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» On the design of robust classifiers for computer vision
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SGAI
2004
Springer
14 years 1 months ago
Interactive Selection of Visual Features through Reinforcement Learning
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Sébastien Jodogne, Justus H. Piater
ICCV
2001
IEEE
14 years 9 months ago
Face Recognition with Support Vector Machines: Global versus Component-based Approach
We present a component-based method and two global methods for face recognition and evaluate them with respect to robustness against pose changes. In the component system we first...
Bernd Heisele, Purdy Ho, Tomaso Poggio
WACV
2007
IEEE
14 years 2 months ago
A Vision System for Monitoring Intermodal Freight Trains
We describe the design and implementation of a vision based Intermodal Train Monitoring System(ITMS) for extracting various features like length of gaps in an intermodal(IM) train...
Avinash Kumar, Narendra Ahuja, John M. Hart, Vises...
ICPR
2002
IEEE
14 years 8 months ago
Robust Contrast-Invariant EigenDetection
We achieve two goals in this paper: (1) to build a novel appearance-based object representation that takes into account variations in contrast often found in training images; (2) ...
Chakra Chennubhotla, Allan D. Jepson, John Midgley
CVPR
2005
IEEE
14 years 1 months ago
The Distinctiveness, Detectability, and Robustness of Local Image Features
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...
Gustavo Carneiro, Allan D. Jepson