Low resolution face recognition based on support vector data description

Sang Woong Lee, Jooyoung Park, Seong Whan Lee

    Research output: Contribution to journalArticlepeer-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 languageEnglish
    Pages (from-to)1809-1812
    Number of pages4
    JournalPattern Recognition
    Volume39
    Issue number9
    DOIs
    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.

    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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