Background modeling for segmentation of video-rate stereo sequences

• Published in: Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231) pp. 266 - 271
• Main Authors: Eveland, C., Konolige, K., Bolles, R.C.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 1998
• Subjects: Application software; Artificial intelligence; Computer science; Electrical capacitance tomography; Head; Humans; Image segmentation; Layout; Statistics; Tracking
• ISBN: 0818684976; 9780818684975
• ISSN: 1063-6919
• DOI: 10.1109/CVPR.1998.698619

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 detect and track people using a stereo head mounted on a pan/tilt platform. It runs at video rates using standard PC hardware.