We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
As development on a software project progresses, developers shift their focus between different topics and tasks many times. Managers and newcomer developers often seek ways of un...
Analyzing the author and topic relations in email corpus is an important issue in both social network analysis and text mining. The AuthorTopic model is a statistical model that id...
Objects in the world can be arranged into a hierarchy based on their semantic meaning (e.g. organism ? animal ? feline ? cat). What about defining a hierarchy based on the visual ...
Josef Sivic, Bryan C. Russell, Andrew Zisserman, W...