A Machine Vision Architecture for Passive Depth Perception  and Scene Analysis (Computer and Information Science)
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This research is aimed at building a machine vision system              for visual depth and scene analysis.  The system is a passive                   system which simulates the accommodation of human vision system                 by taking and analyzing images with adjustable internal camera                  parameters.  Compared with the previous passive systems, the                    greatest advantage of the proposed system is that it can provide                a complete depth map of a scene, which permits the development of               a paradigm for the extraction of the 3-D structures in a scene.                 Also, it has some advantages over the active systems in the task                of image segmentation along the direction of depth.  Because of                 these advantages, the proposed system has some of the most                      desirable capabilities which may lead to better depth finding                   techniques.                                                                             The first task of this research is to develop a general                 theory for the system based on a preliminary mathematical                       analysis.  This analysis will be followed by an investigation of                several simplified methods for the depth recovery based on the                  system, since the 3-D data provided by the system is in a special               form with implicit depth information in it.  The advantages of                  the system over other machine vision systems will be                            experimentally determined, in particular.
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