We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
In order to recover spectral reflectances or transmittances using a multispectral imaging based technique, it is necessary to know the spectral radiance of the illuminant used to ...
Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, ...
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...