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Real-time Pose Detection and Tracking of Hundreds of Objects
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-3731-0582
2015 (English)In: IEEE transactions on circuits and systems for video technology (Print), ISSN 1051-8215, E-ISSN 1558-2205Article in journal (Refereed) Published
Abstract [en]

We propose a novel model-based method for tracking the six-degrees-of-freedom (6DOF) pose of a very large number of rigid objects in real-time. By combining dense motion and depth cues with sparse keypoint correspondences, and by feeding back information from the modeled scene to the cue extraction process, the method is both highly accurate and robust to noise and occlusions. A tight integration of the graphical and computational capability of graphics processing units (GPUs) allows the method to simultaneously track hundreds of objects in real-time. We achieve pose updates at framerates around 40 Hz when using 500,000 data samples to track 150 objects using images of resolution 640x480. We introduce a synthetic benchmark dataset with varying objects, background motion, noise and occlusions that enables the evaluation of stereo-vision-based pose estimators in complex scenarios. Using this dataset and a novel evaluation methodology, we show that the proposed method greatly outperforms state-of-the-art methods. Finally, we demonstrate excellent performance on challenging real-world sequences involving multiple objects being manipulated.

Place, publisher, year, edition, pages
IEEE Press, 2015.
Keyword [en]
Benchmarking; graphics processing unit (GPU); model-based object pose estimation; optical flow; real time; stereo
National Category
Robotics Robotics
Identifiers
URN: urn:nbn:se:kth:diva-165635DOI: 10.1109/TCSVT.2015.2430652ISI: 000390423900004Scopus ID: 2-s2.0-84977503169OAI: oai:DiVA.org:kth-165635DiVA: diva2:808735
Note

QC 20161111

Available from: 2015-04-29 Created: 2015-04-29 Last updated: 2017-11-13Bibliographically approved

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Pauwels, Karl

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
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  • Other locale
More languages
Output format
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