We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
We present an approach to tracking human activities in a monocular video. We model the human body by decomposing it into torso and limbs and use simple 3D shapes to approximate th...
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
In many computer vision tasks, scene changes hinder the generalization ability of trained classifiers. For instance, a human detector trained with one set of images is unlikely t...