Robust and flexible landmarks detection for uncontrolled frontal faces in the wild
In this paper, we propose a robust facial landmarking scheme for frontal faces which can be applied on both controlled and uncontrolled environ-ment. This scheme is based on improvement/extension of the tree-structured facial landmarking scheme proposed by Zhu and Ramanan. The whole system is divide...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
American Institute of Mathematical Sciences
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/10316 |
| _version_ | 1848746199331373056 |
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| author | Liang, A. Wang, C. Liu, Wan-Quan Li, L. |
| author_facet | Liang, A. Wang, C. Liu, Wan-Quan Li, L. |
| author_sort | Liang, A. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper, we propose a robust facial landmarking scheme for frontal faces which can be applied on both controlled and uncontrolled environ-ment. This scheme is based on improvement/extension of the tree-structured facial landmarking scheme proposed by Zhu and Ramanan. The whole system is divided into two main parts: face detection and face landmarking. In the face detection part, we proposed a Tree-structured Filter Model (TFM) combined with Viola and Jones face detector to significantly reduce the false positives while maintaining high accuracy. For the facial landmarking step, we improve the accuracy and the amount of the facial landmarks by readjusting the face structure to provide better geometrical information. Furthermore, we expand the face models into Multi-Resolution (MR) models with the adaptive land-mark approach via landmark reduction to train the face models to be able to detect facial landmarks on face images with resolutions as low as 30x30 pixels. Our experiments show that our proposed approaches can improve the accuracy of facial landmark detection on both controlled and uncontrolled environment. Furthermore, they also show that our MR models are more robust on detecting facial components (eyebrows, eyes, nose, and mouth) on very small faces. |
| first_indexed | 2025-11-14T06:29:27Z |
| format | Journal Article |
| id | curtin-20.500.11937-10316 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:29:27Z |
| publishDate | 2016 |
| publisher | American Institute of Mathematical Sciences |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-103162017-09-13T14:49:27Z Robust and flexible landmarks detection for uncontrolled frontal faces in the wild Liang, A. Wang, C. Liu, Wan-Quan Li, L. In this paper, we propose a robust facial landmarking scheme for frontal faces which can be applied on both controlled and uncontrolled environ-ment. This scheme is based on improvement/extension of the tree-structured facial landmarking scheme proposed by Zhu and Ramanan. The whole system is divided into two main parts: face detection and face landmarking. In the face detection part, we proposed a Tree-structured Filter Model (TFM) combined with Viola and Jones face detector to significantly reduce the false positives while maintaining high accuracy. For the facial landmarking step, we improve the accuracy and the amount of the facial landmarks by readjusting the face structure to provide better geometrical information. Furthermore, we expand the face models into Multi-Resolution (MR) models with the adaptive land-mark approach via landmark reduction to train the face models to be able to detect facial landmarks on face images with resolutions as low as 30x30 pixels. Our experiments show that our proposed approaches can improve the accuracy of facial landmark detection on both controlled and uncontrolled environment. Furthermore, they also show that our MR models are more robust on detecting facial components (eyebrows, eyes, nose, and mouth) on very small faces. 2016 Journal Article http://hdl.handle.net/20.500.11937/10316 10.3934/naco.2016011 American Institute of Mathematical Sciences unknown |
| spellingShingle | Liang, A. Wang, C. Liu, Wan-Quan Li, L. Robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| title | Robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| title_full | Robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| title_fullStr | Robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| title_full_unstemmed | Robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| title_short | Robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| title_sort | robust and flexible landmarks detection for uncontrolled frontal faces in the wild |
| url | http://hdl.handle.net/20.500.11937/10316 |