Occlusion-aware Dynamic Human Emotion Recognition Using Landmark Detection

Human emotion analysis depends upon the accurate identification of key frames and balanced representation of facial features. Accurate identification and tracking of facial features while including variations in pose, face shape, illumination, and image resolution is very much essential for serving...

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Bibliographic Details
Published in:	2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) pp. 795 - 799
Main Authors:	Engoor, Smitha, SendhilKumar, S., Hepsibah Sharon, C., Mahalakshmi, G.S.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-03-2020
Subjects:	ACNN Emotion recognition Face Face recognition Face tracking Landmark detection Logic gates Occlusion Robustness Task analysis Videos
Online Access:	Get full text
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Summary:	Human emotion analysis depends upon the accurate identification of key frames and balanced representation of facial features. Accurate identification and tracking of facial features while including variations in pose, face shape, illumination, and image resolution is very much essential for serving the purpose. The complexity improves when the task has to be performed from videos since tracking human emotions frame-wise is cumbersome. Face alignment issues and occlusions need to be taken into account in a robust manner. This paper proposes novel methods based on ACNN for dynamic emotion recognition from human videos.
ISBN:	1728151961 9781728151960
ISSN:	2575-7288
DOI:	10.1109/ICACCS48705.2020.9074318