Building a computation savings real-time face detection and recognition system

This paper presents two techniques in developing a computation savings Real-Time Face Detection and Recognition System. There have been numerous techniques proposed for face detection and face recognition. Most techniques emphasize on the efficiency in getting positive results, but when come to implementation in a real-time system, speed is vital. We focuses on our proposed methods to speed up and optimize the system components, e.g. the image resolution resizing technique to perform faster face detection in high resolution image, and face tracking to reduce redundant processes in face recognition. Our system testing reveals that the techniques are effective whereby the system is successfully optimized to have improved computation speed especially in a computationally constrained task environment, thus making it compatible for real-time applications.