Multi-view face detection and pose estimation employing edge-based feature vectors

A multi-view face detection and pose estimation system has been developed employing the edge-based feature representations. Using the posed face images at four angles: 0°, 30°, 60°, and 90° as templates, the performance of pose estimation of about 80% has been achieved for test images in the entire angle range of 0° - 90°. In order to further enhance the performance, the concept of focus-of-attention (FOA) has been introduced in the vector generation. Namely, edge-based feature vectors are generated from the restricted area mostly containing essential information of facial images. As a result, the detection rate has been enhanced to more than 90% for profile images, which is difficult to achieve when original edge-based vectors are used.