The aim of this work is to investigate how to exploit the temporal information in a video sequence for the task of face recognition. Following the approach in [11], we propose a p...
Abstract. This paper addresses the problem of how to learn an appropriate feature representation from video to benefit video-based face recognition. By simultaneously exploiting th...
Abstract. In this paper a new extension of the CONDENSATION algorithm, with application to infants face tracking, will be introduced. In this work we address the problem of trackin...
Luigi Bagnato, Matteo Sorci, Gianluca Antonini, Gi...
Human recognition from video requires solving the two tasks, recognition and tracking, simultaneously. This leads to a parameterized time series state space model, representing bo...
In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approa...