Programs
- M. Tech. in Automotive Engineering -Postgraduate
- Building Disaster Resilience and Social Responsibility through Experiential Learning: Integrating AI, GIS, and Remote Sensing -Certificate
The proposed work aims to detect the suspicious activity detection in an examination hall. The system framework consists of three parts to monitor the student activity during examination. Firstly, the face region of the students is detected and their orientation is monitored using Haar feature Extraction. Secondly, the hand contact detection is analyzed when two students exchange papers or any other foreign objects between them by grid formation. Thirdly, the hand signaling of the student using convex hull is recognized and the alert is given to the invigilator.
