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» Feature Mining for Image Classification
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121
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ICIAP
2005
ACM
16 years 2 months ago
A New Efficient Method for Producing Global Affine Invariants
This paper introduces a new efficient way for computing affine invariant features from gray-scale images. The method is based on a novel image transform which produces infinitely m...
Esa Rahtu, Janne Heikkilä, Mikko Salo
TNN
2008
74views more  TNN 2008»
15 years 2 months ago
Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector
The matrix, as an extended pattern representation to the vector, has proven to be effective in feature extraction. But the subsequent classifier following the matrix-pattern-orien...
Zhe Wang, Songcan Chen, Jun Liu, Daoqiang Zhang
108
Voted
CVPR
2010
IEEE
15 years 11 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun
125
Voted
CVPR
2007
IEEE
16 years 4 months ago
Segmental Hidden Markov Models for View-based Sport Video Analysis
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
Yi Ding, Guoliang Fan
CVPR
2009
IEEE
1096views Computer Vision» more  CVPR 2009»
16 years 9 months ago
How far can you get with a modern face recognition test set using only simple features?
In recent years, large databases of natural images have become increasingly popular in the evaluation of face and object recognition algorithms. However, Pinto et al. previously ...
Nicolas Pinto, James J. DiCarlo, David D. Cox