Towards facial feature extraction and verification for omni-face detection in video/images

Xingquan Zhu, Jianping Fan, Ahmed Elmagarmid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)


Face detection is important in video/image content analysis and organization since the most important object in those medias is often human being. We propose a facial feature based omni-face detection algorithm in this paper. While utilizing the skin color model for face cue detection, a pairwise skin region refinement strategy is applied to eliminate the errors incurred by skin model. Then, a region based adaptive threshold selection scheme is employed for facial feature segmentation. After the facial feature filtering, an orientation, pose and scale invariant face verification strategy is utilized to verify the detected face candidate regions. Experimental results demonstrate successful detection over a wide variety of facial variation in background, scale, view and orientation from different types of video collections.

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Publication statusPublished - 1 Jan 2002
Externally publishedYes
EventInternational Conference on Image Processing (ICIP'02) - Rochester, NY, United States
Duration: 22 Sep 200225 Sep 2002


OtherInternational Conference on Image Processing (ICIP'02)
CountryUnited States
CityRochester, NY


ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Zhu, X., Fan, J., & Elmagarmid, A. (2002). Towards facial feature extraction and verification for omni-face detection in video/images. In IEEE International Conference on Image Processing (Vol. 2)