2.5D face landmarking via scale-invariant feature extraction and centroid localization

In this paper, we present and discuss our proposed method on landmarking on 2.5-dimensional (2.5D) face range images. Face landmarking plays an important role as an intermediary component in several face processing operation applications. Locating facial landmarks automatically remains a challenge....

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Main Authors: Suk, Ting Pui, Terrin, Lim, Jacey-Lynn, Minoi
Format: Article
Language:English
Published: IEEE 2016
Subjects:
Online Access:http://ir.unimas.my/id/eprint/16543/
http://ir.unimas.my/id/eprint/16543/1/2.5D%20Face%20Landmarking%20via%20Scale-invariant%20Feature%20%28abstract%29.pdf
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author Suk, Ting Pui
Terrin, Lim
Jacey-Lynn, Minoi
author_facet Suk, Ting Pui
Terrin, Lim
Jacey-Lynn, Minoi
author_sort Suk, Ting Pui
building UNIMAS Institutional Repository
collection Online Access
description In this paper, we present and discuss our proposed method on landmarking on 2.5-dimensional (2.5D) face range images. Face landmarking plays an important role as an intermediary component in several face processing operation applications. Locating facial landmarks automatically remains a challenge. Detecting and localizing landmarks from raw face data are often performed manually by trained and experienced scientists or clinicians, and the process is usually lengthy, laborious and tedious. In order to overcome these challenges, we introduce a method that employs geometric approach, through utilizing the mean and Gaussian curvatures, primitive surfaces information to identify and label features as anatomical landmarks. In addition, comparative experiments on both automatic landmarking and manual landmarking were also performed and the results have demonstrated that the proposed method outperforms the manual landmarking in terms of obtaining distinct facial landmarks correctly and accurately.
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spelling unimas-165432017-06-08T06:02:41Z http://ir.unimas.my/id/eprint/16543/ 2.5D face landmarking via scale-invariant feature extraction and centroid localization Suk, Ting Pui Terrin, Lim Jacey-Lynn, Minoi T Technology (General) In this paper, we present and discuss our proposed method on landmarking on 2.5-dimensional (2.5D) face range images. Face landmarking plays an important role as an intermediary component in several face processing operation applications. Locating facial landmarks automatically remains a challenge. Detecting and localizing landmarks from raw face data are often performed manually by trained and experienced scientists or clinicians, and the process is usually lengthy, laborious and tedious. In order to overcome these challenges, we introduce a method that employs geometric approach, through utilizing the mean and Gaussian curvatures, primitive surfaces information to identify and label features as anatomical landmarks. In addition, comparative experiments on both automatic landmarking and manual landmarking were also performed and the results have demonstrated that the proposed method outperforms the manual landmarking in terms of obtaining distinct facial landmarks correctly and accurately. IEEE 2016 Article PeerReviewed text en http://ir.unimas.my/id/eprint/16543/1/2.5D%20Face%20Landmarking%20via%20Scale-invariant%20Feature%20%28abstract%29.pdf Suk, Ting Pui and Terrin, Lim and Jacey-Lynn, Minoi (2016) 2.5D face landmarking via scale-invariant feature extraction and centroid localization. 3rd International Conference on Computer and Information Sciences (ICCOINS), 2016. ISSN ISBN : 978-1-5090-2549-7 http://ieeexplore.ieee.org/document/7783244/ DOI: 10.1109/ICCOINS.2016.7783244
spellingShingle T Technology (General)
Suk, Ting Pui
Terrin, Lim
Jacey-Lynn, Minoi
2.5D face landmarking via scale-invariant feature extraction and centroid localization
title 2.5D face landmarking via scale-invariant feature extraction and centroid localization
title_full 2.5D face landmarking via scale-invariant feature extraction and centroid localization
title_fullStr 2.5D face landmarking via scale-invariant feature extraction and centroid localization
title_full_unstemmed 2.5D face landmarking via scale-invariant feature extraction and centroid localization
title_short 2.5D face landmarking via scale-invariant feature extraction and centroid localization
title_sort 2.5d face landmarking via scale-invariant feature extraction and centroid localization
topic T Technology (General)
url http://ir.unimas.my/id/eprint/16543/
http://ir.unimas.my/id/eprint/16543/
http://ir.unimas.my/id/eprint/16543/
http://ir.unimas.my/id/eprint/16543/1/2.5D%20Face%20Landmarking%20via%20Scale-invariant%20Feature%20%28abstract%29.pdf