Real-time face recognition for human-robot interaction

The ability to recognize people is a key element for improving human-robot interaction in service robots. There are many approaches for face recognition; however, these assume unrealistic conditions for a service robot, like having an image with a centered face under controlled illumination. We have developed a novel face recognition system so that a mobile robot can learn new faces and recognize them in real–time in realistic indoor environments. It is able to learn on-line a new face based on a single frame, which is later used to recognize the person even under different environmental conditions. We employ a preprocessing step to reduce the effect of different illumination conditions, and then identify 3 regions in the face: left eye, right eye and nose–mouth. SIFT features are extracted from each region and stored in a feature vector, which is used for recognition. The matching strategy is able to discard unknown faces and the recognition process uses a Bayesian approach over ...

• Type: Conference
• Year: 2008
• Where: FGR
• Authors: Claudia Cruz, Luis Enrique Sucar, Eduardo F. Morales
• Keywords: Assume Unrealistic Conditions, Biometrics, Face Recognition, FGR 2008, Service Robot