Abstract
One major problem of contour-based tracking is how to evaluate the accuracy of tracking results due to nonrigid and deformative properties of contours. We propose a shape context-based evaluation measure that considers the semantic shape similarity between the tracked contour and ground-truth contour. In addition, a pyramid match kernel is introduced for shape histogram matching, which can effectively deal with the contours with different scales. Experimental results demonstrate, compared to two start-of-art evaluation measures, our measure effectively captures the local shape information and thus is more consistent with human vision. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3633334]
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