An evolutionary framework for stereo correspondence

In this paper we propose an evolutionary framework to establish feature correspondence from two uncalibrated images. By minimizing a proposed cost function, we match the feature points, discard the outliers and recover the epipolar geometry in one step. The unifying framework is furnished by genetic algorithm. We also create a new genetic operator to exchange the information between match process and robust epipolar line estimation so that epipolar geometry constraint can be elegantly incorporated into match process. Experiments on synthetic and real images show that this approach is very effective and fast