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CS297 ProposalVisual and Lingual Emotional Recognition using Deep Learning TechniquesAkshay Kajale akshay.kajale@sjsu.edu Advisor: Dr. Chris Pollett In this era of technology and Artificial Intelligence, there is growing demand for human computer interaction. Humans express their emotions in differwnt ways (facial, speaking etc). The aim of this project is to detect the emotions of a person using facial expression and linguistic features by implementing computer vision, and natural language processing techniques. We will develop a hybrid neural network model to identify the emotion of a person based on the facial expreesion and pitch of the voice while speaking. Schedule
Deliverables The full project will be done when CS298 is completed. The following will be done by the end of CS297: 1. Implement a neural network to detect emotion using facial recognition algorithm with good accuracy. 2. Generate a video dataset which contains a person having different facial expressions. 3. Develop a mobile application which can access both cameras at the same time using split screen. 4. Deploy the model on Mobile Application for initial testing. 5. CS297 Report Due. References [1]L. Zhang, Y. Yang, W. Li, S. Dang and M. Zhu, "Research of Facial Expression Recognition Based on Deep Learning," 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, 2018, pp. 1-4, doi: 10.1109/ICSESS.2018.8663777. [2]Mao Xu, Wei Cheng, Qian Zhao, Li Ma and Fang Xu, "Facial expression recognition based on transfer learning from deep convolutional networks," 2015 11th International Conference on Natural Computation (ICNC), Zhangjiajie, 2015, pp. 702-708, doi: 10.1109/ICNC.2015.7378076. [3]A. Fathallah, L. Abdi and A. Douik, "Facial Expression Recognition via Deep Learning," 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), Hammamet, 2017, pp. 745-750, doi: 10.1109/AICCSA.2017.124. |