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  Depth Sensor Based Detection of Obstacles and Notification for Virtual Reality Systems

Wozniak, P., Capobianco, A., Javahiraly, N., & Curticapean, D. (2020). Depth Sensor Based Detection of Obstacles and Notification for Virtual Reality Systems. In T. Ahram (Ed.), Advances in Human Factors in Wearable Technologies and Game Design. AHFE 2019. Advances in Intelligent Systems and Computing (pp. 271-282). Cham: Springer.

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 Creators:
Wozniak, Peter1, Author           
Capobianco, Antonio, Author
Javahiraly, Nicolas, Author
Curticapean, Dan, Author
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: Walking interfaces offer advantages in navigation of VE systems over other types of locomotion. However, VR helmets have the disadvantage that users cannot see their immediate surroundings. Our publication describes the prototypical implementation of a virtual environment (VE) system, capable of detecting possible obstacles using an RGB-D sensor. In order to warn users of potential collisions with real objects while they are moving throughout the VE tracking area, we designed 4 different visual warning metaphors: Placeholder, Rubber Band, Color Indicator and Arrow. A small pilot study was carried out in which the participants had to solve a simple task and avoid any arbitrarily placed physical obstacles when crossing the virtual scene. Our results show that the Placeholder metaphor (in this case: trees), compared to the other variants, seems to be best suited for the correct estimation of the position of obstacles and in terms of the ability to evade them.

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Language(s): eng - English
 Dates: 2020
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-030-20476-1_28
 Degree: -

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Title: Advances in Human Factors in Wearable Technologies and Game Design. AHFE 2019. Advances in Intelligent Systems and Computing
Source Genre: Proceedings
 Creator(s):
Ahram, T., Editor
Affiliations:
-
Publ. Info: Cham : Springer
Pages: - Volume / Issue: 973 Sequence Number: - Start / End Page: 271 - 282 Identifier: ISBN: 978-3-030-20475-4