Low resolution face recognition based on support vector data description

Sang Woong Lee; Jooyoung Park; Seong Whan Lee

doi:10.1016/j.patcog.2006.04.033

Low resolution face recognition based on support vector data description

Sang Woong Lee, Jooyoung Park, Seong Whan Lee

Department of Artificial Intelligence

Research output: Contribution to journal › Article › peer-review

92 Citations (Scopus)

Abstract

In the face recognition process, it is important to deal with a facial image of low-resolution. For low-resolution face recognition, we propose a new method of extending the SVDD, which is one of the most well-known support vector learning methods for the one-class problem. The proposed method can recognize a person even with a low-resolution image.

Original language	English
Pages (from-to)	1809-1812
Number of pages	4
Journal	Pattern Recognition
Volume	39
Issue number	9
DOIs	https://doi.org/10.1016/j.patcog.2006.04.033
Publication status	Published - 2006 Sept

Keywords

Face recognition
Image enhancement
Low resolution
Support vector data description (SVDD)

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

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10.1016/j.patcog.2006.04.033

Cite this

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title = "Low resolution face recognition based on support vector data description",

abstract = "In the face recognition process, it is important to deal with a facial image of low-resolution. For low-resolution face recognition, we propose a new method of extending the SVDD, which is one of the most well-known support vector learning methods for the one-class problem. The proposed method can recognize a person even with a low-resolution image.",

keywords = "Face recognition, Image enhancement, Low resolution, Support vector data description (SVDD)",

author = "Lee, {Sang Woong} and Jooyoung Park and Lee, {Seong Whan}",

note = "Funding Information: This research was supported by the Intelligent Robotics Development Program, one of the 21st Century Frontier R & D Programs funded by the Ministry of Commerce, Industry and Energy of Korea.",

year = "2006",

month = sep,

doi = "10.1016/j.patcog.2006.04.033",

language = "English",

volume = "39",

pages = "1809--1812",

journal = "Pattern Recognition",

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T1 - Low resolution face recognition based on support vector data description

AU - Lee, Sang Woong

AU - Park, Jooyoung

AU - Lee, Seong Whan

N1 - Funding Information: This research was supported by the Intelligent Robotics Development Program, one of the 21st Century Frontier R & D Programs funded by the Ministry of Commerce, Industry and Energy of Korea.

PY - 2006/9

Y1 - 2006/9

N2 - In the face recognition process, it is important to deal with a facial image of low-resolution. For low-resolution face recognition, we propose a new method of extending the SVDD, which is one of the most well-known support vector learning methods for the one-class problem. The proposed method can recognize a person even with a low-resolution image.

AB - In the face recognition process, it is important to deal with a facial image of low-resolution. For low-resolution face recognition, we propose a new method of extending the SVDD, which is one of the most well-known support vector learning methods for the one-class problem. The proposed method can recognize a person even with a low-resolution image.

KW - Face recognition

KW - Image enhancement

KW - Low resolution

KW - Support vector data description (SVDD)

UR - http://www.scopus.com/inward/record.url?scp=33744995034&partnerID=8YFLogxK

U2 - 10.1016/j.patcog.2006.04.033

DO - 10.1016/j.patcog.2006.04.033

M3 - Article

AN - SCOPUS:33744995034

SN - 0031-3203

VL - 39

SP - 1809

EP - 1812

JO - Pattern Recognition

JF - Pattern Recognition

IS - 9

ER -

Low resolution face recognition based on support vector data description

Abstract

Keywords

ASJC Scopus subject areas

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