Abstract
Around 18.5% of the Indian population of students suffer from depression and around 24.4% of students suffer from anxiety disorder. Depression and anxiety are treatable through counseling and certain medicines, and thus, to avail to this huge percentage of students, the help that they require is provided in many reputed colleges and universities. These colleges and universities hire professional counselors to cater to the needs of these students. But, as all problems are not easy to overcome, in this situation also, there is a huge problem. That problem is of students not venting out their need for counseling due to various reasons, and hence, they do not go to counselors to get themselves back in happy life. To conquer such problems, a solution is proposed in this paper, that is, the use of CCTV surveillance recording that is now readily available in various colleges and universities, along with sentiment analysis of each and every student. Their emotional well-being will be monitored through their facial landmark recognition, and if certain students are showing signs of depression through his or her activities, then their names are given to their respective counselors, so as to provide them with care and support and right guidance to start their life afresh. This paper makes use of computer vision, image processing, and convolutional neural network to complete the above-mentioned task.
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Sinha, S., Mishra, S.K., Bilgaiyan, S. (2020). Emotion Analysis to Provide Counseling to Students Fighting from Depression and Anxiety by Using CCTV Surveillance. In: Swain, D., Pattnaik, P., Gupta, P. (eds) Machine Learning and Information Processing. Advances in Intelligent Systems and Computing, vol 1101. Springer, Singapore. https://doi.org/10.1007/978-981-15-1884-3_8
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