Integrated Motion Detection and Tracking for Visual Surveillance

Authors:
Mohamed F. Abdelkader;Rama Chellappa;Qinfen Zheng;Alex L. Chan
Affiliations:
University of Maryland;University of Maryland;University of Maryland;U. S. Army Research Laboratory (ARL), MD
Venue:
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Year:
2006

Citing 0
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Abstract

Visual surveillance systems have gained a lot of interest in the last few years. In this paper, we present a visual surveillance system that is based on the integration of motion detection and visual tracking to achieve better performance. Motion detection is achieved using an algorithm that combines temporal variance with background modeling methods. The tracking algorithm combines motion and appearance information into an appearance model and uses a particle filter framework for tracking the object in subsequent frames. The systems was tested on a large ground-truthed data set containing hundreds of color and FLIR image sequences. A performance evaluation for the system was performed and the average evaluation results are reported in this paper.