Abstract. This paper presents and investigates a set of local spacetime descriptors for representing and recognizing motion patterns in video. Following the idea of local features ...
—In this work we propose a dynamic-texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of te...
Feature trajectories have shown to be efficient for representing videos. Typically, they are extracted using the KLT tracker or matching SIFT descriptors between frames. However,...
Heng Wang, Alexander Kläser, Cordelia Schmid, Che...
In this paper, we propose and evaluate a novel recognition algorithm for container identifiers that effectively overcomes these difficulties and recognizes identifiers from contain...
Abstract. The recognition of events in videos is a relevant and challenging task of automatic semantic video analysis. At present one of the most successful frameworks, used for ob...
Lamberto Ballan, Marco Bertini, Alberto Del Bimbo,...