White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Towards Emotion Recognition using Evolutionary Computation

Tsai, Jing-Ling (2014) Towards Emotion Recognition using Evolutionary Computation. MSc by research thesis, University of York.

Jing-Ling Thesis.pdf
Available under License Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 UK: England & Wales.

Download (10Mb) | Preview


Facial expression recognition and analysis are difficult because huge amounts of input data needs to be processed and automation is even more complex. However, Evolutionary Computing (EC) can be good at complex tasks. For implementation, Evolvable Hardware (EHW) is an advantageous technology which is fast in real-time situations. This thesis uses Evolutionary Computing (EC) for facial expression analysis, and proposes new algorithms to undertake a limited set of facial expression analysis. Compared with conventional classifiers such as Support Vector Machines ( SVMs ), results of using a Cartesian Genetic Programming ( CGP ) classifier show better effectiveness when using the technique. Finally, this thesis discusses Evolvable Hardware (EHW) but does not implement it.

Item Type: Thesis (MSc by research)
Keywords: facial expression recognition
Academic Units: The University of York > Electronics (York)
Depositing User: Ms Jing-Ling Tsai
Date Deposited: 20 Apr 2016 12:06
Last Modified: 20 Apr 2016 12:06
URI: http://etheses.whiterose.ac.uk/id/eprint/12503

You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.

Actions (repository staff only: login required)