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» Unsupervised Learning of Invariant Features Using Video
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CVPR
2007
IEEE
14 years 9 months ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson
CVPR
2004
IEEE
14 years 9 months ago
Video Data Mining Using Configurations of Viewpoint Invariant Regions
We describe a method for obtaining the principal objects, characters and scenes in a video by measuring the reoccurrence of spatial configurations of viewpoint invariant features....
Josef Sivic, Andrew Zisserman
ECCV
2004
Springer
13 years 11 months ago
Geometric Structure of Degeneracy for Multi-body Motion Segmentation
Many techniques have been proposed for segmenting feature point trajectories tracked through a video sequence into independent motions. It has been found, however, that methods tha...
Yasuyuki Sugaya, Ken-ichi Kanatani
AVSS
2003
IEEE
14 years 27 days ago
Invariant Feature Extraction and Biased Statistical Inference for Video Surveillance
Using cameras for detecting hazardous or suspicious events has spurred new research for security concerns. To make such detection reliable, researchers must overcome difficulties...
Yi-Leh Wu, Long Jiao, Gang Wu, Edward Y. Chang, Yu...
ICDAR
2003
IEEE
14 years 26 days ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...