W. Ohyama (Japan), M. Shridhar, and P. Watta (USA)
Computer Vision, Facial Feature Extraction, Face Detec tion, Gradient Feature, MQDF–based distance
In this paper, we propose a novel approach for the extrac tion of facial features from frontal face images. The pro posed approach involves 3 main processing stages. In the first stage, a bounding box is placed over the face. In the second stage, candidate positions for the facial features are identified using a set of MQDF-based distance functions. Finally, in the third stage, the candidate feature positions are evaluated using an MQDF-based verification function, and an optimal configuration is chosen. Results on the FERET database indicate that with a proper setting of pa rameters, the proposed algorithm can accurately extract fa cial features over many different scales.
Important Links:
Go Back
