The ENCARA System for Face Detection and Normalization

摘要

Facial image processing is becoming widespread in human-computer applications, despite its complexity. High-level processes such as face recognition or gender determination rely on low-level routines that must effectively detect and normalize the faces that appear in the input image. In this paper, a face detection and normalization system is described. The approach taken is based on a cascade of fast, weak clasifiers that together try to determine whether a frontal face is present in the image. The system is also able to obtain the position of facial features, such as mouth and eyes, and it operates in real-time. Comprehensive experiments carried out with real video sequences show that the system is faster than other approaches and effective in detecting frontal faces.