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Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona 85287-8809, USA.
This paper proposes an approach to rectifying two images of the same scene captured by cameras at general positions so that the results form a stereo pair that satisfies the constraints of the stereoscopic visualization platforms. This is unlike conventional image rectification research that primarily focuses on making stereo matching easier but pays little attention to 3D viewing. The novel derivation of the rectification algorithm also has an intuitive physical meaning that is not available from conventional approaches. Practical issues related to wide-baseline rectification and operation range of the proposed method are analyzed. Both simulated and real data experiments are used to assess the performance of the proposed algorithm.
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