Multi-image matching for a general motion stereo camera model

Abstract This paper presents an accurate and robust motion stereo algorithm employing multiple images, taken under a general motion. The object functions for individual stereo pairs are represented, in terms of the depth, then these object functions are integrated, considering the positions of cameras and the shape of the object functions. By integrating the general motion stereo images, we not only reduce the ambiguities in correspondence, but also improve the accuracy of reconstruction. Also, by introducing a weight for each object function and selecting only reliable object functions, we can improve the accuracy greatly and eliminate false matches, caused by occlusion or noise. Experimental results on the synthetic and real data sets are presented to demonstrate the performance of the proposed algorithm.