Multi-pose face detection for accurate face logging

In this paper we present a technique for real-time face logging in video streams. Our system is capable of detecting faces across a range of poses and of tracking multiple targets in real time, grabbing face images and evaluating their quality in order to store only the best for each detected target. An advantage of our approach is that we qualify every logged face in terms of a quality measure based both on face pose and on resolution. Extensive qualitative and quantitative evaluation of the performance of our system is provided on many hours of realistic surveillance footage captured in different environments. Results show that our system can simultaneously minimizing false positives and identity mismatches, while balancing this against the need to obtain face images of all people in a scene.