Using adaptive tracking to classify and monitor activities in a site

Author

Grimson, W.E.L. ; Stauffer, C. ; Romano, R. ; Lee, L.

Author_Institution

Artificial Intelligence Lab., MIT, Cambridge, MA, USA

fYear

1998

fDate

23-25 Jun 1998

Firstpage

22

Lastpage

29

Abstract

We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker detects multiple moving objects in the sensors. Our hypothesis is that motion tracking is sufficient to support a range of computations about site activities. We demonstrate using the tracked motion data to calibrate the distributed sensors, to construct rough site models, to classify detected objects, to learn common patterns of activity for different object classes, and to detect unusual activities

Keywords

adaptive estimation; computer vision; motion estimation; security; surveillance; adaptive tracker; adaptive tracking; distributed sensors; motion tracking; multiple moving objects; rough site models; site activities; tracked motion data; vision system; Cameras; Event detection; Intelligent sensors; Machine vision; Monitoring; Motion detection; Object detection; Robustness; Sensor systems; Tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on

Conference_Location

Santa Barbara, CA

ISSN

1063-6919

Print_ISBN

0-8186-8497-6

Type

conf

DOI

10.1109/CVPR.1998.698583

Filename

698583