Region based Facial Expression Recognition using Gradient Directions
Vinola C.1, Vimala Devi K.2, Valarmathi K.3, Manjula V.4, Muthurajkumar S.5
1Vinola C.*, Dept. of CSE, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India.
2VimalaDevi, K., School of CSE, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
3Valarmathi, K., Dept. of ECE, P.S.R Engineering College, Sivakasi, Tamil Nadu, India.
4Manjula V., School of IT, Vellore Institute of Technology, Vellore.
5Muthurajkumar S., Department of CT, MIT Campus, Chennai, Tamil Nadu, India.
Manuscript received on January 16, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 2771-2776 | Volume-9 Issue-4, February 2020. | Retrieval Number: L34271081219/2020©BEIESP | DOI: 10.35940/ijitee.L3427.029420
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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: Facial Expression Recognition (FER) has gained significant importance in the research field of Affective Computing in different extents. As a part of the different dimensional thinking, aiming at improving the accuracy of the recognition system and reducing the computational load, region based FER is proposed in this paper. The system is an emotion identifying system among the basic emotions, through subject independent template matching based on gradient directions. The model designed is tested on the Enhanced Cohn-Kanade (CK+) dataset. Another important contribution of the work is using only eye (including eyebrows and the nose portion near eyes) and mouth regions in the emotion recognition. The emotion classification result is 94.3% (CK+ dataset) for 6-class FER.
Keywords: Facial Expression Recognition, Histogram of Gradient Directions, Region Of Interest(ROI), Template Matching
Scope of the Article: Pattern Recognition