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APVIS
2009
15 years 4 months ago
Contextual picking of volumetric structures
This paper presents a novel method for the interactive identification of contextual interest points within volumetric data by picking on a direct volume rendered image. In clinica...
Peter Kohlmann, Stefan Bruckner, Armin Kanitsar, M...
TSP
2010
15 years 1 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
CVPR
2009
IEEE
17 years 1 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
203
Voted
CVPR
2000
IEEE
16 years 8 months ago
Hierarchical Structure and Nonrigid Motion Recovery from 2D Monocular Views
Inferring both 3D structure and motion of nonrigid objects from monocular images is an important problem in computational vision. The challenges stem not only from the absence of ...
Lin Zhou, Chandra Kambhamettu
193
Voted
CVPR
2003
IEEE
16 years 8 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai