Video-Base people counting and gender recognition

Authors:
Yuen Sum Wong;Cho Wing Tam;Siu Mo Lee;Chuen Pan Chan;Hong Fu
Affiliations:
Department of Computer Science, Chu Hai College of Higher Education, Hong Kong;Department of Computer Science, Chu Hai College of Higher Education, Hong Kong;Department of Computer Science, Chu Hai College of Higher Education, Hong Kong;Department of Computer Science, Chu Hai College of Higher Education, Hong Kong;Department of Computer Science, Chu Hai College of Higher Education, Hong Kong
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Year:
2012

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Abstract

Video based people counting and gender recognition are important but challenging tasks. A neural network method for video-base people counting and gender recognition is proposed in this paper. A multilayer perceptron structure is constructed and meaningful features from target video are extracted as input. The neural network is trained by back-propagation training algorithm. This method is experimented on four videos, including more than 240 peoples. Experiment results have shown the effectiveness of this method.