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» On the design of robust classifiers for computer vision
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ICPR
2008
IEEE
14 years 2 months ago
Adaptive semantic Bayesian framework for image attention
Image attention is the basic technique for many computer vision applications. In this paper, we propose an adaptive Bayesian framework to detect the image attention in color image...
Wei Zhang, Q. M. Jonathan Wu, Guanghui Wang
ECCV
2006
Springer
14 years 9 months ago
Robust Attentive Behavior Detection by Non-linear Head Pose Embedding and Estimation
We present a new scheme to robustly detect a type of human attentive behavior, which we call frequent change in focus of attention (FCFA), from video sequences. FCFA behavior can b...
Nan Hu, Weimin Huang, Surendra Ranganath
ACCV
2010
Springer
13 years 2 months ago
Automatic Workflow Monitoring in Industrial Environments
Robust automatic workflow monitoring using visual sensors in industrial environments is still an unsolved problem. This is mainly due to the difficulties of recording data in work ...
Galina V. Veres, Helmut Grabner, Lee Middleton, Lu...
CVPR
2007
IEEE
14 years 9 months ago
Fast Keypoint Recognition in Ten Lines of Code
While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle pe...
Mustafa Özuysal, Pascal Fua, Vincent Lepetit

Source Code
445views
14 years 8 months ago
Blocks
Blocks is an open source modular MATLAB framework which allows the user to avoid needlessly repeating computation. Blocks may be easily used for your own experiments, and comes ...
Brian Fulkerson, Andrea Vedaldi