Multiple-object tracking in cluttered and crowded public spaces
conference contribution
posted on 2010-01-01, 00:00authored byR Martin, Ognjen Arandjelovic
This paper addresses the problem of tracking moving objects of variable appearance in challenging scenes rich with features and texture. Reliable tracking is of pivotal importance in surveillance applications. It is made particularly difficult by the nature of objects encountered in such scenes: these too change in appearance and scale, and are often articulated (e.g. humans). We propose a method which uses fast motion detection and segmentation as a constraint for both building appearance models and their robust propagation (matching) in time. The appearance model is based on sets of local appearances automatically clustered using spatio-kinetic similarity, and is updated with each new appearance seen. This integration of all seen appearances of a tracked object makes it extremely resilient to errors caused by occlusion and the lack of permanence of due to low data quality, appearance change or background clutter. These theoretical strengths of our algorithm are empirically demonstrated on two hour long video footage of a busy city marketplace.
History
Pagination
89 - 98
Location
Las Vegas, Nevada
Start date
2010-11-29
End date
2010-12-01
ISBN-13
9783642172762
ISBN-10
3642172768
Language
eng
Publication classification
E1.1 Full written paper - refereed
Title of proceedings
ISVC 2010 : Advances in Visual Computing : Proceedings of the 6th international symposium on visual computing 2010