Robust Face Detection Using the Hausdorff Distance

Abstract. The localization of human faces in digital images is a fundamental step in the process of face recognition. This paper presents a shape comparison approach to achieve fast, accurate face detection that is robust to changes in illumination and background. The proposed method is edge-based and works on grayscale still images. The Hausdorff distance is used as a similarity measure between a general face model and possible instances of the object within the image. The paper describes an efficient implementation, making this approach suitable for real-time applications. A two-step process that allows both coarse detection and exact localization of faces is presented. Experiments were performed on a large test set base and rated with a new validation measurement. c In Proc. Third International Conference on Audio- and Video-based Biometric Person Authentication, Springer, Lecture Notes in Computer

• Type: Conference
• Year: 2001
• Where: AVBPA
• Authors: Oliver Jesorsky, Klaus J. Kirchberg, Robert Frischholz
• Keywords: Accurate Face Detection, AVBPA 2001, Biometrics, General Face Model, Shape Comparison Approach