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conference paper
Bayesian Integration of a Discrete Choice Pedestrian Behavioral Model and Image Correlation Techniques for Automatic Multi Object Tracking
2004
2004 IEEE International Conference on Image Processing, ICIP2004
In this paper we deal with the multi-object tracking problem in the particular case of pedestrians, assuming the detection step already done. We use a Bayesian framework to combine the likelihood term provided by an image correlation algorithm with a prior distribution given by a discrete choice model for pedestrian behavior, calibrated on real data. We aim to show how the combination of the image information with a model of pedestrian behavior can provide appreciable results in real and complex scenarios.
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Venegas2004_773.pdf
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