We present a probabilistic generative model of visual attributes, together with an efficient learning algorithm. Attributes are visual qualities of objects, such as ‘red’, ...
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
ion when we annotate content. This therefore requires us to investigate and model video semantics. Because of the type and volume of data, general-purpose approaches are likely to ...
The problem of human activity recognition via visual stimuli can be approached using manifold learning, since the silhouette (binary) images of a person undergoing a smooth motion...
Tat-Jun Chin, Liang Wang, Konrad Schindler, David ...
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...