Psychological health of college students prove a vital role on their overall academic performance. Neglecting this can result in several problems such as stress, anxiety, depression etc. These problems need to be detected and controlled at the initial stages itself for the better mental health of the student. Detecting depression in a vast no of college students is challenging task. Most of the students are totally unaware that they may be having depression. If at all they are aware of it, some students conceal their depression from everyone. So an automated system is required that will pick out the students who are dealing with depression. A system has been proposed here which captures frontal face videos of college students, extracts the facial features from each frame and analyses these facial features to detect signs of depression in them. This system will be trained with of frontal face images of happy, contempt and disgust faces. The presence of these features in the video frames will be analyzed to predict depression in the students.
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D. Venkataraman and Parameswaran, N. S., “Extraction of Facial Features for Depression Detection among Students”, International Journal of Pure and Applied Mathematics, vol. 118, pp. 455-462, 2018.