Patch-Duplets for Object Recognition and Pose Estimation

Authors:
Bjorn Johansson;Anders Moe
Affiliations:
Linköping University, Sweden;Linköping University, Sweden
Venue:
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Year:
2005

Citing 0
Cited 4

Visual-model-based, real-time 3D pose tracking for autonomous navigation: methodology and experiments

Autonomous Robots
Comparison of local image descriptors for full 6 degree-of-freedom pose estimation

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A quick scale-invariant interest point detecting approach

Machine Vision and Applications
Cylindrical Pellet Pose Estimation in Clutter using a Single Robot Mounted Camera

Proceedings of Conference on Advances In Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a view-based method for object recognition and estimation of object pose from a single image. The method is based on feature vector matching and clustering. A set of interest points is detected and combined into pairs. A pair of patches, centered around each point in the pair, is extracted from a local orientation image. The patch orientation and size depends on the relative positions of the points, whichmake them invariant to translation, rotation, and locally invariant to scale. Each pair of patches constitutes a feature vector. The method is demonstrated on a number of real images and the patch-duplet feature is compared to the SIFT feature.