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http://hdl.handle.net/10225/617
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| Title: | 3D RECONSTRUCTION FROM STEREO/RANGE IMAGES |
| Authors: | Yang, Qingxiong |
| Date Created: | 2007 |
| Publisher: | University of Kentucky |
| Abstract: | 3D reconstruction from stereo/range image is one of the most fundamental and extensively researched topics in computer vision. Stereo research has recently experienced somewhat of a new era, as a result of publically available performance testing such as the Middlebury data set, which has allowed researchers to compare their algorithms against all the state-of-the-art algorithms. This thesis investigates into the general stereo problems in both the two-view stereo and multi-view stereo scopes. In the two-view stereo scope, we formulate an algorithm for the stereo matching problem with careful handling of disparity, discontinuity and occlusion. The algorithm works with a global matching stereo model based on an energy minimization framework. The experimental results are evaluated on the Middlebury data set, showing that our algorithm is the top performer. A GPU approach of the Hierarchical BP algorithm is then proposed, which provides similar stereo quality to CPU Hierarchical BP while running at real-time speed. A fast-converging BP is also proposed to solve the slow convergence problem of general BP algorithms. Besides two-view stereo, ecient multi-view stereo for large scale urban reconstruction is carefully studied in this thesis. A novel approach for computing depth maps given urban imagery where often large parts of surfaces are weakly textured is presented. Finally, a new post-processing step to enhance the range images in both the both the spatial resolution and depth precision is proposed. |
| URI: | http://hdl.handle.net/10225/617 |
| Appears in Collections: | Electronic Theses and Dissertations
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Files in This Item:
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| dissert.pdf | 3879Kb | Adobe PDF | View/Open |
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