Model-Based Estimation of Human Pose and Its Analysis Using Hausdorff Matching
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Maik, V. | - |
dc.contributor.author | 박진호 | - |
dc.contributor.author | 김대희 | - |
dc.contributor.author | 백준기 | - |
dc.date.available | 2020-06-08T06:20:55Z | - |
dc.date.issued | 2015-05 | - |
dc.identifier.issn | 2288-9248 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/40410 | - |
dc.description.abstract | This paper presents a novel algorithm for automatically locating, extracting, and recognizing human poses. The proposed algorithm consists of four stages: (i) training of typical poses in 2D and 3D configurations, (ii) Hausdorff matching for locating the pose, (iii) silhouette representation of the located pose using deformable templates, and (iv) joint extraction from the silhouette. In order to reduce the computational overhead, an a priori obtained training set, Hausdorff matching with principal component analysis (PCA), and a heuristic approach were used. The algorithm was tested on typical human poses such as standing, sitting, walking, crouching, and stretching, and experimental results show the efficiency and accuracy of the proposed algorithm. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | 중앙대학교 영상콘텐츠융합연구소 | - |
dc.title | Model-Based Estimation of Human Pose and Its Analysis Using Hausdorff Matching | - |
dc.type | Article | - |
dc.identifier.doi | 10.15323/techart.2015.05.2.2.51 | - |
dc.identifier.bibliographicCitation | TECHART: Journal of Arts and Imaging Science, v.2, no.2, pp 51 - 56 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 56 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 51 | - |
dc.citation.title | TECHART: Journal of Arts and Imaging Science | - |
dc.citation.volume | 2 | - |
dc.publisher.location | 대한민국 | - |
dc.description.journalRegisteredClass | domestic | - |
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