Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/84203
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Type: Conference paper
Title: Real-time tracking of multiple occluding objects using level sets
Author: Bibby, C.
Reid, I.
Citation: Proceedings of 23rd IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010 / pp.1307-1314
Publisher: IEEE
Publisher Place: USA
Issue Date: 2010
Series/Report no.: IEEE Conference on Computer Vision and Pattern Recognition
ISBN: 9781424469840
ISSN: 1063-6919
Conference Name: IEEE Conference on Computer Vision and Pattern Recognition (23rd : 2010 : San Francisco, CA)
Statement of
Responsibility: 
Charles Bibby and Ian Reid
Abstract: We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth ordering of the objects being tracked in the scene. The method uses the observed image data to compute a posterior over the objects' poses, shapes and relative depths. The poses are group transformations, the shapes are implicit contours represented using level-sets and the relative depths give the discrete depth ordering of the objects. All nuisance variables are marginalised out at the pixel-level resulting in a pixel-wise posterior, as opposed to a pixel-wise likelihood, and we show using quantitative results that this provides increased resilience to noise. We also demonstrate how motion models can be incorporated within the same probabilistic framework and show how this enables the system to track complete occlusions. The effectiveness of our method is demonstrated on a variety of challenging video sequences.
Rights: ©2010 IEEE
RMID: 0020131208
DOI: 10.1109/CVPR.2010.5539818
Appears in Collections:Computer Science publications

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