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3D-based face segmentation using adaptive radius

Face detection and segmentation is an important prerequisite step for many face related processes such as face recognition and facial expression recognition. A method that automatically segments the given faces images irrespective of their different sizes and orientations will not only ease the subs...

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Main Authors: Rabiu, Habibu, Saripan, M. Iqbal, Marhaban, Mohammad Hamiruce, Mashohor, Syamsiah
Format: Conference or Workshop Item
Language:English
Published: IEEE 2013
Online Access:http://psasir.upm.edu.my/id/eprint/41439/1/3D-based%20face%20segmentation%20using%20adaptive%20radius.pdf
http://psasir.upm.edu.my/id/eprint/41439/
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spelling my.upm.eprints.414392018-10-31T00:42:05Z http://psasir.upm.edu.my/id/eprint/41439/ 3D-based face segmentation using adaptive radius Rabiu, Habibu Saripan, M. Iqbal Marhaban, Mohammad Hamiruce Mashohor, Syamsiah Face detection and segmentation is an important prerequisite step for many face related processes such as face recognition and facial expression recognition. A method that automatically segments the given faces images irrespective of their different sizes and orientations will not only ease the subsequent face analysis task but will as well enhances its performance. In this work, an adaptive radius based face segmentation method is presented. We utilised the face's intrinsic properties derived from Gaussian and mean curvature of the face surface to segment each face. The UPM-3DFE and Gavab 3D face databases were used in testing the new method. Visual inspection of the result indicated that the novel method can attained up to 99.23% segmentation accuracy. IEEE 2013 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/41439/1/3D-based%20face%20segmentation%20using%20adaptive%20radius.pdf Rabiu, Habibu and Saripan, M. Iqbal and Marhaban, Mohammad Hamiruce and Mashohor, Syamsiah (2013) 3D-based face segmentation using adaptive radius. In: 2013 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 8-10 Oct. 2013, Melaka, Malaysia. (pp. 237-240). 10.1109/ICSIPA.2013.6708010
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Face detection and segmentation is an important prerequisite step for many face related processes such as face recognition and facial expression recognition. A method that automatically segments the given faces images irrespective of their different sizes and orientations will not only ease the subsequent face analysis task but will as well enhances its performance. In this work, an adaptive radius based face segmentation method is presented. We utilised the face's intrinsic properties derived from Gaussian and mean curvature of the face surface to segment each face. The UPM-3DFE and Gavab 3D face databases were used in testing the new method. Visual inspection of the result indicated that the novel method can attained up to 99.23% segmentation accuracy.
format Conference or Workshop Item
author Rabiu, Habibu
Saripan, M. Iqbal
Marhaban, Mohammad Hamiruce
Mashohor, Syamsiah
spellingShingle Rabiu, Habibu
Saripan, M. Iqbal
Marhaban, Mohammad Hamiruce
Mashohor, Syamsiah
3D-based face segmentation using adaptive radius
author_facet Rabiu, Habibu
Saripan, M. Iqbal
Marhaban, Mohammad Hamiruce
Mashohor, Syamsiah
author_sort Rabiu, Habibu
title 3D-based face segmentation using adaptive radius
title_short 3D-based face segmentation using adaptive radius
title_full 3D-based face segmentation using adaptive radius
title_fullStr 3D-based face segmentation using adaptive radius
title_full_unstemmed 3D-based face segmentation using adaptive radius
title_sort 3d-based face segmentation using adaptive radius
publisher IEEE
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/41439/1/3D-based%20face%20segmentation%20using%20adaptive%20radius.pdf
http://psasir.upm.edu.my/id/eprint/41439/
_version_ 1643832998167052288
score 13.211869

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