Twelve anchor points detection by direct point calculation
Facial features can be categorized it into three approaches; Region Approaches, Anchor Point (landmark) Approaches and Contour Approaches. Generally, anchor points approach provide more accurate and consistent representation. For this reason, anchor points approach has been chose to utilize. Althoug...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Utara Malaysia Press
2007
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| Online Access: | http://psasir.upm.edu.my/id/eprint/34839/ http://psasir.upm.edu.my/id/eprint/34839/1/Twelve%20anchor%20points%20detection%20by%20direct%20point%20calculation.pdf |
| _version_ | 1848847886015528960 |
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| author | Khalid, Fatimah Tengku Sembok, Tengku Mohd Omar, Khairuddin |
| author_facet | Khalid, Fatimah Tengku Sembok, Tengku Mohd Omar, Khairuddin |
| author_sort | Khalid, Fatimah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Facial features can be categorized it into three approaches; Region Approaches, Anchor Point (landmark) Approaches and Contour Approaches. Generally, anchor points approach provide more accurate and consistent representation. For this reason, anchor points approach has been chose to utilize. Although, as the experiment data sets have become larger, algorithms have become more sophisticated even if the reported recognition rates are not as high as in some earlier works. This will cause a higher complexity and computer burden. Indirectly, it also will affect the time for real time face recognition systems. Here, it is proposed the approach of calculating the points directly from the text file to detect twelve anchor points ( nose tip, mouth centre, right eye centre, left eye centre, upper nose and chin). In order to get the anchor points, points for the nose tip have to be detected first. Then the upper nose and face point is localization. Lastly, the outer and inner eyes corner is localized. An experiment has been carried out with 420 models taken from GavabDB in two positions with frontal view and variation of expressions and positions. Our results are compared with three researchers that is similar to and show that better result is obtained with a median error of the eight points is around 5.53mm. |
| first_indexed | 2025-11-15T09:25:43Z |
| format | Article |
| id | upm-34839 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:25:43Z |
| publishDate | 2007 |
| publisher | Universiti Utara Malaysia Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-348392016-10-10T04:19:47Z http://psasir.upm.edu.my/id/eprint/34839/ Twelve anchor points detection by direct point calculation Khalid, Fatimah Tengku Sembok, Tengku Mohd Omar, Khairuddin Facial features can be categorized it into three approaches; Region Approaches, Anchor Point (landmark) Approaches and Contour Approaches. Generally, anchor points approach provide more accurate and consistent representation. For this reason, anchor points approach has been chose to utilize. Although, as the experiment data sets have become larger, algorithms have become more sophisticated even if the reported recognition rates are not as high as in some earlier works. This will cause a higher complexity and computer burden. Indirectly, it also will affect the time for real time face recognition systems. Here, it is proposed the approach of calculating the points directly from the text file to detect twelve anchor points ( nose tip, mouth centre, right eye centre, left eye centre, upper nose and chin). In order to get the anchor points, points for the nose tip have to be detected first. Then the upper nose and face point is localization. Lastly, the outer and inner eyes corner is localized. An experiment has been carried out with 420 models taken from GavabDB in two positions with frontal view and variation of expressions and positions. Our results are compared with three researchers that is similar to and show that better result is obtained with a median error of the eight points is around 5.53mm. Universiti Utara Malaysia Press 2007 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/34839/1/Twelve%20anchor%20points%20detection%20by%20direct%20point%20calculation.pdf Khalid, Fatimah and Tengku Sembok, Tengku Mohd and Omar, Khairuddin (2007) Twelve anchor points detection by direct point calculation. Journal of Information and Communication Technology, 6. pp. 59-72. ISSN 1675-414X; ESSN: 2180-3862 http://www.jict.uum.edu.my/index.php/previous-issues/135-journal-of-information-and-communication-technology-jict-vol-6-2007 |
| spellingShingle | Khalid, Fatimah Tengku Sembok, Tengku Mohd Omar, Khairuddin Twelve anchor points detection by direct point calculation |
| title | Twelve anchor points detection by direct point calculation |
| title_full | Twelve anchor points detection by direct point calculation |
| title_fullStr | Twelve anchor points detection by direct point calculation |
| title_full_unstemmed | Twelve anchor points detection by direct point calculation |
| title_short | Twelve anchor points detection by direct point calculation |
| title_sort | twelve anchor points detection by direct point calculation |
| url | http://psasir.upm.edu.my/id/eprint/34839/ http://psasir.upm.edu.my/id/eprint/34839/ http://psasir.upm.edu.my/id/eprint/34839/1/Twelve%20anchor%20points%20detection%20by%20direct%20point%20calculation.pdf |