Pedestrian detection and tracking in infrared imagery using shape and appearance
Computer Vision and Image Understanding
Robust tracking with and beyond visible spectrum: a four-layer data fusion framework
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Thermal cameras and applications: a survey
Machine Vision and Applications
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This paper introduces a layered representation for infrared imagery and studies its application into pedestrian detection and tracking. We present a generalized EM algorithm to decompose infrared images into background and foreground layers and study the phenomenon of polarity switch. We propose a hybrid (shape+appearance) algorithm for pedestrian detection, in which shape cue is first used to eliminate non-pedestrian moving objects and appearance cue is then used to pin down the location of pedestrians. We also formulate the problem of shot segmentation and present a graph matching-based pedestrian tracking algorithm. Experimental results with OSU Thermal Pedestrian Database are reported to demonstrate the excellent performance of our algorithms.