Emotion detection using relative grid based coefficients through human facial expressions

Kudiri, K.M. and Said, A.M. and Nayan, M.Y. (2013) Emotion detection using relative grid based coefficients through human facial expressions. In: UNSPECIFIED.

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Abstract

Facial expressions are important in human computer interaction, because the machine can thereby understand human reactions and act accordingly. Facial expressions act like a nonverbal communication cues in human-human or human computer interactions. In noises environment, getting visual data is difficult. According to the relative bin sub-image based studies, high dimensionality is affecting the system which consequently affects the performance of the emotion detection system. Due to these reasons, a new approach using relative grid coefficient feature extraction through visual data is proposed. Support vector machine with radial basis kernel is used for the classification of emotions. Preliminary results showed that an average of 89 accuracy was obtained for relative grid based features. © 2013 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0; Conference of 2013 International Conference on Research and Innovation in Information Systems, ICRIIS 2013 ; Conference Date: 27 November 2013 Through 28 November 2013; Conference Code:103283
Uncontrolled Keywords: Classification of emotions; Facial Expressions; Grid-based; High dimensionality; Human facial expressions; Human machine interaction; Nonverbal communication cues; Relative sub-image based features, Communication; Feature extraction; Information systems; Support vector machines, Human computer interaction
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:51
Last Modified: 09 Nov 2023 15:51
URI: https://khub.utp.edu.my/scholars/id/eprint/3273

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