapid development of mobile devices during the recent decade has been greatly driven by interaction and visualization technologies. Although touchscreens have signicantly enhanced the interaction technology, it is predictable that with the future mobile devices, e.g., augmentedreality glasses and smart watches, users will demand more intuitive in-puts such as free-hand interaction in 3D space. Specically, for manipulation of the digital content in augmented environments, 3D hand/body gestures will be extremely required. Therefore, 3D gesture recognition and tracking are highly desired features for interaction design in future smart environments. Due to the complexity of the hand/body motions, and limitations of mobile devices in expensive computations, 3D gesture analysis is still an extremely diffcult problem to solve.

This thesis aims to introduce new concepts, theories and technologies for natural and intuitive interaction in future augmented environments. Contributions of this thesis support the concept of bare-hand 3D gestural interaction and interactive visualization on future smart devices. The introduced technical solutions enable an e ective interaction in the 3D space around the smart device. High accuracy and robust 3D motion analysis of the hand/body gestures is performed to facilitate the 3D interaction in various application scenarios. The proposed technologies enable users to control, manipulate, and organize the digital content in 3D space.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. xii, 101 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 14:02
Keyword
3D gestural interaction, gesture recognition, gesture tracking, 3D visualization, 3D motion analysis, augmented environments
National Category
Engineering and Technology
Research subject
Media Technology
Identifiers
urn:nbn:se:kth:diva-141938 (URN)978-91-7595-031-0 (ISBN)
Public defence
2014-03-17, F3, Lindstedtsvägen 26, KTH, Stockholm, 13:15 (English)
Opponent
Supervisors
Note

QC 20140226

Available from: 2014-02-26 Created: 2014-02-26 Last updated: 2014-02-26Bibliographically approved

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Li, Haibo

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