An analytic-to-holistic approach for face recognition based on a single frontal view

Kin Man Lam, Hong Yan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

206 Citations (Scopus)


In this paper, we propose an analytic-to-holistic approach which can identify faces at different perspective variations. The database for the test consists of 40 frontal-view faces. The first step is to locate 15 feature points on a face. A head model is proposed, and the rotation of the face can be estimated using geometrical measurements. The positions of the feature points are adjusted so that their corresponding positions for the frontal view are approximated. These feature points are then compared with the feature points of the faces in a database using a similarity transform. In the second step, we set up windows for the eyes, nose, and mouth. These feature windows are compared with those in the database by correlation. Results show that this approach can achieve a similar level of performance from different viewing directions of a face. Under different perspective variations, the overall recognition rates are over 84 percent and 96 percent for the first and the first three likely matched faces, respectively.
Original languageEnglish
Pages (from-to)673-686
Number of pages14
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number7
Publication statusPublished - 1 Dec 1998


  • Correlation. © 1998 ieee
  • Face recognition
  • Facial feature detection
  • Head model
  • Point matching

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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