A combined two-stage local-spatial interest point matching algorithm

A local-spatial interest point matching algorithm for articulated human upper body tracking application is proposed in this paper. The first stage finds confidently matched pairs of interest points from the reference and target interest point lists through a local-feature-descriptors-based matching method. Applying two cross-checking and displacement-checking steps reduces the number of mismatched pairs and results confidently matched pairs. Using these confidently matched pairs, the second stage recovers more matched interest point pairs from the remaining unmatched through the graph matching by a cyclic string matching algorithm. The proposed approach benefits from the speed of local matching algorithms as well as the accuracy and robustness of spatial matching methods. In addition, it compensates for the reference list leakage problem. Experimental results show that the combined two-stage interest matching method efficiently improves the matching process for articulated human upper body tracking.