A robust algorithm for feature point matching

Image matching is a key problem of computer vision and frequently used in 3D-model reconstruction, object recognition, image alignment, camera self-calibration and so on. Feature point matching is the most common one among all kinds of image matching. The result of feature point matching is affected greatly by many factors, such as object occlusions, lighting conditions and noises, therefore it is important to find a robust algorithm of feature point matching. In this paper, we extend the method for standard assignment algorithm to solve extended assignment problem and propose a new feature point matching algorithm. It employs the condition that the depth of the scene is local continuous as extra constraint, and uses the method for extended assignment problem to do global optimization. Moreover. this algorithm only needs two optimizations and can be implemented with almost complete matrix computation. so its efficiency is higher than the existing algorithms. Experiments show that the results of the algorithm are satisfactory. (C) 2002 Elsevier Science Ltd. All rights reserved.