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Essentials of fuzzy modeling and control
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CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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IEEE Transactions on Pattern Analysis and Machine Intelligence
MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets
IEEE Transactions on Pattern Analysis and Machine Intelligence
People detection and tracking using stereo vision and color
Image and Vision Computing
Fuzzy component based object detection
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Face detection and tracking using a Boosted Adaptive Particle Filter
Journal of Visual Communication and Image Representation
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IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
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International Journal of Approximate Reasoning
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International Journal of Approximate Reasoning
Multi-camera people tracking using evidential filters
International Journal of Approximate Reasoning
Description logic programs under probabilistic uncertainty and fuzzy vagueness
International Journal of Approximate Reasoning
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International Journal of Approximate Reasoning
Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning
International Journal of Approximate Reasoning
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Hierarchical and conditional combination of belief functions induced by visual tracking
International Journal of Approximate Reasoning
Fuzzy adaptive particle filter for localization of a mobile robot
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
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This paper describes a system capable of detecting and tracking various people using a new approach based on colour, stereo vision and fuzzy logic. Initially, in the people detection phase, two fuzzy systems are used to filter out false positives of a face detector. Then, in the tracking phase, a new fuzzy logic based particle filter (FLPF) is proposed to fuse stereo and colour information assigning different confidence levels to each of these information sources. Information regarding depth and occlusion is used to create these confidence levels. This way, the system is able to keep track of people, in the reference camera image, even when either stereo information or colour information is confusing or not reliable. To carry out the tracking, the new FLPF is used, so that several particles are generated while several fuzzy systems compute the possibility that some of the generated particles correspond to the new position of people. Our technique outperforms two well known tracking approaches, one based on the method from Nummiaro et al. [1] and other based on the Kalman/meanshift tracker method in Comaniciu and Ramesh [2]. All these approaches were tested using several colour-with-distance sequences simulating real life scenarios. The results show that our system is able to keep track of people in most of the situations where other trackers fail, as well as to determine the size of their projections in the camera image. In addition, the method is fast enough for real time applications.