We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
Graham Taylor, Leonid Sigal, David Fleet, Geoffrey...
Psychologists have proposed that many human-object interaction activities form unique classes of scenes. Recognizing these scenes is important for many social functions. To enable...
Historically non-rigid shape recovery and articulated pose estimation have evolved as separate fields. Recent methods for non-rigid shape recovery have focused on improving the a...
We present a generic objectness measure, quantifying how
likely it is for an image window to contain an object of
any class. We explicitly train it to distinguish objects with
a...
Pierre America, Robin Milner, Oscar Nierstrasz, Ma...
Visual recognition and detection are computationally intensive tasks and current research efforts primarily focus on solving them without considering the computational capability ...
We present an algorithm to remove wobble artifacts from a video captured with a rolling shutter camera undergoing large accelerations or jitter. We show how estimating the rapid m...
Simon Baker, Eric Bennett, Sing Bing Kang, Richard...
The widespread availability of digital cameras and ubiquitous Internet access have facilitated the creation of massive image collections. These collections can be highly interconn...
Many computer vision problems involving feature correspondence among images can be formulated as an assignment problem with a quadratic cost function. Such problems are computatio...
We analyze a previously unexplored generalization of the scalar total variation to vector-valued functions, which is motivated by geometric measure theory. A complete mathematical...