Video-based human body tracking using color segmentation often causes problems due to movements of the object or changes in the global illumination parameters. In this paper the innuence of varying lighting conditions and large object movements in space is measured and analysed. For color segmentation an eecient technique for histogram-classiication is used. Based on the measurement results we propose a simple method to combine the histograms of several measurements which improves the segmentation. The method leads to an automatic calibration procedure which allows stable segmentation under varying lighting conditions. Finally, an application of this method to a model-based person tracking system is described.
[1]
James L. Crowley,et al.
Vision for man machine interaction
,
1995
.
[2]
Michael Hoch,et al.
A prototype system for intuitive film planning
,
1998,
Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.
[3]
Sven Schrr,et al.
Automatic Calibration of Lookup-tables for Color Image Segmentation
,
1997
.
[4]
Alex Pentland,et al.
Real-time self-calibrating stereo person tracking using 3-D shape estimation from blob features
,
1996,
Proceedings of 13th International Conference on Pattern Recognition.