Multi-Pose Face Detection and Tracking Using Condensation

Automatically locating face areas can advance applications either in images or videos. This paper proposes a video-based approach for face detection and tracking in an indoor environment to determine where face areas appear in video sequences. Our approach involves four main modules: an initialization module for setting all configurations, a Condensation module for face tracking, a template module for measuring the observation process in Condensation, and a correction module for correcting the tracking if the tracked face has been lost. We adapted the Condensation algorithm for dealing with the face tracking problem, and designed a checklist scheme for the template module that can record the most significant templates of the tracked face poses. We also performed experiments to demonstrate the performance and the robustness of our proposed approach for face detection and tracking.