Teach it Yourself - Fast Modeling of Industrial Objects for 6D Pose Estimation

Sølund Thomas, Thiusius Rajeeth Savarimuthu, Anders Glent Buch, Anders Billesø Beck, Norbert Krüger, Henrik Aanaes

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Abstrakt

In this paper, we present a vision system that allows a human to create new 3D models of novel industrial parts by placing the part in two different positions in the scene. The two shot modeling framework generates models with a precision that allows the model to be used for 6D pose estimation without loss in pose accuracy. We quantitatively show that our modeling framework reconstructs noisy but adequate object models with a mean RMS error at 2. 7 mm, a mean standard deviation at 0. 025mm and a completeness of 70. 3% over all 14 reconstructed models, compared to the ground truth CAD models. In addition, the models are applied in a pose estimation application, evaluated with 37 different scenes with 61 unique object poses. The pose estimation results show a mean translation error on 4. 97mm and a mean rotation error on 3. 38 degrees.

OriginalsprogEngelsk
TitelComputer Vision Systems : 10th International Conference, ICVS 2015, Copenhagen, Denmark, July 6-9, 2015, Proceedings
RedaktørerAntonios Gasteratos, Lazaros Nalpantidis, Volker Kruger, Jan-Olof Eklundh
ForlagSpringer
Publikationsdato2015
Sider289-302
ISBN (Trykt)978-3-319-20903-6
ISBN (Elektronisk)978-3-319-20904-3
DOI
StatusUdgivet - 2015
Begivenhed10th International Conference on Computer Vision Systems - København, Danmark
Varighed: 6. jul. 20159. jul. 2015

Konference

Konference10th International Conference on Computer Vision Systems
Land/OmrådeDanmark
ByKøbenhavn
Periode06/07/201509/07/2015
NavnLecture Notes in Computer Science
Vol/bind9163
ISSN0302-9743

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