Recognition of Emotion From Facial Expression for Autism Disorder
A. Sivasangari1, Bhanu Prakash.V2, G. V. V. Rajesh3
1Dr. A. Sivasangari, Department of Information Technology, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Bhanu Prakash.V, Department of Information Technology, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
3G. V. V. Rajesh, Department of Information Technology, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 19 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 530-532 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B10950782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1095.0782S319
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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 expressions convey verbal indications that play an important role in interpersonal relationships. Despite the fact that people immediately perceive facial expressions for all intents and purposes, solid expression recognition by machine is still a challenge. From the point of view of automatic recognition, The facial expression may included the figurations of the facial parts and their spatial relationships or changes in the pigmentation of the face. The study of automatic facial recognition addresses issues relating to the static or dynamic qualities of such distortion or facial pigmentation. Use The Camera to capture the live images of autism people.
Keywords: Augmentation, Deep Convolutional Neural Network, Deep Learning, Live Facial Images, Camera, Opencv, Tensorflow.
Scope of the Article: Pattern Recognition