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» Estimating Vision Parameters given Data with Covariances
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IJCV
1998
238views more  IJCV 1998»
13 years 7 months ago
Feature Detection with Automatic Scale Selection
The fact that objects in the world appear in different ways depending on the scale of observation has important implications if one aims at describing them. It shows that the not...
Tony Lindeberg
ICPR
2004
IEEE
14 years 8 months ago
BTF Image Space Utmost Compression and Modelling Method
The bidirectional texture function (BTF) describes texture appearance variations due to varying illumination and viewing conditions. This function is acquired by large number of m...
Jirí Filip, Michael Arnold, Michal Haindl
ICPR
2002
IEEE
14 years 8 months ago
Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning
A heretofore unsolved problem of great archaeological importance is the automatic assembly of pots made on a wheel from the hundreds (or thousands) of sherds found at an excavatio...
David B. Cooper, Andrew R. Willis, Stuart Andrews,...
IPSN
2007
Springer
14 years 1 months ago
MeshEye: a hybrid-resolution smart camera mote for applications in distributed intelligent surveillance
Surveillance is one of the promising applications to which smart camera motes forming a vision-enabled network can add increasing levels of intelligence. We see a high degree of i...
Stephan Hengstler, Daniel Prashanth, Sufen Fong, H...
ICCV
2007
IEEE
14 years 9 months ago
Gradient Feature Selection for Online Boosting
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...
Ting Yu, Xiaoming Liu 0002