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» Learning for Optical Flow Using Stochastic Optimization
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ICIP
2002
IEEE
15 years 11 months ago
Efficient selection of image patches with high motion confidence
Motion confidence measures aim to identify how well an image patch determines image motion. These kinds of confidence measures are commonly used to select points for optical flow ...
Peter Sand, Leonard McMillan
BMVC
1998
14 years 10 months ago
Comparing Different Template Features for Recognizing People by their Gait
To recognize people by their gait from a sequence of images, we have proposed a statistical approach which combined eigenspace transformation (EST) with canonical space transforma...
Ping S. Huang, Chris J. Harris, Mark S. Nixon
ISMAR
2003
IEEE
15 years 2 months ago
Augmented Reality Kanji Learning
ARToolKit programmers are familiar with the kanji symbols supplied with the distribution. Most of them have do not know what these kanji symbols mean. We propose a piece of educat...
Daniel Wagner, István Barakonyi
GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
15 years 1 months ago
A Bayesian approach to learning classifier systems in uncertain environments
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...
ICML
2008
IEEE
15 years 10 months ago
On partial optimality in multi-label MRFs
We consider the problem of optimizing multilabel MRFs, which is in general NP-hard and ubiquitous in low-level computer vision. One approach for its solution is to formulate it as...
Pushmeet Kohli, Alexander Shekhovtsov, Carsten Rot...