Face detection using support vector domain description in color images

Jin Seo, Hanseok Ko

    Research output: Contribution to journalConference articlepeer-review

    26 Citations (Scopus)

    Abstract

    In this paper, we present a face detection system using the Support Vector Domain Description (SVDD) in color images. Conventional face detection algorithms require a training procedure using both face and non-face images. In the SVDD, however, we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use Entropie Threshold for extracting the facial feature and Sliding Window for improved performance while saving the processing time. The experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to the conventional PCA (Principal Component Analysis)-based methods.

    Original languageEnglish
    Pages (from-to)V-729-V-732
    JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume5
    Publication statusPublished - 2004
    EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
    Duration: 2004 May 172004 May 21

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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