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» Image sampling for localization using entropy
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CVPR
2003
IEEE
16 years 2 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
102
Voted
TCSV
2010
14 years 7 months ago
Face and Human Gait Recognition Using Image-to-Class Distance
We propose a new distance measure for face recognition and human gait recognition. Each probe image (a face image or an average human silhouette image) is represented as a set of ...
Yi Huang, Dong Xu, Tat-Jen Cham
ICCV
2005
IEEE
16 years 2 months ago
Deformation Invariant Image Matching
We propose a novel framework to build descriptors of local intensity that are invariant to general deformations. In this framework, an image is embedded as a 2D surface in 3D spac...
Haibin Ling, David W. Jacobs
90
Voted
ICPR
2010
IEEE
14 years 10 months ago
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations
Classifying images using features extracted from densely sampled local patches has enjoyed significant success in many detection and recognition tasks. It is also well known that ...
Mert Dikmen, Thomas S. Huang
82
Voted
CVPR
2008
IEEE
16 years 2 months ago
Local grouping for optical flow
Optical flow estimation requires spatial integration, which essentially poses a grouping question: what points belong to the same motion and what do not. Classical local approache...
Xiaofeng Ren