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» Model Selection Criteria in Computer Vision: Are They Differ...
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ECCV
2004
Springer
14 years 8 months ago
Detecting Keypoints with Stable Position, Orientation, and Scale under Illumination Changes
Local feature approaches to vision geometry and object recognition are based on selecting and matching sparse sets of visually salient image points, known as `keypoints' or `p...
Bill Triggs
ICPR
2004
IEEE
14 years 7 months ago
Motion Analysis Using Frame Differences with Spatial Gradient Measures
The paper considers making inferences about the underlying true 2-D motion when only evaluations of a local block-based cost function, the mean of absolute or squared differences,...
Pekka Sangi, Janne Heikkilä, Olli Silvé...
CVPR
2004
IEEE
14 years 8 months ago
Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and Its Applications
In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
Kun Huang, René Vidal, Yi Ma
CVPR
2011
IEEE
13 years 3 months ago
Saliency Estimation Using a Non-Parametric Low-Level Vision Model
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
WACV
2008
IEEE
14 years 18 days ago
Iris Extraction Based on Intensity Gradient and Texture Difference
Biometrics has become more and more important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy. Succ...
Guodong Guo, Michael J. Jones