Comparative Study of Different Types of Feature Extraction Algorithms and Classifiers used in FER System
Trina Das1, Shamneesh Sharma2
1Trina Das, M.Tech Scholar, Department of Computer Science & Engineering, Alakh Prakash Goyal Shimla University, Shimla (Himachal Pradesh), India.
2Shamneesh Sharma, Head, Division of Information Technology & Associate Professor, Department of Computer Science & Engineering, Alakh Prakash Goyal Shimla University, Shimla (Himachal Pradesh), India.
Manuscript received on 26 March 2019 | Revised Manuscript received on 07 April 2019 | Manuscript Published on 18 April 2019 | PP: 789-794 | Volume-7 Issue-6S March 2019 | Retrieval Number: F03540376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The computerized identification and classification of the facial expressions has been an investigative field from very beginning. Being a major approach of emotion detection, the automatic recognition of Facial Expression has been one of the latest research topics within various fields such as computer vision, medicine and psychology since 1990’s. The ideal facial expression recognition is still a confront for a machine or computers. A numerous number of research efforts and techniques have been made in the field of facial expression recognition from still pictures and live videos. Despite of important advances, it also has some defies. This paper includes an overview of facial expression recognition techniques, related issues and few published and reviewed papers on emotion detection are summarized here briefly.
Keywords: Face Recognition, Global and Local Feature, Feature Extraction Algorithm, Classifier, FER Dataset.
Scope of the Article: Algorithm Engineering