Reliable and fast tracking of faces under varying pose

Abstract

This paper presents a system that is able to track multiple faces under varying pose (tilted and rotated) reliably in real-time. The system consists of two interactive modules. The first module performs detection of face subject to rotations. The second does online learning based face tracking. A mechanism of switching between the two modules is embedded into the system to automatically decide the best strategy for reliable tracking. The mechanism enables smooth transit between the detection and tracking module when one of them gives no results or unreliable results. Results demonstrate that the system can make reliable real-time tracking of multiple faces in complex background under out-of-plane rotation, up to 90 degree tilting, fast nonlinear motion, partial occlusion, large scale changes, and camera motion