Dense Extraction of Features from Salient Regions for Face Recognition

Abstract In this paper we propose a robust method for face recognition using a descriptor which has been designed to search for features using a grid pattern. This is different from popular key point descriptors which search images only in positions where they expect to extract the most features. An image segmentation technique to modify the representations of images of some standard datasets by enhancing its salient features. The descriptor provides us with a vector of key points of the image. The features obtained from the keypoints that are extracted are aggregated using a feature aggregator. A comparison study on the results obtained from classification of these aggregated features using different non-linear machine learning classifiers is performed.