Searching for the corresponding fragments and points on several images of the same scene is one of the central problems in many applications: autonomous navigation extended landmarks, pattern recognition, 3D-scene reconstruction, etc. To solve this problem, various correlation methods for the similarity analysis of fragments are used. Algorithms based on these methods have a high computational complexity. In this paper we consider a stereo matching algorithm for 3D-scene reconstruction. We propose a computational scheme that improves the performance of this algorithm. This computational scheme is implemented using CUDA technology. A high degree of parallelism is achieved due to a large number of the same operations for corresponding points on epipolar lines. Numerical experiments were carried out using the proposed parallel algorithm. The resulting speed-up is estimated.

Keywords: stereo matching, 3D reconstruction, projective geometry, epipolar geometry, parallel computing, graphics processors, CUDA technology.

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