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IJRR
2002
218views more  IJRR 2002»
13 years 7 months ago
Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks
A key component of a mobile robot system is the ability to localize itself accurately and, simultaneously, to build a map of the environment. Most of the existing algorithms are b...
Stephen Se, David G. Lowe, James J. Little
IJCV
2008
192views more  IJCV 2008»
13 years 7 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
ICPR
2010
IEEE
13 years 7 months ago
A Discrete Labelling Approach to Attributed Graph Matching Using SIFT Features
Local invariant feature extraction methods are widely used for image-features matching. There exist a number of approaches aimed at the refinement of the matches between image-fe...
Gerard Sanromà, René Alquézar...
CVPR
2007
IEEE
14 years 9 months ago
3D Probabilistic Feature Point Model for Object Detection and Recognition
This paper presents a novel statistical shape model that can be used to detect and localise feature points of a class of objects in images. The shape model is inspired from the 3D...
Sami Romdhani, Thomas Vetter
ICCV
2005
IEEE
14 years 9 months ago
Building a Classification Cascade for Visual Identification from One Example
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...