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- AI MAGAZINE , 1988
Active stereo-integrating disparity, vergence, focus, aperture, and calibration for surface estimation
- IEEE Trans. Pattern Anal. Machine. Intell , 1993
"... Abstract-Much research has emphasized stereo disparity as a source of depth information. To a lesser extent, camera vergence and lens focus have also been investigated for their utility in depth recovery. Each of these visual cues exhibits shortcomings when used individually in the sense that none a ..."
Abstract - Cited by 26 (2 self) - Add to MetaCart
Abstract-Much research has emphasized stereo disparity as a source of depth information. To a lesser extent, camera vergence and lens focus have also been investigated for their utility in depth recovery. Each of these visual cues exhibits shortcomings when used individually in the sense that none alone can be used to reconstruct surfaces for real scenes that often cover a wide field of view and a large range of depth. This paper presents an approach to integration of these cues that attempts to exploit their complementary strengths and weaknesses through active control of camera focus and orientations. In addition, the aperture and zoom settings of the cameras are controlled. The result is an active vision system that dynamically and cooperatively interleaves image acquisition with surface estimation. A dense composite map of a single contiguous surface is synthesized by automatically scanning the surface and combining estimates of adjacent, local surface patches. This problem is formulated as one of minimizing a pair of objective functions. The first such function is concerned with the selection of a target for fixation. The second objective function guides the surface estimation process in the vicinity of the fixation point. Calibration parameters of the cameras are treated as variables during optimization, thus making camera calibration an integral, flexible component of surface estimation. An implementation of this method is described, and a performance evaluation of the system is presented. An average absolute error of less than 0.15 % in estimated depth was achieved for a large surface having a depth of approximately 2 m. Index Terms-Active vision, camera calibration, fixation, range from focus, range from stereo, range from vergence, surface estimation, visual cue integration, visual target selection. I.