A real-time adaptive segmentation method based on new distance features is proposed for the binary centroid tracker. These novel features are the distances between the predicted center pixel of a target object, measured by a tracking filter, and each pixel in the extraction of a moving target. The proposed method restricts clutters with target-like intensity from entering a tracking window and has low computational complexity for real-time applications compared with other complex feature-based methods. Comparative experiments show that the proposed method is superior to other segmentation methods based on intensity features in target detection and tracking.
Robust centroid target tracker based on new distance features in cluttered image sequences
IEICE Transactions on Information and Systems ; E83-D , 12 ; 2142-2151
2000
10 Seiten, 29 Quellen
Aufsatz (Zeitschrift)
Englisch
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