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 in2020 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
LanguageEnglish
Published IEEE 01.03.2020
Subjects
ACNN
Emotion recognition
Face
Face recognition
Face tracking
Landmark detection
Logic gates
Occlusion
Robustness
Task analysis
Videos
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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