DocumentCode :
2654386
Title :
Vehicle segmentation by edge classification method and the S-T MRF model
Author :
Inoue, Hiroshi ; Liu, Mingzhe ; Kamijo, Shunsuke
Author_Institution :
Tokyo Univ.
fYear :
2006
fDate :
17-20 Sept. 2006
Firstpage :
1543
Lastpage :
1549
Abstract :
In this paper, we propose a tracking algorithm, which is based on the collaboration of the S-T MRF model and a dedicated segmentation algorithm. Although the S-T MRF model was designed to be robust against occlusion, it regards vehicles that move in parallel occluding each other from the beginning to the end of the traffic images as a single region. In order to compensate such a defect of S-T MRF, we have developed a dedicated segmentation algorithm which decides boundaries of vehicles contained in such a single region by referring to the difference of edge patterns among the vehicles. By the experiments using traffic video from three different angles at different locations, our method was proved to be very successful
Keywords :
Markov processes; edge detection; image classification; image segmentation; random processes; traffic engineering computing; S-T MRF model; edge classification; spatio-temporal Markov random field; tracking algorithm; traffic images; traffic video; vehicle segmentation; Cameras; Image segmentation; Image sensors; Labeling; Lighting; Monitoring; Pixel; Robustness; Surveillance; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems Conference, 2006. ITSC '06. IEEE
Conference_Location :
Toronto, Ont.
Print_ISBN :
1-4244-0093-7
Electronic_ISBN :
1-4244-0094-5
Type :
conf
DOI :
10.1109/ITSC.2006.1707443
Filename :
1707443
Link To Document :
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