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Temporal Surface Reconstruction

Author(s)
Heel, Joachim
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Abstract
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.
Date issued
1991-05-01
URI
http://hdl.handle.net/1721.1/6808
Other identifiers
AITR-1296
Series/Report no.
AITR-1296
Keywords
3D reconstruction, Kalman Filter, temporal vision, structuresestimation, surface reconstruction

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