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» Sparse Flexible Models of Local Features
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IJCV
2008
266views more  IJCV 2008»
13 years 7 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
CGF
2005
186views more  CGF 2005»
13 years 7 months ago
Interpolatory Refinement for Real-Time Processing of Point-Based Geometry
The point set is a flexible surface representation suitable for both geometry processing and real-time rendering. In most applications, the control of the point cloud density is c...
Gaël Guennebaud, Loïc Barthe, Mathias Pa...
CVPR
2005
IEEE
14 years 9 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
NEUROSCIENCE
2001
Springer
13 years 12 months ago
Neural Mechanisms for Representing Surface and Contour Features
Contours and surfaces are basic qualities which are processed by the visual system to aid the successful behavior of autonomous beings within the environment. There is increasing e...
Thorsten Hansen, Heiko Neumann
ISRR
2005
Springer
118views Robotics» more  ISRR 2005»
14 years 1 months ago
A Provably Consistent Method for Imposing Sparsity in Feature-Based SLAM Information Filters
An open problem in Simultaneous Localization and Mapping (SLAM) is the development of algorithms which scale with the size of the environment. A few promising methods exploit the ...
Matthew Walter, Ryan Eustice, John J. Leonard