{"title":"A Study of Techniques for Facial Detection and Expression Classification","authors":"G. Hemalatha, C. Sumathi, Manonmaniam Sundaranar","doi":"10.5121/IJCSES.2014.5203","DOIUrl":null,"url":null,"abstract":"Automatic recognition of facial expressions is an important component for human-machine interfaces. It has lot of attraction in research area since 1990's.Although humans recognize face without effort or delay, recognition by a machine is still a challenge. Some of its challenges are highly dynamic in their orientation, lightening, scale, facial expression and occlusion. Applications are in the fields like user authentication, person identification, video surveillance, information security, data privacy etc. The various approaches for facial recognition are categorized into two namely holistic based facial recognition and feature based facial recognition. Holistic based treat the image data as one entity without isolating different region in the face where as feature based methods identify certain points on the face such as eyes, nose and mouth etc. In this paper, facial expression recognition is analyzed with various methods of facial detection,facial feature extraction and classification.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"67","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science & Engineering Survey","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJCSES.2014.5203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 67
Abstract
Automatic recognition of facial expressions is an important component for human-machine interfaces. It has lot of attraction in research area since 1990's.Although humans recognize face without effort or delay, recognition by a machine is still a challenge. Some of its challenges are highly dynamic in their orientation, lightening, scale, facial expression and occlusion. Applications are in the fields like user authentication, person identification, video surveillance, information security, data privacy etc. The various approaches for facial recognition are categorized into two namely holistic based facial recognition and feature based facial recognition. Holistic based treat the image data as one entity without isolating different region in the face where as feature based methods identify certain points on the face such as eyes, nose and mouth etc. In this paper, facial expression recognition is analyzed with various methods of facial detection,facial feature extraction and classification.