Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models
In this paper, we aim to improve one of the current state-of-the-art models for facial components detection/localization. The objectives are to increase the amount of landmark points detected and improve the landmark extraction accuracy for frontal faces. The model is following Zhu and Ramanan'...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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I E E E Computer Society
2014
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/19239 |
| _version_ | 1848749975939317760 |
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| author | Liang, Antoni Liu, Wan-Quan Li, Ling Farid, M. Le, V. |
| author2 | Prof. Michael Felsberg, Linköping University |
| author_facet | Prof. Michael Felsberg, Linköping University Liang, Antoni Liu, Wan-Quan Li, Ling Farid, M. Le, V. |
| author_sort | Liang, Antoni |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper, we aim to improve one of the current state-of-the-art models for facial components detection/localization. The objectives are to increase the amount of landmark points detected and improve the landmark extraction accuracy for frontal faces. The model is following Zhu and Ramanan's approach with a tree-structure. The popular AR dataset is chosen as an alternative training dataset as it provides more landmark points requested. Our extension models are compared with Zhu and Ramanan's frontal face models in terms of detection accuracy. We also compare our models with another robust facial components detector called CompASM. Our experiments show that our models can achieve lower error rate on some fiducial points by providing more landmarks, and these accurate fiducial points will provide more accurate features for some applications related to facial shapes. The impact of image colour spaces other than RGB on the proposed detector is also investigated. |
| first_indexed | 2025-11-14T07:29:29Z |
| format | Conference Paper |
| id | curtin-20.500.11937-19239 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:29:29Z |
| publishDate | 2014 |
| publisher | I E E E Computer Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-192392017-09-13T13:46:47Z Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models Liang, Antoni Liu, Wan-Quan Li, Ling Farid, M. Le, V. Prof. Michael Felsberg, Linköping University CompASM. fiducial points landmark points landmark extraction accuracy AR dataset RGB facial components detection/localization Zhu and Ramanan's frontal face models tree-structure In this paper, we aim to improve one of the current state-of-the-art models for facial components detection/localization. The objectives are to increase the amount of landmark points detected and improve the landmark extraction accuracy for frontal faces. The model is following Zhu and Ramanan's approach with a tree-structure. The popular AR dataset is chosen as an alternative training dataset as it provides more landmark points requested. Our extension models are compared with Zhu and Ramanan's frontal face models in terms of detection accuracy. We also compare our models with another robust facial components detector called CompASM. Our experiments show that our models can achieve lower error rate on some fiducial points by providing more landmarks, and these accurate fiducial points will provide more accurate features for some applications related to facial shapes. The impact of image colour spaces other than RGB on the proposed detector is also investigated. 2014 Conference Paper http://hdl.handle.net/20.500.11937/19239 10.1109/ICPR.2014.103 I E E E Computer Society restricted |
| spellingShingle | CompASM. fiducial points landmark points landmark extraction accuracy AR dataset RGB facial components detection/localization Zhu and Ramanan's frontal face models tree-structure Liang, Antoni Liu, Wan-Quan Li, Ling Farid, M. Le, V. Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models |
| title | Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models |
| title_full | Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models |
| title_fullStr | Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models |
| title_full_unstemmed | Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models |
| title_short | Accurate Facial Landmarks Detection for Frontal Faces with Extended Tree-Structured Models |
| title_sort | accurate facial landmarks detection for frontal faces with extended tree-structured models |
| topic | CompASM. fiducial points landmark points landmark extraction accuracy AR dataset RGB facial components detection/localization Zhu and Ramanan's frontal face models tree-structure |
| url | http://hdl.handle.net/20.500.11937/19239 |