—Facial expression is one of the most powerful, natural, and abrupt means for human beings which have the knack to communicate emotion and regulate inter-personal behaviour. In this paper we focus on two different approaches of expression recognition. First template based method, second appearance based method i.e. principle component analysis. In template based we make use of template matching to excerpt templates of different facial components. The facial expression information is mostly concentrate on facial expression information regions, mouth, eye and eyebrow regions areas are segmented from the facial expression images. Using these templates we calculate facial characteristics points (FCP’s).Then we define 30 facial characteristic points to describe the position and shape of the above three organs to find diverse parameters which are input to the decision tree for recognizing different facial expressions.
—Decision tree, facial characteristics points extraction, PCA, feature extraction, template matching.
Priyanka. Tripathi and Kesari Verma are with the National Institute of Technology, Raipur, India (e-mail: email@example.com, firstname.lastname@example.org).
Ligendra Kumar Verma is with Raipur Institute of Technology, India (email : email@example.com)
Nazil Parveen is with Central University Bilaspur India (email: firstname.lastname@example.org)
Cite:Priyanka Tripathi M, Kesari Verma, Ligendra Kumar Verma, and Nazil Parveen, "Facial Expression Recognition Using Data Mining Algorithm," Journal of Economics, Business and Management vol. 1, no. 4, pp. 343-346, 2013.