A novel hybrid face profile recognition system using the FERET and MUGSHOT databases

Face recognition has established itself as an important subbranch of pattern recognition within the field of computer science. Many state-of-the-art systems have focused on the task of recognizing frontal views of people. In this work we will present an approach to recognize profile views (90? ) with a system trained on transformed frontal views. The system combines an Artificial Neural Network (ANN) and a classification process based on Hidden Markov Models (HMM). One of the main ideas of this system is to perform the recognition task without the use of any 3D-information of heads and faces. The presented system has been tested with subsets of the FERET and the MUGSHOT databases.

• Type: Conference
• Year: 2001
• Where: ICIP
• Authors: Frank Wallhoff, Gerhard Rigoll, Payman Moallem
• Keywords: Frontal Views, Hidden Markov Models, ICIP 2001, Image Processing, Recognition Task