We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
This paper presents an adaptive discriminative generative model that generalizes the conventional Fisher Linear Discriminant algorithm and renders a proper probabilistic interpret...
Ruei-Sung Lin, David A. Ross, Jongwoo Lim, Ming-Hs...
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models ...
This article proposes an active basis model and a shared pursuit algorithm for learning deformable templates from image patches of various object categories. In our generative mod...
Ying Nian Wu, Zhangzhang Si, Chuck Fleming, Song C...