Landmark-based multi-points warping approach to 3D facial expression recognition in human
Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challen...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/78096/1/Landmark-based%20multi-points%20warping%20approach%20to%203D%20facial%20expression%20recognition%20in%20human.pdf |
| _version_ | 1825950968678711296 |
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| author | Opeoluwa, Agbolade Olalekan Ahmad Nazri, Azree Shahrel Yaakob, Razali Abd Ghani, Abdul Azim Cheah, Yoke Kqueen |
| author_facet | Opeoluwa, Agbolade Olalekan Ahmad Nazri, Azree Shahrel Yaakob, Razali Abd Ghani, Abdul Azim Cheah, Yoke Kqueen |
| author_sort | Opeoluwa, Agbolade Olalekan |
| collection | UPM |
| description | Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D: such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark. The results indicate that Fear expression has the lowest recognition accuracy while Surprise expression has the highest recognition accuracy. The classifier achieved a recognition accuracy of 99.58%. |
| first_indexed | 2024-03-06T10:22:43Z |
| format | Conference or Workshop Item |
| id | upm.eprints-78096 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:22:43Z |
| publishDate | 2019 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-780962020-06-03T06:31:41Z http://psasir.upm.edu.my/id/eprint/78096/ Landmark-based multi-points warping approach to 3D facial expression recognition in human Opeoluwa, Agbolade Olalekan Ahmad Nazri, Azree Shahrel Yaakob, Razali Abd Ghani, Abdul Azim Cheah, Yoke Kqueen Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D: such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark. The results indicate that Fear expression has the lowest recognition accuracy while Surprise expression has the highest recognition accuracy. The classifier achieved a recognition accuracy of 99.58%. IEEE 2019 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/78096/1/Landmark-based%20multi-points%20warping%20approach%20to%203D%20facial%20expression%20recognition%20in%20human.pdf Opeoluwa, Agbolade Olalekan and Ahmad Nazri, Azree Shahrel and Yaakob, Razali and Abd Ghani, Abdul Azim and Cheah, Yoke Kqueen (2019) Landmark-based multi-points warping approach to 3D facial expression recognition in human. In: 2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS), 19 Sept. 2019, Perak, Malaysia. (pp. 180-185). 10.1109/AiDAS47888.2019.8970972 |
| spellingShingle | Opeoluwa, Agbolade Olalekan Ahmad Nazri, Azree Shahrel Yaakob, Razali Abd Ghani, Abdul Azim Cheah, Yoke Kqueen Landmark-based multi-points warping approach to 3D facial expression recognition in human |
| title | Landmark-based multi-points warping approach to 3D facial expression recognition in human |
| title_full | Landmark-based multi-points warping approach to 3D facial expression recognition in human |
| title_fullStr | Landmark-based multi-points warping approach to 3D facial expression recognition in human |
| title_full_unstemmed | Landmark-based multi-points warping approach to 3D facial expression recognition in human |
| title_short | Landmark-based multi-points warping approach to 3D facial expression recognition in human |
| title_sort | landmark based multi points warping approach to 3d facial expression recognition in human |
| url | http://psasir.upm.edu.my/id/eprint/78096/1/Landmark-based%20multi-points%20warping%20approach%20to%203D%20facial%20expression%20recognition%20in%20human.pdf |
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