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Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking

Stoiber, Manuel and Elsayed, Mariam and Reichert, Anne Elisabeth and Steidle, Florian and Lee, Dongheui and Triebel, Rudolph (2023) Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking. In: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023. IEEE. IEEE/RSJ International Conference on Intelligent Robots (IROS) 2023, Detroit, IL, USA. doi: 10.1109/IROS55552.2023.10341961. ISBN 978-166549190-7. ISSN 2153-0858.

Full text not available from this repository.

Official URL: https://ieeexplore.ieee.org/document/10341961

Abstract

In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual appearance and geometry to estimate object poses. The algorithm extends our previous method ICG, which uses geometry, to additionally consider surface appearance. In general, object surfaces contain local characteristics from text, graphics, and patterns, as well as global differences from distinct materials and colors. To incorporate this visual information, two modalities are developed. For local characteristics, keypoint features are used to minimize distances between points from keyframes and the current image. For global differences, a novel region approach is developed that considers multiple regions on the object surface. In addition, it allows the modeling of external geometries. Experiments on the YCB-Video and OPT datasets demonstrate that our approach ICG+ performs best on both datasets, outperforming both conventional and deep learning-based methods. At the same time, the algorithm is highly efficient and runs at more than 300 Hz. The source code of our tracker is publicly available.

Item URL in elib:https://elib.dlr.de/195723/
Document Type:Conference or Workshop Item (Speech)
Title:Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Stoiber, ManuelUNSPECIFIEDhttps://orcid.org/0000-0002-0762-9288UNSPECIFIED
Elsayed, MariamUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Reichert, Anne ElisabethUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Steidle, FlorianUNSPECIFIEDhttps://orcid.org/0000-0001-6935-9810UNSPECIFIED
Lee, DongheuiUNSPECIFIEDhttps://orcid.org/0000-0003-1897-7664UNSPECIFIED
Triebel, RudolphUNSPECIFIEDhttps://orcid.org/0000-0002-7975-036XUNSPECIFIED
Date:2023
Journal or Publication Title:2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.1109/IROS55552.2023.10341961
Publisher:IEEE
ISSN:2153-0858
ISBN:978-166549190-7
Status:Published
Keywords:object tracking;
Event Title:IEEE/RSJ International Conference on Intelligent Robots (IROS) 2023
Event Location:Detroit, IL, USA
Event Type:international Conference
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Multisensory World Modelling (RM) [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Institute of Robotics and Mechatronics (since 2013)
Deposited By: Strobl, Dr. Klaus H.
Deposited On:03 Jul 2023 08:34
Last Modified:23 Jan 2024 12:40

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