| Summary: | In the 1960s, a group of AI researchers came to the conclusion that automatic depth recovery by two cameras and a computer was a simple task, and conquerable within an estimated five to ten years. Emboldened by the Information Gestalt theories, which affirm that the task is at least tractable, the field of machine vision was born. Forty years later, the problem is still far from being solved, and is still a very active field of study. This thesis summarizes the developments which have taken place in stereo vision research since its inception. The various solutions which have been developed are described and their deficiencies noted. An approach to generating depth maps from stereo image pairs is proposed. This technique is suitable for implementation on low cost computing hardware and is intended top provide assistance to a human operator. Results are presented which show the operation of this system on synthetic and natural images and the observed performance is analysed and discussed. The discussion covers many of the issues which cannot normally be found in a standard searcjh of the literature and brings them together in one location.
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