Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments

Michael G. Adam, Sebastian Eger, Martin Piccolrovazzi, Maged Iskandar, Joern Vogel, Alexander Dietrich, Seongjien Bien, Jon Skerlj, Abdeldjallil Naceri, Eckehard Steinbach, Alin Albu-Schaeffer, Sami Haddadin, Wolfram Burgard

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

As labor shortage increases in the health sector, the demand for assistive robotics grows. However, the needed test data to develop those robots is scarce, especially for the application of active 3D object detection, where no real data exists at all. This short paper counters this by introducing such an annotated dataset of real environments. The captured environments represent areas which are already in use in the field of robotic health care research. We further provide ground truth data within one room, for assessing SLAM algorithms running directly on a health care robot.

OriginalspracheEnglisch
TitelProceedings - 2023 IEEE International Symposium on Multimedia, ISM 2023
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten260-261
Seitenumfang2
ISBN (elektronisch)9798350395761
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung2023 IEEE International Symposium on Multimedia, ISM 2023 - Laguna Hills, USA/Vereinigte Staaten
Dauer: 11 Dez. 202313 Dez. 2023

Publikationsreihe

NameProceedings - 2023 IEEE International Symposium on Multimedia, ISM 2023

Konferenz

Konferenz2023 IEEE International Symposium on Multimedia, ISM 2023
Land/GebietUSA/Vereinigte Staaten
OrtLaguna Hills
Zeitraum11/12/2313/12/23

Fingerprint

Untersuchen Sie die Forschungsthemen von „Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren