Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
This paper describes a technique to estimate human face pose from colour video sequence using Dynamic Bayesian Network(DBN). As face and facial features trackers usually track eyes, pupils, mouth corners and skin region(face), our proposed method utilizes merely three of these features – pupils, mo...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://eprints.usm.my/15180/ http://eprints.usm.my/15180/1/paper.pdf |
| _version_ | 1848872203897012224 |
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| author | A. Suandi, Shahrel Enokida, Shuichi Ejima, Toshiaki |
| author_facet | A. Suandi, Shahrel Enokida, Shuichi Ejima, Toshiaki |
| author_sort | A. Suandi, Shahrel |
| building | USM Institutional Repository |
| collection | Online Access |
| description | This paper describes a technique to estimate human face pose from colour video sequence using Dynamic Bayesian Network(DBN). As face and facial features trackers usually
track eyes, pupils, mouth corners and skin region(face), our proposed method utilizes merely three of these features – pupils, mouth centre and skin region – to compute the evidence
for DBN inference.
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| first_indexed | 2025-11-15T15:52:15Z |
| format | Conference or Workshop Item |
| id | usm-15180 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T15:52:15Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-151802017-11-20T07:22:04Z http://eprints.usm.my/15180/ Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network. A. Suandi, Shahrel Enokida, Shuichi Ejima, Toshiaki TK1-9971 Electrical engineering. Electronics. Nuclear engineering This paper describes a technique to estimate human face pose from colour video sequence using Dynamic Bayesian Network(DBN). As face and facial features trackers usually track eyes, pupils, mouth corners and skin region(face), our proposed method utilizes merely three of these features – pupils, mouth centre and skin region – to compute the evidence for DBN inference. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/15180/1/paper.pdf A. Suandi, Shahrel and Enokida, Shuichi and Ejima, Toshiaki (2008) Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network. In: International Workshop On Application of Computer Vision, Copper Mountain, 7-9 January 2008. |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering A. Suandi, Shahrel Enokida, Shuichi Ejima, Toshiaki Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network. |
| title | Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
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| title_full | Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
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| title_fullStr | Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
|
| title_full_unstemmed | Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
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| title_short | Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
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| title_sort | face pose estimation from video sequence using dynamic bayesian network. |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/15180/ http://eprints.usm.my/15180/1/paper.pdf |