The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embed...
The estimation of head pose angle from face images is an integral component of face recognition systems, human computer interfaces and other human-centered computing applications....
Vineeth Nallure Balasubramanian, Jieping Ye, Sethu...