Our goal is to automatically determine the cast of a feature-length film. This is challenging because the cast size is not known, with appearance changes of faces caused by extrin...
We address the problem of tracking and recognizing faces in real-world, noisy videos. We track faces using a tracker that adaptively builds a target model reflecting changes in ap...
Minyoung Kim, Sanjiv Kumar, Vladimir Pavlovic, Hen...
Boosting-basedmethods have recently led to the state-ofthe-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like featu...
We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating feature...
In this paper, a novel sparse feature set is introduced into the Adaboost learning framework for multi-view face detection (MVFD), and a learning algorithm based on heuristic sear...