Temporal Surface Reconstruction

Title: en_US Temporal Surface Reconstruction
Creator: en_US Heel, Joachim
Date: 2004-10-20T19:57:38Z
Date Available: 2004-10-20T19:57:38Z
Date Issued: en_US 1991-05-01
Identifier: en_US AITR-1296
uri: http://hdl.handle.net/1721.1/6808
Abstract: en_US 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.
Extent: en_US 149 p.; 23730458 bytes; 8484961 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-1296
Subject: en_US 3D reconstruction; en_US Kalman Filter; en_US temporal vision; en_US structuresestimation; en_US surface reconstruction