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WACV
2005
IEEE
14 years 1 months ago
Incorporating Background Invariance into Feature-Based Object Recognition
Current feature-based object recognition methods use information derived from local image patches. For robustness, features are engineered for invariance to various transformation...
Andrew N. Stein, Martial Hebert
CVPR
2003
IEEE
14 years 9 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICIP
2006
IEEE
14 years 9 months ago
A Probabilistic Approach to Robust Shape Matching
We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
Graham McNeill, Sethu Vijayakumar
ICIP
2008
IEEE
14 years 9 months ago
Classification of unlabeled point sets using ANSIG
We address two-dimensional shape-based classification, considering shapes described by arbitrary sets of unlabeled points, or landmarks. This is relevant in practice because, in m...
José J. Rodrigues, João M. F. Xavier...
IBPRIA
2007
Springer
14 years 1 months ago
Boundary Shape Recognition Using Accumulated Length and Angle Information
In this paper we present a method to recognize shapes by analyzing a polygonal approximation of their boundaries. The method is independent of the used approximation method since i...
Marçal Rusiñol, Philippe Dosch, Jose...