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Temporal Surface Reconstruction

This thesis investigates the problem of estimating the three-dimensional structure of a scene from a sequence of images. Structure information is recovered from images continuously using shading, motion or other visual mechanisms. A Kalman filter represents structure in a dense depth map. With each new image, the filter first updates the current depth map by a minimum variance estimate that best fits the new image data and the previous estimate. Then the structure estimate is predicted for the next time step by a transformation that accounts for relative camera motion. Experimental evaluation shows the significant improvement in quality and computation time that can be achieved using this technique.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/6808
Date01 May 1991
CreatorsHeel, Joachim
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
Format149 p., 23730458 bytes, 8484961 bytes, application/postscript, application/pdf
RelationAITR-1296

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