IIUM Repository

Support vector machine for face emotion detection on real time basis

Bouhabba, El Mehdi and Shafie, Amir Akramin and Akmeliawati, Rini (2011) Support vector machine for face emotion detection on real time basis. In: 2011 4th International Conference on Mechatronics: Integrated Engineering for Industrial and Societal Development (ICOM 2011), 17-19 May, 2011, Kuala Lumpur, Malaysia.

[img] PDF (Support vector machine for face emotion detection on real time basis) - Published Version
Restricted to Repository staff only

Download (295kB) | Request a copy


Enabling computer systems to recognize facial expressions and infer emotions from them in real time presents a challenging research topic. In this paper, a real-time method is proposed as a solution to the problem of facial expression classification in video sequences. We employ an automatic facial feature tracker to perform face localization and feature extraction. The facial feature displacements in the video stream are used as input to a Support Vector Machine classifier. We evaluate our method in terms of recognition accuracy for a variety of interaction and classification scenarios. Our person-dependent and person-independent experiments demonstrate the effectiveness of a support vector machine and feature tracking approach to fully automatic, unobtrusive expression recognition in live video.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 5119/5363
Uncontrolled Keywords: emotional classification , facial expressions , real-time features tracking , vector machines
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Prof. Dr. Rini Akmeliawati
Date Deposited: 14 Nov 2011 14:43
Last Modified: 08 May 2012 14:25
URI: http://irep.iium.edu.my/id/eprint/5363

Actions (login required)

View Item View Item


Downloads per month over past year