Detection of human faces under scale, orientation and viewpoint variations

Many current human face detection algorithmsmake implicit assumptions about the scale, orientation or viewpoint of faces in an image and exploit these constraints to detect and localize faces. The algorithm may be robust for the assumed conditionsbuthowever itbecomes very difficulttoextend the results to general imaging conditions. In an earlier paper, we proposed a feature-based face detection algorithm to detect faces in complex background. In this paper, we willexamine its abilityto detect faces under different scale, orientation and viewpoint. The results show that the algorithm can indeed cope with a good range of scale, orientation and viewpoint variations that is typical of a subject sitting in front of a computer terminal.

• Type: Conference
• Year: 1996
• Where: FGR
• Authors: Kin Choong Yow, Roberto Cipolla
• Keywords: Biometrics, Face Detection, Face Detection Algorithm, FGR 1996, Human Face Detection