Face detection using support vector domain description in color images

Jin Seo, Hanseok Ko

Research output: Contribution to journalConference article

16 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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