Online multi-face detection and tracking using detector confidence and structured SVMs

Online detection and tracking of a variable number of faces in video is a crucial component in many real-world applications ranging from video-surveillance to online gaming. In this paper we propose FAST-DT, a fully automated system capable of detecting and tracking a variable number of faces online without relying on any scene-specific cues. FAST-DT integrates a generic face detector with an adaptive structured output SVM tracker and uses the detector's continuous confidence to solve the target creation and removal problem. We improve in recall and precision over a state-of-the-art method on a video dataset of more than two hours while providing in addition an increase in throughput.