In this paper, we demonstrate the use of learning with non-uniform error-cost as a novel technique to design a multiclass cost-sensitive classifier. We investigate two important ...
We introduce an object recognition system in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to b...
We propose a framework to learn scene semantics from surveillance videos. Using the learnt scene semantics, a video analyst can efficiently and effectively retrieve the hidden sem...
Recently a large amount of research has been devoted to
automatic activity analysis. Typically, activities have been
defined by their motion characteristics and represented by
t...
This paper introduces a fully-automated, unsupervised method to recognise sign from subtitles. It does this by using data mining to align correspondences in sections of videos. Bas...