Real-time keypoints matching: application to visual servoing

Many computer vision problems such as recognition, image retrieval, and tracking require matching two images. Currently, ones try to find as reliable as possible matching techniques with a very little constraint of computational time. In this paper, we are interested in applying image matching technique into robotic problems such as visual servoing in which the computational time is a critical element. We propose in this paper a real time keypoint based matching method. The novelties of this method include a fast corner detector, a compact corner descriptor based on principal component analysis (PCA) technique and an efficient matching with help of approximate nearest neighbor (ANN) technique. We show that the method gives a very satisfying result on accuracy as well as the computational time. The matching algorithm is applied to control a robot in a visual servoing application. It works at 10-14Hz and is well robust to variations in 3D viewpoint and illumination.