A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Real-time people localization and tracking through fixed stereo vision
Applied Intelligence
Understanding transit scenes: a survey on human behavior-recognition algorithms
IEEE Transactions on Intelligent Transportation Systems
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Because a people detection system that considers only a single feature tends to be unstable, many people detection systems that consider multiple features simultaneously have been proposed. These detection systems usually integrate features using a heuristic method based on the designers' observations and induction. Whenever the number of features to be considered is changed, the designer must change and adjust the integration mechanism accordingly. To avoid this tedious process, we propose a multi-modal fusion system that can detect and track people in a scalable, accurate, robust and flexible manner. Each module considers a single feature and all modules operate independently at the same time. The outputs from the individual modules are integrated together and tracked using a Kalman filter.