Enhancing Safety using AR Headsets with Motion Prediction Visualization

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksProceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten545-546
Seitenumfang2
ISBN (elektronisch)9798350348392
ISBN (Print)979-8-3503-4840-8
PublikationsstatusVeröffentlicht - 2023
Veranstaltung2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023 - Shanghai, China
Dauer: 25 März 202329 März 2023

Abstract

Pedestrian collisions are a serious safety issue when considering hazards to elderly persons and to distracted people due to AR gaming. The inability to anticipate an oncoming danger could put these pedestrians at a safety risk endangering their lives. However if we use an AR device to visualise future motion, then this could firstly help elderly wearing them to forsee any oncoming danger and secondly alert a distracted AR gamer if this information is included in the game. The RGBD sensors of an AR device continuously scans the environment to place virtual content. Our prototype idea focuses on applying motion detection and prediction algorithms to this scan data, and communicating it as information to the users. Then other traffic participants, who might potentially get in conflict with an AR headset user can be predicted in advance and informed. This can not only promote the use of AR headsets as a safety aid especially for elderly and disabled but also increase safety in outdoor spaces when using AR. In this paper we share our first results for our prototype based on the above idea where future pedestrian motions are detected and visualised with Unity on the Hololens 2.

ASJC Scopus Sachgebiete

Zitieren

Enhancing Safety using AR Headsets with Motion Prediction Visualization. / Kamalasanan, Vinu; Ai-Taan, Ahmed; Busch, Steffen et al.
Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023. Institute of Electrical and Electronics Engineers Inc., 2023. S. 545-546.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Kamalasanan, V, Ai-Taan, A, Busch, S & Sester, M 2023, Enhancing Safety using AR Headsets with Motion Prediction Visualization. in Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023. Institute of Electrical and Electronics Engineers Inc., S. 545-546, 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023, Shanghai, China, 25 März 2023. https://doi.org/10.1109/VRW58643.2023.00120
Kamalasanan, V., Ai-Taan, A., Busch, S., & Sester, M. (2023). Enhancing Safety using AR Headsets with Motion Prediction Visualization. In Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023 (S. 545-546). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VRW58643.2023.00120
Kamalasanan V, Ai-Taan A, Busch S, Sester M. Enhancing Safety using AR Headsets with Motion Prediction Visualization. in Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023. Institute of Electrical and Electronics Engineers Inc. 2023. S. 545-546 doi: 10.1109/VRW58643.2023.00120
Kamalasanan, Vinu ; Ai-Taan, Ahmed ; Busch, Steffen et al. / Enhancing Safety using AR Headsets with Motion Prediction Visualization. Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023. Institute of Electrical and Electronics Engineers Inc., 2023. S. 545-546
Download
@inproceedings{c6f80218df92489e87bc59195a1c2c39,
title = "Enhancing Safety using AR Headsets with Motion Prediction Visualization",
abstract = "Pedestrian collisions are a serious safety issue when considering hazards to elderly persons and to distracted people due to AR gaming. The inability to anticipate an oncoming danger could put these pedestrians at a safety risk endangering their lives. However if we use an AR device to visualise future motion, then this could firstly help elderly wearing them to forsee any oncoming danger and secondly alert a distracted AR gamer if this information is included in the game. The RGBD sensors of an AR device continuously scans the environment to place virtual content. Our prototype idea focuses on applying motion detection and prediction algorithms to this scan data, and communicating it as information to the users. Then other traffic participants, who might potentially get in conflict with an AR headset user can be predicted in advance and informed. This can not only promote the use of AR headsets as a safety aid especially for elderly and disabled but also increase safety in outdoor spaces when using AR. In this paper we share our first results for our prototype based on the above idea where future pedestrian motions are detected and visualised with Unity on the Hololens 2.",
author = "Vinu Kamalasanan and Ahmed Ai-Taan and Steffen Busch and Monika Sester",
note = "Funding Information: This research is funded by the DAAD under the GSSP Program with the German Research Foundation (DFG) through the Research TrainingGroup SocialCars (GRK 1931).; 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023 ; Conference date: 25-03-2023 Through 29-03-2023",
year = "2023",
doi = "10.1109/VRW58643.2023.00120",
language = "English",
isbn = "979-8-3503-4840-8",
pages = "545--546",
booktitle = "Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

Download

TY - GEN

T1 - Enhancing Safety using AR Headsets with Motion Prediction Visualization

AU - Kamalasanan, Vinu

AU - Ai-Taan, Ahmed

AU - Busch, Steffen

AU - Sester, Monika

N1 - Funding Information: This research is funded by the DAAD under the GSSP Program with the German Research Foundation (DFG) through the Research TrainingGroup SocialCars (GRK 1931).

PY - 2023

Y1 - 2023

N2 - Pedestrian collisions are a serious safety issue when considering hazards to elderly persons and to distracted people due to AR gaming. The inability to anticipate an oncoming danger could put these pedestrians at a safety risk endangering their lives. However if we use an AR device to visualise future motion, then this could firstly help elderly wearing them to forsee any oncoming danger and secondly alert a distracted AR gamer if this information is included in the game. The RGBD sensors of an AR device continuously scans the environment to place virtual content. Our prototype idea focuses on applying motion detection and prediction algorithms to this scan data, and communicating it as information to the users. Then other traffic participants, who might potentially get in conflict with an AR headset user can be predicted in advance and informed. This can not only promote the use of AR headsets as a safety aid especially for elderly and disabled but also increase safety in outdoor spaces when using AR. In this paper we share our first results for our prototype based on the above idea where future pedestrian motions are detected and visualised with Unity on the Hololens 2.

AB - Pedestrian collisions are a serious safety issue when considering hazards to elderly persons and to distracted people due to AR gaming. The inability to anticipate an oncoming danger could put these pedestrians at a safety risk endangering their lives. However if we use an AR device to visualise future motion, then this could firstly help elderly wearing them to forsee any oncoming danger and secondly alert a distracted AR gamer if this information is included in the game. The RGBD sensors of an AR device continuously scans the environment to place virtual content. Our prototype idea focuses on applying motion detection and prediction algorithms to this scan data, and communicating it as information to the users. Then other traffic participants, who might potentially get in conflict with an AR headset user can be predicted in advance and informed. This can not only promote the use of AR headsets as a safety aid especially for elderly and disabled but also increase safety in outdoor spaces when using AR. In this paper we share our first results for our prototype based on the above idea where future pedestrian motions are detected and visualised with Unity on the Hololens 2.

UR - http://www.scopus.com/inward/record.url?scp=85159694486&partnerID=8YFLogxK

U2 - 10.1109/VRW58643.2023.00120

DO - 10.1109/VRW58643.2023.00120

M3 - Conference contribution

AN - SCOPUS:85159694486

SN - 979-8-3503-4840-8

SP - 545

EP - 546

BT - Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

Y2 - 25 March 2023 through 29 March 2023

ER -

Von denselben Autoren