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Publication Type : Journal Article
Publisher : International Journal of Computers and Applications
Source : International Journal of Computers and Applications, Taylor & Francis, p.1-10 (2019)
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2019
Abstract : Video surveillance, within prisons, monitor the emotional status of inmates, as human emotions provide insight into their intended actions. This work attempts to build an automated system that cognizes human emotion from the pattern of pixels in a facial image. In this paper, a solution based on Iterative Optimization Strategy is proposed to minimize the loss function. The proposed strategy is applied in the Fully Connected layer of Deep ConvNet. To evaluate the performance of the system we use two benchmark datasets named Japanese Female Facial Expression database and Kaggle Facial Expression Recognition dataset respectively. The system was manually tested with captured video, and video from a real documentary on YouTube. From the results, we could see that the proffered system achieves a precision, i.e. (the closeness of agreement among a set of results) of 0.93.
Cite this Research Publication : K. S. Gautam and Dr. Senthil Kumar T., “Video analytics-based facial emotion recognition system for smart buildings”, International Journal of Computers and Applications, pp. 1-10, 2019.