A robust face detector algorithm utilizing neural networks and partial template matching
Pitoyo Hartono, Shuji Hashimoto · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Face detection from an arbitrary scene has become a very actively studied topic in the image processing and pattern recognition fields. The reason for the importance of face detection is in its broad applications, for example in human detection by means of visual input for security reason, human-machine interaction, and video archiving. Human face is composed from several components, each with large varieties and it can take many postures in arbitrary scene, which make detection task a very difficult one. In this study we propose a method for robust face detection from arbitrary scene utilizing neural network as face's posture predictor and partial template matching of human face. The proposed model is robust to the lighting conditions and postures of the frontal faces.