Pose Estimation using Local Structure-Specific Shape and Appearance Context

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Abstract

We address the problem of estimating the alignment pose between two models using structure-specific local descriptors. Our descriptors are generated using a combination of 2D image data and 3D contextual shape data, resulting in a set of semi-local descriptors containing rich appearance and shape information for both edge and texture structures. This is achieved by defining feature space relations which describe the neighborhood of a descriptor. By quantitative evaluations, we show that our descriptors provide high discriminative power compared to state of the art approaches. In addition, we show how to utilize this for the estimation of the alignment pose between two point sets. We present experiments both in controlled and real-life scenarios to validate our approach.
OriginalsprogEngelsk
TitelIEEE International Conference on Robotics and Automation (ICRA)
Antal sider8
ForlagIEEE
Publikationsdato2013
Sider2080-2087
ISBN (Trykt)978-1-4673-5641-1
DOI
StatusUdgivet - 2013
Begivenhed2013 IEEE International Conference on Robotics and Automation: Anthropomatics - Technologies for Humans - Kongresszentrum Karlsruhe, Karlsruhe, Tyskland
Varighed: 6. maj 201310. maj 2013

Konference

Konference2013 IEEE International Conference on Robotics and Automation
LokationKongresszentrum Karlsruhe
Land/OmrådeTyskland
ByKarlsruhe
Periode06/05/201310/05/2013

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