Surface Reconstruction By Dynamic Integration Of Focus, Camera Vergence, And Stereo

This paper concerns estimation of surface maps for real scenes having a wide field of view and a wide range of depths. Much research has emphasized stereo disparity as a source of depth information. To a lesser extent, camera focus and camera vergence have also been investigated for their utility in depth recovery. We argue that these sources of visual information have mutually complementary strengths and weaknesses, and to obtain surface maps for real scenes these processes must be integrated. Such integration requires active control of camera orientations and imaging parameters to dynamically and cooperatively interleave image acquisition with surface estimation. Accordingly, a global surface map of the visual field is synthesized by systematically scanning the scene, and combining estimates of adjacent, local surface patches, each acquired by an intermediate camera configuration and having a small depth range. We present an algorithm to perform this integration, and describe its implementation on a dynamic stereo-camera imaging system. Experimental results are presented to demonstrate the superior performance of the integrated system over that of each of its components.