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» Some Solutions to the Missing Feature Problem in Vision
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ICPR
2008
IEEE
14 years 2 months ago
Non-linear feature extraction by linear PCA using local kernel
This paper presents how to extract non-linear features by linear PCA. KPCA is effective but the computational cost is the drawback. To realize both non-linearity and low computati...
Kazuhiro Hotta
CVPR
2010
IEEE
14 years 23 hour ago
Local Features Are Not Lonely - Laplacian Sparse Coding for Image Classification
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
Shenghua Gao, Wai-Hung Tsang, Liang-Tien Chia, Pei...
ICPR
2010
IEEE
13 years 5 months ago
Performance Evaluation of Automatic Feature Discovery Focused within Error Clusters
We report performance evaluation of our automatic feature discovery method on the publicly available Gisette dataset: a set of 29 features discovered by our method ranks 129 among...
Sui-Yu Wang, Henry S. Baird
ICPR
2008
IEEE
14 years 2 months ago
Improvement of feature matching in catadioptric images using gyroscope data
Most of vision-based algorithms for motion and localization estimation requires matching some interest points in a pair of images. After building feature correspondence, it is pos...
Jean Charles Bazin, Inso Kweon, Cédric Demo...
CVPR
2012
IEEE
11 years 10 months ago
Classifying covert photographs
The advances in image acquisition techniques make recording images never easier and brings a great convenience to our daily life. It raises at the same time the issue of privacy p...
Haitao Lang, Haibin Ling