Dynamic Vision From Images to Face Recognition

Face recognition is a task which the human visual system seems to perform almost effortlessly, yet goal of building machines with comparable capabilities has proven difficult to realize. The task requires the ability to locate and track faces through scenes which are often complex and dynamic. Recognition is difficult because of variations in factors such as lighting conditions, viewpoint, body movement and facial expression. Although evidence from psychophysical and neurobiological experiments provides intriguing insights into how we might code and recognize faces, their bearings on computational and engineering solutions are far from clear.This book describes how to build learning machines to perform face recognition in dynamic scenes. The task at hand is that of engineering robust machine vision systems that can operate under poorly controlled and changing conditions. Many of the issues raised are relevant to object recognition in general, and such visual learning machines have numerous potential applications in areas such as visual surveillance multimedia and visually mediated interaction.