Tracking and data association
Fundamentals of digital image processing
Fundamentals of digital image processing
Precision Tracking Based on Segmentation with Optimal Layering for Imaging Sensors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Precision tracking based-on fuzzy reasoning segmentation in cluttered image sequences
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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In our previous work [J. Cho, D. Kim, D. Park, Robust centroid target tracker based on new distance features in cluttered image sequences. IEICE Transactions on Information and Systems, Vol. E83-D, No. 12, December, 2000.], we presented a novel centroid target tracker based on new distance features in cluttered image sequences. A real-time adaptive segmentation method based on new distance features was proposed for the binary centroid tracker. The target classifier by the Bayes decision rule for minimizing the probability of error should properly estimate the state-conditional densities. In this correspondence, the proposed target classifier adopts the fuzzy-reasoning segmentation instead of the estimation of the state-conditional probability densities. Comparative experiments show that the performance of the proposed fuzzy-reasoning segmentation is superior to that of the conventional thresholding methods. The usefulness of the fuzzy-reasoning segmentation for practical applications is demonstrated by considering two sequences of real target images. The tracking results are good and stable without difficulty of the probability densities estimation.