Multi-view gait-based human identification with automatic joint detection
This research work proposes a joint detection approach to detect locations of body joint automatically by applying a priori knowledge of body proportion. The joint detection approach does not attempt to detect each lower limb of a human, so it can detect the body joints even from self-occluded silho...
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| التنسيق: | أطروحة |
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2014
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my-mmu-ep.5989 |
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my-mmu-ep.59892023-04-12T07:56:15Z Multi-view gait-based human identification with automatic joint detection 2014-01 Ng, Hu TK7800-8360 Electronics This research work proposes a joint detection approach to detect locations of body joint automatically by applying a priori knowledge of body proportion. The joint detection approach does not attempt to detect each lower limb of a human, so it can detect the body joints even from self-occluded silhouettes or those occluded by apparel (long blouses or baggy trousers) or bags (handbag or rucksack). In this research work, an improved perspective correction technique to normalize oblique-view walking sequences to side-view plane has been developed. The silhouettes from oblique-view walking sequences are vertical and horizontal adjusted to fit the sideview. 2014-01 Thesis http://shdl.mmu.edu.my/5989/ http://erep.mmu.edu.my/ phd doctoral Multimedia University Faculty of Computing and Informatics EREP ID: 7948 |
| institution |
Multimedia University |
| collection |
MMU Institutional Repository |
| topic |
TK7800-8360 Electronics |
| spellingShingle |
TK7800-8360 Electronics Ng, Hu Multi-view gait-based human identification with automatic joint detection |
| description |
This research work proposes a joint detection approach to detect locations of body joint automatically by applying a priori knowledge of body proportion. The joint detection approach does not attempt to detect each lower limb of a human, so it can detect the body joints even from self-occluded silhouettes or those occluded by apparel (long blouses or baggy trousers) or bags (handbag or rucksack). In this research work, an improved perspective correction technique to normalize oblique-view walking sequences to side-view plane has been developed. The silhouettes from oblique-view walking sequences are vertical and horizontal adjusted to fit the sideview. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Ng, Hu |
| author_facet |
Ng, Hu |
| author_sort |
Ng, Hu |
| title |
Multi-view gait-based human identification with automatic joint detection |
| title_short |
Multi-view gait-based human identification with automatic joint detection |
| title_full |
Multi-view gait-based human identification with automatic joint detection |
| title_fullStr |
Multi-view gait-based human identification with automatic joint detection |
| title_full_unstemmed |
Multi-view gait-based human identification with automatic joint detection |
| title_sort |
multi-view gait-based human identification with automatic joint detection |
| granting_institution |
Multimedia University |
| granting_department |
Faculty of Computing and Informatics |
| publishDate |
2014 |
| _version_ |
1776101413940625408 |