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» Feature Space Trajectory Methods for Active Computer Vision
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CVPR
2006
IEEE
14 years 11 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
CVPR
2009
IEEE
1561views Computer Vision» more  CVPR 2009»
15 years 4 months ago
SURFTrac: Efficient Tracking and Continuous Object Recognition using Local Feature Descriptors
We present an efficient algorithm for continuous image recognition and feature descriptor tracking in video which operates by reducing the search space of possible interest poin...
Duy-Nguyen Ta (Georgia Institute of Technology), W...
CVPR
2007
IEEE
14 years 11 months ago
Cast Shadow Removal Combining Local and Global Features
In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM t...
Zhou Liu, Kaiqi Huang, Tieniu Tan, Liangsheng Wang
ICPR
2008
IEEE
14 years 3 months ago
Hallucinating facial images and features
In facial image analysis, image resolution is an important factor which has great influence on the performance of face recognition systems. As for lowresolution face recognition p...
Bo Li, Hong Chang, Shiguang Shan, Xilin Chen, Wen ...
ICCV
1995
IEEE
14 years 21 days ago
Object Indexing Using an Iconic Sparse Distributed Memory
A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...
Rajesh P. N. Rao, Dana H. Ballard