Comparative study of people detection in surveillance scenes

Authors:
A. Negre;H. Tran;N. Gourier;D. Hall;A. Lux;J. L. Crowley
Affiliations:
Institut National Polytechnique de Grenoble, Laboratory GRAVIR, INRIA Rhone-Alpes, France;Institut National Polytechnique de Grenoble, Laboratory GRAVIR, INRIA Rhone-Alpes, France;Institut National Polytechnique de Grenoble, Laboratory GRAVIR, INRIA Rhone-Alpes, France;Institut National Polytechnique de Grenoble, Laboratory GRAVIR, INRIA Rhone-Alpes, France;Institut National Polytechnique de Grenoble, Laboratory GRAVIR, INRIA Rhone-Alpes, France;Institut National Polytechnique de Grenoble, Laboratory GRAVIR, INRIA Rhone-Alpes, France
Venue:
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2006

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Abstract

We address the problem of determining if a given image region contains people or not, when environmental conditions such as viewpoint, illumination and distance of people from the camera are changing. We develop three generic approaches to discriminate between visual classes: ridge-based structural models, ridge-normalized gradient histograms, and linear auto-associative memories. We then compare the performance of these approaches on the problem of people detection for 26 video sequences taken from the CAVIAR database.