Face detection and recognition using geometrical features and a neural network verifier
Sung Ho Yoon, Gi-yeon Park, Gi T. Hur, Jung H. Kim · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
This paper presents a new method for face verification for vision applications. There are many approaches to detect and track a face in a sequence of images; however, the high computations of image algorithms, as well as, face detection and head tracking failures under unrestricted environments remain to be a difficult problem. We present a robust algorithm that improves face detection and tracking in video sequences by using geometrical facial information and a recurrent neural network verifier. Two types of neural networks are proposed for face detection verification. A new method, a three-face reference model (TFRM), and its advantages, such as, allowing for a better match for face verification, will be discussed in this paper.