Work place: School of Electronics Engineering, VIT University, Chennai, Tamil Nadu, India
E-mail: manojkumar.r@vit.ac.in
Website:
Research Interests: Computational Science and Engineering, Computer systems and computational processes, Computational Learning Theory, Computer Vision, Image Compression, Image Manipulation, Image Processing, Data Structures and Algorithms
Biography
Manoj Kumar Rajagopal received his B.E degree in 2003 from University of Madras and his Ph.D. degree in 2012 from Telecom Sudparis, France. Currently he is working as Associate Professor in VIT University, Chennai. His research interest includes Computer Vision, Machine Learning and Image processing, Affective Computing. He has published nearly 10 papers in peer reviewed international journals and conferences.
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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