A fast background scene modeling and maintenance for outdoor surveillance

被引：0
|
作者：
Haritaoglu, I [1 ]
Harwood, D [1 ]
Davis, LS [1 ]
机构：
[1] IBM Corp, Almaden Res, San Jose, CA 95120 USA
来源：
15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 4, PROCEEDINGS: APPLICATIONS, ROBOTICS SYSTEMS AND ARCHITECTURES | 2000年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We described fast background scene modeling and maintenance techniques for real time visual surveillance system for tracking people in an outdoor environment. It operates on monocular grayscale video imagery, or on video imagery from an infrared camera. The system learns and models background scene statistically to detect foreground objects, even when the background is not completely stationary (e.g. motion of tree branches) using shape and motion cues. Also a background maintenance model is proposed for preventing maintenance model is proposed for preventing false positives, such as, illumination changes (the sun being blocked by clouds causing changes in brightness), or false negative, such as, physical changes (person detection while he is getting out of the parked car). Experimental results demonstrate robustness and real-time performance of the algorithm.
引用
收藏
页码：179 / 183
页数：5
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