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

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

93 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

Bibliographical 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.

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",

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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)

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U2 - 10.1016/j.patcog.2006.04.033

DO - 10.1016/j.patcog.2006.04.033

M3 - Article

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SN - 0031-3203

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SP - 1809

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JO - Pattern Recognition

JF - Pattern Recognition

IS - 9

ER -

Low resolution face recognition based on support vector data description

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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