BOP: Benchmark for 6D Object Pose Estimation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00323976" target="_blank" >RIV/68407700:21230/18:00323976 - isvavai.cz</a>

Result on the web

<a href="http://openaccess.thecvf.com/content_ECCV_2018/papers/Tomas_Hodan_PESTO_6D_Object_ECCV_2018_paper.pdf" target="_blank" >http://openaccess.thecvf.com/content_ECCV_2018/papers/Tomas_Hodan_PESTO_6D_Object_ECCV_2018_paper.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-01249-6_2" target="_blank" >10.1007/978-3-030-01249-6_2</a>

Result language

angličtina

Original language name

BOP: Benchmark for 6D Object Pose Estimation

Original language description

We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: (i) eight datasets in a unified format that cover different practical scenarios, including two new datasets focusing on varying lighting conditions, (ii) an evaluation methodology with a pose-error function that deals with pose ambiguities, (iii) a comprehensive evaluation of 15 diverse recent methods that captures the status quo of the field, and (iv) an online evaluation system that is open for continuous submission of new results. The evaluation shows that methods based on point-pair features currently perform best, outperforming template matching methods, learning-based methods and methods based on 3D local features. The project website is available at bop.felk.cvut.cz

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

ECCV2018: Proceedings of the European Conference on Computer Vision, Part X

ISBN

978-3-030-01248-9

ISSN

0302-9743

e-ISSN

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Number of pages

17

Pages from-to

19-35

Publisher name

Springer, Cham

Place of publication

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Event location

Munich

Event date

Sep 8, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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