Bayesian Integration of a Discrete Choice Pedestrian Behavioral Model and Image Correlation Techniques for Automatic Multi Object Tracking

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.


Published in:
2004 IEEE International Conference on Image Processing, ICIP2004, 2, 1037-1040
Presented at:
2004 IEEE International Conference on Image Processing, ICIP2004, Singapore, 24-27 Oct. 2004
Year:
2004
Publisher:
IEEE
ISBN:
0-7803-8554-3
Keywords:
Laboratories:




 Record created 2006-06-14, last modified 2018-03-18

n/a:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)