CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Learning the Statistics of People in Images and Video
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
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In this paper, we examine sensor specific distributions of local image operators (edge and line detectors), which describe the appearance of people in video sequences. The distributions are used to describe a probabilistic articulated motion model to track the gestures of a person in terms of arms and body movement, which is solved using a particle filter. We focus on modeling the statistics of one sensor and examine the influence of image noise and scale, and the spatial accuracy that is obtainable. Additionally spatial correlation between pixels is modeled in the appearance model. We show that by neglecting the correlation high detection probabilities are quickly overestimated, which can often lead to false positives. Using the weighted geometric mean of pixel information leads to much improved results.