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» Learning epipolar geometry from image sequences
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CVPR
2006
IEEE
14 years 1 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
SCIA
2005
Springer
211views Image Analysis» more  SCIA 2005»
14 years 1 months ago
Perception-Action Based Object Detection from Local Descriptor Combination and Reinforcement Learning
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Lucas Paletta, Gerald Fritz, Christin Seifert
ICCV
2005
IEEE
14 years 9 months ago
Globally Optimal Estimates for Geometric Reconstruction Problems
We introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. While traditional algorithms often suffer from either local minima or ...
Fredrik Kahl, Didier Henrion
DGCI
2000
Springer
13 years 12 months ago
Deformable Modeling for Characterizing Biomedical Shape Changes
Abstract. We present a new algorithm for modeling and characterizing shape changes in 3D image sequences of biomedical structures. Our algorithm tracks the shape changes of the obj...
Matthieu Ferrant, Benoit M. Macq, Arya Nabavi, Sim...
SACI
2007
IEEE
14 years 1 months ago
Map Building and Localization of a Robot Using Omnidirectional Image Sequences
: The paper describes a map building module, where the image sequences of the omnidirectional camera are transformed into virtual top-view ones and melted into the global dynamic m...
Zoltan Vamossy