Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral Segmentation with Multiscale Graph Decomposition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Vehicle Count in the Presence of Multiple-Vehicle Occlusions in Traffic Images
IEEE Transactions on Intelligent Transportation Systems
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A novel method is proposed for solving the shadow and occlusion problems of vehicle analysis. Kalman filter is combined with random walk algorithm. First, the computation region of random walk is reduced through the prediction information from the Kalman filter, then the seed points is extracted in this region for segmentation. Further, the segmentation of random walk is implemented, and the results of which is used to update the filter parameters. In order to obtain the initial state vector for Kalman filter, the random walk based on car bottom shadow is proposed too. Experiment results show that the problem of moving vehicles shadows, tracking and occlusion can be solved.