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Paper Details

Paper Title
Facial Feature Extraction & Appearance Based Human Affect Recognition System
Abstract
There has been enormous amount of research on face recognition which consists of modification of state of art face recognition methods to make it able to work under partial occlusion, illumination/pose changes. Those modifications came up with additional computations which have compromised with execution time for accuracy. The modified version of LRC(linear regression classification) known as CRC (census regression based classification) grabbed an attention of researchers through its recognition performance. These CRC generates census transformed test and training images then estimates importance of each pixels which takes twice amount of time than execution time of LRC. The goal of this research is to improve execution performance of CRC(census regression classification) by eventually switch to LRC face recognition system for non-Face Matching face by detecting whether the face is Face Matching or not prior to face recognition using Facial Feature Extraction of face and SVM. Experimental analysis shows that proposed occlusion Recognition method has 96% accuracy for artificially generated occlusions of face images of SQL face database and execution time has been reduced by more than 50% for non- Face Matching faces.
Keyword
face recognition, LRC, Facial Feature Extraction.
Others Details
Paper Id : 34039
Author Name : Swapnil O. Shelke
Volume/Issue No : Volume 05 Issue 08
Page No : 20-26
DOI Number : DOI:10.21090/IJAERD.34039
License : This work is licensed under a Creative Commons Attribution 4.0 International License.
website : http://www.ijaerd.com/index.php
Impact Factor : 5.71, SJIF-2017
ISSN Details : eISSN: 2348-4470, pISSN:2348-6406
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