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Les Séminaires CerVIM, Université Laval ont lieu le vendredi à 11h00.
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Alejandro Sanchez
Laboratoire DAMAS

Vehicle detection and tracking in car video based on motion model


Jazayeri, A., Cai, H., Zheng, J.Y. and Tuceryan, M., Vehicle detection and tracking in car video based on motion model, IEEE Transactions on Intelligent Transportation Systems 2011, Volume 12, Issue 2, Pages 583 - 595.


The authors propose a comprehensive approach to localizing target vehicles in video under various environmental conditions. The extracted geometry features from the video are continuously projected onto a 1-D profile and are constantly tracked. They 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. They probabilistically model the motion in the field of view according to the scene characteristics and the vehicle motion model. The hidden Markov model (HMM) is used to separate target vehicles from the background and track them probabilistically. The proposed approach is robust and effective in dealing with changes in environment and illumination and indicates that real-time processing becomes possible for vehicle-borne cameras.


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