Automated detection of human for visual surveillance system
- 1 January 1996
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 3 (10514651) , 865-869 vol.3
- https://doi.org/10.1109/icpr.1996.547291
Abstract
This paper describes a robust and reliable method of human detection for visual surveillance systems. The merit of this method is to use simple shape parameters of silhouette patterns to classify humans from other moving objects such as butterflies and autonomous factory vehicles. An extra function based on the brightness level transformation is used to extract the precise shape of the silhouette patterns. An approach to overcome the occlusions of humans is also proposed. We tested our method for 2,500 images (1,100 from humans and 1,400 from other moving objects). Our test system detected the humans at the rate of 98% (=1,077/1,100) and judged 92% (=1,283/1,400) of the other moving objects as non-humans.Keywords
This publication has 4 references indexed in Scilit:
- Description and tracking of moving articulated objectsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Shadow and rhythm as sign patterns of obstacle detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Model-based image analysis of human motion using constraint propagationIEEE Transactions on Pattern Analysis and Machine Intelligence, 1980
- A Threshold Selection Method from Gray-Level HistogramsIEEE Transactions on Systems, Man, and Cybernetics, 1979