Robust object detection based on local similar structure statistical matching

We present a robust object detection method to detect generic objects with incompact, complex and changeable shapes without training. First, we build a composite template set, which contains changeful shapes, scales and viewpoints of an interested object class, extract the local structure features from the composite template set and simplify them to construct a non-similar local structure feature set of the object class. Then, we propose a matching method of local similar structure statistical matching (LSSSM) to obtain the similarity image from a test image to the local structure feature set. Finally, we use the method of non-maxima suppression in the similarity image to extract the object position and mark the object in the test image. The experimental results demonstrate that our approach performs effectively on the face and infrared human body detection.