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Vehicle Detection and Tracking in Car Video Based on Motion Model
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资源说明：Vehicle Detection and Tracking in Car Video Based on Motion Model--This work aims at real-time in-car video analysis to detect and track vehicles ahead for safety, auto-driving, and target tracing. This
paper describes a comprehensive approach to localize target vehicles in video under various environmental conditions. The extracted
geometry features from the video are projected onto a 1D profile continuously and are tracked constantly. We rely on temporal
information of features and their motion behaviors for vehicle identification, which compensates for the complexity in recognizing
vehicle shapes, colors, and types. We model the motion in the field of view probabilistically according to the scene characteristic and
vehicle motion model. The Hidden Markov Model is used for separating target vehicles from background, and tracking them
probabilistically. We have investigated videos of day and night on different types of roads, showing that our approach is robust and
effective in dealing with changes in environment and illumination, and that real time processing becomes possible for vehicle borne
cameras.
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