Author : Mr. L. Guru Kumar 1
Date of Publication :7th March 2017
Abstract: Feature extraction is one of the challenging issues in face recognition and matching process. Here we proposea novel method for dense featureextraction in face recognition.This methodology consists of two steps. In first step, encoding scheme is defined that shifts high dimensional data into compact representation by maximizing intra user correlation. In second step an adaptive feature matching is done for image classification which works for images with different scaling limits. This methodology is implemented on local facial database. We introduce a novel human-machine interface based on movements of head pose. This human machine interface works by detecting facial features from live cam and then tracking face features.Movement and actions of cursor are performed by using facial feature tracking. We prove that our methodology yields better results compared to state-of-art criteria, our method performs better at noisy condition, illumination changes, complex background and at different head poses.
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