Low resolution face recognition based on support vector data description

Sang Woong Lee, Jooyoung Park, Seong Whan Lee

Research output: Contribution to journalArticlepeer-review

92 Citations (Scopus)


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 languageEnglish
Pages (from-to)1809-1812
Number of pages4
JournalPattern Recognition
Issue number9
Publication statusPublished - 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.


  • 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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