A rectification algorithm for un-calibrated multi-view images based on SIFT features

In this paper, we present an efficient rectification algorithm for un-calibrated multi-view images based on SIFT (Scale-invariant feature transform) feature matching. Un-calibrated rectification is necessary for some specific occasions and we extend generic stereo pair rectification to multi-view camera array with projection shift method. We bring in SIFT algorithm to extract and match features (key points) automatically. Block-division features extraction method is proposed and RANSAC is used to improve precision of rectifying transformation. From the experiments, we find that our method is effective to rectify parallel cameras array. Rectified images have uniform horizontal disparities and the vertical mismatches between adjacent views are eliminated.

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