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Facial feature extraction is a fundamental problem in image processing. Correct extraction of features is essential for the success of many applications. Typical feature extraction algorithms fail for low resolution images which do not contain sufficient facial details. In this paper, a region-based super-resolution aided facial feature extraction method for low resolution video sequences is described. The region based approach makes use of segmented faces as the region of interest whereby a significant reduction in computational complexity of the super-resolution algorithm is achieved. The results indicate that the region-based super-resolution aided facial feature extraction algorithm provides significant performance improvement in terms of correctly detecting the location of the facial feature points. There are 6.4 fold reductions in the computational cost.

Enhanced Facial Feature Extraction Using Region-Based Super-Resolution Aided Video Sequences