Tracking the invisible: Learning where the object might be

Grabner, Helmut and Matas, Jiri and Van Gool, Luc and Cattin, Philippe. (2010) Tracking the invisible: Learning where the object might be. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition. pp. 1285-1292.

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Official URL: https://edoc.unibas.ch/78934/

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Objects are usually embedded into context. Visual context has been successfully used in object detection tasks, however, it is often ignored in object tracking. We propose a method to learn supporters which are, be it only temporally, useful for determining the position of the object of interest. Our approach exploits the General Hough Transform strategy. It couples the supporters with the target and naturally distinguishes between strongly and weakly coupled motions. By this, the position of an object can be estimated even when it is not seen directly (e.g., fully occluded or outside of the image region) or when it changes its appearance quickly and significantly. Experiments show substantial improvements in model-free tracking as well as in the tracking of "virtual" points, e.g., in medical applications.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Imaging and Computational Modelling > Center for medical Image Analysis & Navigation (Cattin)
UniBasel Contributors:Cattin, Philippe Claude
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:26 Jan 2021 09:47
Deposited On:26 Jan 2021 09:47

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