International Journal of Computer
Trends and Technology

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Volume 24 | Number 1 | Year 2015 | Article Id. IJCTT-V24P114 | DOI : https://doi.org/10.14445/22312803/IJCTT-V24P114

Facial Expression Recognition using Analytical Hierarchy Process

Vinita Phatnani, Akash Wanjari

Citation :

Vinita Phatnani, Akash Wanjari, "Facial Expression Recognition using Analytical Hierarchy Process," International Journal of Computer Trends and Technology (IJCTT), vol. 24, no. 1, pp. 69-71, 2015. Crossref, https://doi.org/10.14445/22312803/IJCTT-V24P114

Abstract

Face Expression Recognition and Analysis is an actively researched topic since early nineties due to its significant contribution in Human- Computer Interaction which has paved the way for Affect-Sensitive Computing, also called Human Centered Computing. There have been several advances in terms of face detection and tracking, feature extraction methods and the techniques adopted for expression classification. But most face expression analysis systems utilize low-level visual features to recognize face expressions, while the user perception of facial expression recognition often varies with each individual. Low level visual features suffer a high degree of variability due to a number of factors and are unstable due to the variation of imaging conditions. So it is very important to introduce the semantic knowledge into the automatic recognition process in order to improve the recognition rate. In this paper, a semantic-based facial expression recognition model is proposed that incorporate both, the low-level feature and the human semantics using a multi-criteria decision making model, called Analytical Hierarchy Process (AHP). Experimental results show that the recognition rate is improved with this approach.

Keywords

Analytical Hierarchy Process, Facial Expression Recognition, High-Level Semantic Knowledge, Low-Level Visual Feature.

References

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