3D Face Recognition

The survival of an individual in a socially complex world depends greatly on the ability to interpret visual information about the age, sex, race, identity and emotional state of another person based on that person’s face. Despite a variety of different adverse conditions (varying facial expressions and facial poses, differences in illumination and appearance), humans can perform face identification with remarkable robustness without conscious effort. Face recognition research using automatic or semi-automatic techniques emerged in the 1960s, and especially in the last two decades it has received significant attention. One reason for this growing interest is the wide range of possible applications for face recognition systems. Another reason is the emergence of affordable hardware, such as digital photography and video, which have made the acquisition of high-quality and highresolution images much more ubiquitous. Despite this growing attention, the current stateof-the-art face recognition systems perform well when facial images are captured under uniform and controlled conditions. However, the development of face recognition systems that work robustly in uncontrolled situations is still an open research issue. Even though there are various alternative biometric techniques that perform very well today, e.g. fingerprint analysis and iris scans, these methods require the cooperation of the subjects and follow a relatively strict data acquisition protocol. Face recognition is much more flexible since subjects are not necessarily required to cooperate or even be aware of being scanned and identified. This makes face recognition a less intrusive and potentially more effective identification technique. Finally, the public’s perception of the face as a biometric modality is more positive compared to the other modalities (Hietmeyer, 2000).