Facial image pre-processing and emotion classification: A deep learning approach

Document Type

Conference Proceeding

Source of Publication

Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA

Publication Date

11-1-2019

Abstract

© 2019 IEEE. Facial emotion detection and expressions are vital for applications that require credibility assessment, evaluating truthfulness, and detection of deception. However, most of the research reveal low accuracy in emotion detection mainly due to the low quality of images under consideration. Conducting intensive pre-processing activities and using artificial intelligence especially deep learning techniques are increasing accuracy in computational predictions. Our research focuses on emotion detection using deep learning techniques and combined preprocessing activities. We propose a solution that applies and compares four deep learning models for image pre-processing with the main objective to improve emotion recognition accuracy. Our methodology includes three major stages in the data value chain, pre-processing, deep learning and post-processing. We evaluate the proposed scheme on a real facial data set, namely Facial Image Data of Indian Film Stars for our study. The experimentation compares the performance of various deep learning techniques on the facial image data and confirms that our approach enhanced significantly the image quality using intensive pre-processing and deep-learning, improves accuracy in emotion prediction.

ISBN

9781728150529

ISSN

2161-5322

Publisher

IEEE Computer Society

Volume

2019-November

Last Page

8

Disciplines

Computer Sciences

Keywords

Accuracy Improvement, Deep Learning, Deep Neural Network, Emotion Detection, Facial Emotion, Image Enhancement, Image Pre-Processing

Scopus ID

85082679982

Indexed in Scopus

yes

Open Access

no

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