Face alignment based on the multi-scale local features

Many face recognition algorithms depend on careful positioning of face images into the same canonical pose. Currently, this positioning is usually done by detecting the locations of eyes. And the face images are transformed to the same positions according to the eye coordinates detected. In this pap...

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Main Authors: Geng, Cong, Jiang, Xudong
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/98794
http://hdl.handle.net/10220/13413
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-987942020-03-07T13:24:48Z Face alignment based on the multi-scale local features Geng, Cong Jiang, Xudong School of Electrical and Electronic Engineering IEEE International Conference on Acoustics, Speech and Signal Processing (2012 : Kyoto, Japan) DRNTU::Engineering::Electrical and electronic engineering Many face recognition algorithms depend on careful positioning of face images into the same canonical pose. Currently, this positioning is usually done by detecting the locations of eyes. And the face images are transformed to the same positions according to the eye coordinates detected. In this paper, we describe a method based on multi-scale local features to achieve face alignment automatically not just dependent on the localizations of two eyes. Given an unaligned face image resulting from a face detector and a set of aligned face images in the data set, we build an automatic transformation mechanism, under which the unaligned face image can be precisely aligned for the following recognition process. Our alignment method improves performance on face recognition tasks, over images aligned by many other algorithms. 2013-09-09T07:31:39Z 2019-12-06T19:59:44Z 2013-09-09T07:31:39Z 2019-12-06T19:59:44Z 2012 2012 Conference Paper Geng, C., & Jiang, X. (2012). Face alignment based on the multi-scale local features . 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1517-1520. https://hdl.handle.net/10356/98794 http://hdl.handle.net/10220/13413 10.1109/ICASSP.2012.6288179 en © 2012 IEEE.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Geng, Cong
Jiang, Xudong
Face alignment based on the multi-scale local features
description Many face recognition algorithms depend on careful positioning of face images into the same canonical pose. Currently, this positioning is usually done by detecting the locations of eyes. And the face images are transformed to the same positions according to the eye coordinates detected. In this paper, we describe a method based on multi-scale local features to achieve face alignment automatically not just dependent on the localizations of two eyes. Given an unaligned face image resulting from a face detector and a set of aligned face images in the data set, we build an automatic transformation mechanism, under which the unaligned face image can be precisely aligned for the following recognition process. Our alignment method improves performance on face recognition tasks, over images aligned by many other algorithms.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Geng, Cong
Jiang, Xudong
format Conference or Workshop Item
author Geng, Cong
Jiang, Xudong
author_sort Geng, Cong
title Face alignment based on the multi-scale local features
title_short Face alignment based on the multi-scale local features
title_full Face alignment based on the multi-scale local features
title_fullStr Face alignment based on the multi-scale local features
title_full_unstemmed Face alignment based on the multi-scale local features
title_sort face alignment based on the multi-scale local features
publishDate 2013
url https://hdl.handle.net/10356/98794
http://hdl.handle.net/10220/13413
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