T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00307060" target="_blank" >RIV/68407700:21230/17:00307060 - isvavai.cz</a>

Result on the web

<a href="http://cmp.felk.cvut.cz/t-less" target="_blank" >http://cmp.felk.cvut.cz/t-less</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/WACV.2017.103" target="_blank" >10.1109/WACV.2017.103</a>

Result language

angličtina

Original language name

T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects

Original language description

We introduce T-LESS, a new public dataset for estimating the 6D pose, i.e. translation and rotation, of texture-less rigid objects. The dataset features thirty industry-relevant objects with no significant texture and no discriminative color or reflectance properties. The objects exhibit symmetries and mutual similarities in shape and/or size. Compared to other datasets, a unique property is that some of the objects are parts of others. The dataset includes training and test images that were captured with three synchronized sensors, specifically a structured-light and a time-of-flight RGB-D sensor and a high-resolution RGB camera. There are approximately 39K training and 10K test images from each sensor. Additionally, two types of 3D models are provided for each object, i.e. a manually created CAD model and a semi-automatically reconstructed one. Training images depict individual objects against a black background. Test images originate from twenty test scenes having varying complexity, which increases from simple scenes with several isolated objects to very challenging ones with multiple instances of several objects and with a high amount of clutter and occlusion. The images were captured from a systematically sampled view sphere around the object/scene, and are annotated with accurate ground truth 6D poses of all modeled objects. Initial evaluation results indicate that the state of the art in 6D object pose estimation has ample room for improvement, especially in difficult cases with significant occlusion. The T-LESS dataset is available online at cmp.felk.cvut.cz/t-less.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

<a href="/en/project/TE01020415" target="_blank" >TE01020415: V3C - Visual Computing Competence Center</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

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

Article name in the collection

2017 IEEE Winter Conference on Applications of Computer Vision (WACV)

ISBN

978-1-5090-4822-9

ISSN

2472-6737

e-ISSN

—

Number of pages

9

Pages from-to

880-888

Publisher name

IEEE

Place of publication

New Jersey

Event location

Santa Rosa

Event date

Mar 24, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000404165800093