Work place: School of Electronics Engineering, VIT University, Chennai, Tamil Nadu, India
E-mail: manoj.prabhakaran2013@vit.ac.in
Website:
Research Interests: Human-Computer Interaction, Computational Learning Theory, Image Compression, Image Manipulation, Image Processing, Data Structures and Algorithms, Mathematical Analysis
Biography
Manoj Prabhakaran Kumar received B.E. degree in Electronics and Communication Engineering from Anna University, Coimbatore, India, in 2011, M.E in Embedded Systems and Technology from SRM University, Chennai, India, in 2013 and pursuing Ph.D. degree in School Electronics Engineering from VIT University, Chennai, India. His current research interests include Human–Computer Interaction, Affective Computing, and Human Behaviors analysis, Machine learning and Image Processing.
By Manoj Prabhakaran Kumar Manoj Kumar Rajagopal
DOI: https://doi.org/10.5815/ijisa.2018.08.08, Pub. Date: 8 Aug. 2018
This paper aims to finding happiness in human face with minimal feature vectors. In this system, the face detection and tracking are carried out by Constrained Local Model (CLM). Using CLM grid node, the entire and minimal feature vector displacement is obtained through extracted features. The feature vector displacements are computed in multi-classes of Twin- Support Vector Machines (TWSVM) classifier to evaluate the happiness. In training and testing phases, the following databases are used such as MMI database, Cohn-Kanade (CK), Extended-CK, Mahnob-Laughter and also Real Time data. Also, this paper compares the Supervised Support Vector Machines and Unsupervised Twin Support Vector Machines classifier with cross data-validation. Using the normalization of Min-max and Z-norm technique, the overall accuracy of finding happiness are computed as 86.29% and 83.79% respectively.
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