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.