This paper proposes a novel weighted template matching method. It employs a generalized distance transform (GDT) and an orientation map (OM). The GDT allows us to weight the distance transform more on the strong edge points and the OM provides supplementary local orientation information for matching. Based on the matching method, a two-stage human detection method consisting of template matching and Bayesian verification is developed. Experimental results have shown that the proposed method can effectively reduce the false positive and false negative detection rates and perform superiorly in comparison to the conventional Chamfer matching method.
REF has proposed a novel template matching method known as Chamfer matching method.
A novel template matching method for human detection
2009 16th IEEE International Conference on Image Processing (ICIP)
2009 16th IEEE International Conference on Image Processing (ICIP)
Computer Science