Uncertainty reasoning in hierachical visual evidence space
One of the major problems in computer vision involves dealing with uncertain information. Occlusion, dissimilar views, insufficient illumination, insufficient resolution, and degradation give rise to imprecise data. At the same time, incomplete or local knowledge of the scene gives rise to imprecise...
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ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-387562021-04-16T05:40:44Z Uncertainty reasoning in hierachical visual evidence space Qian, Jianzhong Electrical Engineering Ehrich, Roger W. LD5655.V856 1990.Q536 Computer vision -- Research One of the major problems in computer vision involves dealing with uncertain information. Occlusion, dissimilar views, insufficient illumination, insufficient resolution, and degradation give rise to imprecise data. At the same time, incomplete or local knowledge of the scene gives rise to imprecise interpretation rules. Uncertainty arises at different processing levels of computer vision either because of the imprecise data or because of the imprecise interpretation rules. It is natural to build computer vision systems that incorporate uncertainty reasoning. The Dempster-Shafer (D-S) theory of evidence is appealing for coping with uncertainty hierarchically. However, very little work has been done to apply D-S theory to practical vision systems because some important problems are yet to be resolved. Ph. D. 2014-03-14T21:15:47Z 2014-03-14T21:15:47Z 1990-04-01 2007-07-11 2007-07-11 2007-07-11 Dissertation Text etd-07112007-092846 http://hdl.handle.net/10919/38756 http://scholar.lib.vt.edu/theses/available/etd-07112007-092846/ en OCLC# 22250192 LD5655.V856_1990.Q536.pdf In Copyright http://rightsstatements.org/vocab/InC/1.0/ xi, 264 leaves BTD application/pdf application/pdf Virginia Tech |
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LD5655.V856 1990.Q536 Computer vision -- Research |
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LD5655.V856 1990.Q536 Computer vision -- Research Qian, Jianzhong Uncertainty reasoning in hierachical visual evidence space |
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One of the major problems in computer vision involves dealing with uncertain information. Occlusion, dissimilar views, insufficient illumination, insufficient resolution, and degradation give rise to imprecise data. At the same time, incomplete or local knowledge of the scene gives rise to imprecise interpretation rules.
Uncertainty arises at different processing levels of computer vision either because of the imprecise data or because of the imprecise interpretation rules. It is natural to build computer vision systems that incorporate uncertainty reasoning. The Dempster-Shafer (D-S) theory of evidence is appealing for coping with uncertainty hierarchically. However, very little work has been done to apply D-S theory to practical vision systems because some important problems are yet to be resolved. === Ph. D. |
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Electrical Engineering |
author_facet |
Electrical Engineering Qian, Jianzhong |
author |
Qian, Jianzhong |
author_sort |
Qian, Jianzhong |
title |
Uncertainty reasoning in hierachical visual evidence space |
title_short |
Uncertainty reasoning in hierachical visual evidence space |
title_full |
Uncertainty reasoning in hierachical visual evidence space |
title_fullStr |
Uncertainty reasoning in hierachical visual evidence space |
title_full_unstemmed |
Uncertainty reasoning in hierachical visual evidence space |
title_sort |
uncertainty reasoning in hierachical visual evidence space |
publisher |
Virginia Tech |
publishDate |
2014 |
url |
http://hdl.handle.net/10919/38756 http://scholar.lib.vt.edu/theses/available/etd-07112007-092846/ |
work_keys_str_mv |
AT qianjianzhong uncertaintyreasoninginhierachicalvisualevidencespace |
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