Multi-face tracking based on spatio-temporal detections

Tracking-by-detection methods have become increasingly popular recently. This work presents a new multi-face tracking algorithm based on the association of detection responses given by a spatio-temporal face detector; which are considered as initial small trajectories or tracklets. An appearance model based on the spatio-termporal information is used to guide the tracker. Besides, a new adaptive Kalman filter that dynamically adjusts its parameters on the basis of the quality of the detector output is proposed. The introduced approach is evaluated on several challenging video sequences from the YouTube Faces database, achieving a very good performance.