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PAMI
2008
161views more  PAMI 2008»
15 years 2 months ago
Multilayered 3D LiDAR Image Construction Using Spatial Models in a Bayesian Framework
Standard 3D imaging systems process only a single return at each pixel from an assumed single opaque surface. However, there are situations when the laser return consists of multip...
Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J...
ECCV
2008
Springer
16 years 4 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
122
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CVPR
2009
IEEE
16 years 9 months ago
Discriminative Structure Learning of Hierarchical Representations for Object Detection
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
167
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MVA
2010
206views Computer Vision» more  MVA 2010»
14 years 9 months ago
Estimating the motion of plant root cells from in vivo confocal laser scanning microscopy images
Images of cellular structures in growing plant roots acquired using confocal laser scanning microscopy (CLSM) have some unusual properties that make motion estimation challenging....
Timothy J. Roberts, Stephen J. McKenna, Cheng-Jin ...
126
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JMLR
2010
165views more  JMLR 2010»
14 years 9 months ago
Learning with Blocks: Composite Likelihood and Contrastive Divergence
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...