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» Local Features, All Grown Up
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CVPR
2006
IEEE
14 years 7 months ago
Local Features, All Grown Up
We present a technique to adapt the domain of local features through the matching process to augment their discriminative power. We start with local affine features selected and n...
Andrea Vedaldi, Stefano Soatto
IJCV
2008
241views more  IJCV 2008»
13 years 4 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe
CVPR
2006
IEEE
14 years 7 months ago
Multiclass Object Recognition with Sparse, Localized Features
We apply a biologically inspired model of visual object recognition to the multiclass object categorization problem. Our model modifies that of Serre, Wolf, and Poggio. As in that...
Jim Mutch, David G. Lowe
RAS
2007
85views more  RAS 2007»
13 years 4 months ago
Self-localization in non-stationary environments using omni-directional vision
This paper presents an image-based approach for localization in non-static environments using local feature descriptors, and its experimental evaluation in a large, dynamic, popul...
Henrik Andreasson, André Treptow, Tom Ducke...
CVPR
2009
IEEE
15 years 21 hour ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...