Background modeling for segmentation of video-rate stereo sequences

被引：48

作者：

Eveland, C ^{[1
]}

Konolige, K ^{[1
]}

Bolles, RC ^{[1
]}

机构：

[1] Univ Rochester, Dept Comp Sci, Rochester, NY 14627 USA

来源：

1998 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS | 1998年

关键词：

D O I：

10.1109/CVPR.1998.698619

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Stereo sequences promise to be a powerful method for segmenting images for applications such as tracking human figures. We present a method of statistical background modeling for stereo sequences that improves the reliability and sensitivity of segmentation in the presence of object clutter The dynamic version of the method called gated background adaptation, can reliably learn background statistics in the presence of corrupting foreground motion. The method has been used with a simple head discriminator to defect and track people using a stereo head mounted on a pan/tilt platform. It runs at video rates using standard PC hardware.

引用

页码：266 / 271

页数：6