We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex tempor...
A prototype-based approach is introduced for action
recognition. The approach represents an action as a se-
quence of prototypes for efficient and flexible action match-
ing in ...
Much of recent action recognition research is based on
space-time interest points extracted from video using a Bag
of Words (BOW) representation. It mainly relies on the discrimi...
Matteo Bregonzio (Queen Mary, University of London...
We propose to use high-level visual information to improve illuminant estimation. Several illuminant estimation approaches are applied to compute a set of possible illuminants. Fo...
Joost van de Weijer, Cordelia Schmid, Jakob J. Ver...