This paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face… Click to show full abstract
This paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face component detection and cropping. The facial components are detected and cropped accurately during all pose-changing circumstances. The cropped components are represented by the histogram of oriented gradients (HOG). The weight of each component was determined using a validation process. Combining these weights was done by a simple voting technique. Three public databases were used: the AT&T database, the PUT database, and the AR database. Several improvements are observed using the weighted voting recognition method presented in this paper.
               
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