Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
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In this paper we propose a fast template matching method which can handle various types of objects. In our method the discretized orientations of image gradients which are robust to illumination changes and clutterd backgrounds are used as features. The features are binary represented and they can be matched very fast using bitwise operations. Furthermore, the rotated and resized templates those have similar feature vectors are clustered to one template and the total number of templates are greatly reduced, which boosts the detection speed. The experimental results show that our method can detect target objects (the search space includes translation, ±180 deg rotation, and ±50% scale change) with sub-pixel accracy in real-time.