UPM Institutional Repository

Twelve anchor points detection by direct point calculation


Citation

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

Abstract

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.


Download File

[img]
Preview
PDF (Abstract)
Twelve anchor points detection by direct point calculation.pdf

Download (34kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Publisher: Universiti Utara Malaysia Press
Keywords: 3D face recognition; 3D face detection
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 10 Oct 2016 04:19
Last Modified: 10 Oct 2016 04:19
URI: http://psasir.upm.edu.my/id/eprint/34839
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item