huzhangron/Cheat-Detection

System for detection of abnormal or cheating activities in exam. This is done by using artificial neural networks for detecting the body posture of the student during the examination using the cctv footage of the classroom. Actions like turning back, bending etc are detected. Faces are registered to a database by pre-computing the face embeddings of the students.The student is recognised using facial recognition and a report about his activities along with a timestamp is sent to the examiners following which action can be taken after reviewing the report . Technologies involved are: machine learning for detection of student cheating activity in exam; OpenCV and deep learning for face recognition and identification. The database used is SQLite.

Python