SADGF: Surveillance based Anxiety Detection using Gender-based Facial Emotion Recognition

Care for elders and children is vital and important in the present era. With the advancement in Vision applications, it’s become feasible to build models for detecting anxiety. Existing methodologies like smart home devices that measure the heart rate, blood pressure etc., are not sufficient information that gives family members, doctors, caretakers the accurate feedback on mental health. The objective of this work is to develop an effective classification framework that recognizes the facial emotion of the concerned person using video surveillance data. The proposed framework performs Facial Recognition, Emotion Detection and Gender Detection using CNN model.