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ECCV
2008
Springer
14 years 10 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
ECCV
2002
Springer
1127views Computer Vision» more  ECCV 2002»
14 years 10 months ago
Removing Shadows from Images
Illumination conditions cause problems for many computer vision algorithms. Inparticular, shadows in an image can cause segmentation, tracking, or recognition algorithms to fail. I...
Graham D. Finlayson, Steven D. Hordley, Mark S. Dr...
ECCV
2010
Springer
14 years 1 months ago
Robust Multi-View Boosting with Priors
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
CVPR
2011
IEEE
13 years 3 months ago
A Large-scale Benchmark Dataset for Event Recognition in Surveillance Video
We introduce a new large-scale video dataset designed to assess the performance of diverse visual event recognition algorithms with a focus on continuous visual event recognition ...
Sangmin Oh, Anthony Hoogs, A.G.Amitha Perera, Chia...
CHI
2006
ACM
14 years 8 months ago
PaperSpace: a system for managing digital and paper documents
Here we present PaperSpace a computer vision based document management system that allows users to combine paper and digital documents. Using PaperSpace users can locate paper cop...
Jeff Smith, Jeremy Long, Tanya Lung, Mohd M. Anwar...