Improved Indirect Virtual Objects Selection Methods for Cluttered Augmented Reality Environments on Mobile Devices

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU143690" target="_blank" >RIV/00216305:26230/22:PU143690 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/12654/" target="_blank" >https://www.fit.vut.cz/research/publication/12654/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/HRI53351.2022.9889374" target="_blank" >10.1109/HRI53351.2022.9889374</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Improved Indirect Virtual Objects Selection Methods for Cluttered Augmented Reality Environments on Mobile Devices

Popis výsledku v původním jazyce

The problem of selecting virtual objects within augmented reality on handheld devices has been tackled multiple times. However, evaluations were carried out on purely synthetic tasks with uniformly placed homogeneous objects, often located on a plane and with none or low occlusions. This paper presents two novel approaches to indirect object selection dealing with highly occluded objects with large spatial distribution variability and heterogeneous size and appearance. The methods are designed to enable long-term usage with a tablet-like device. One method is based on a spatially anchored hierarchy menu, and the other utilizes a crosshair and a side menu that shows candidate objects according to a custom-developed metric. The proposed approaches are compared with direct touch in the context of spatial visual programming of collaborative robots problem, on a realistic workplace and a common robotic task. The preliminary evaluation indicates that the main benefit of the proposed indirect methods could be their higher precision and higher selection confidence for the user.

Název v anglickém jazyce

Improved Indirect Virtual Objects Selection Methods for Cluttered Augmented Reality Environments on Mobile Devices

Popis výsledku anglicky

The problem of selecting virtual objects within augmented reality on handheld devices has been tackled multiple times. However, evaluations were carried out on purely synthetic tasks with uniformly placed homogeneous objects, often located on a plane and with none or low occlusions. This paper presents two novel approaches to indirect object selection dealing with highly occluded objects with large spatial distribution variability and heterogeneous size and appearance. The methods are designed to enable long-term usage with a tablet-like device. One method is based on a spatially anchored hierarchy menu, and the other utilizes a crosshair and a side menu that shows candidate objects according to a custom-developed metric. The proposed approaches are compared with direct touch in the context of spatial visual programming of collaborative robots problem, on a realistic workplace and a common robotic task. The preliminary evaluation indicates that the main benefit of the proposed indirect methods could be their higher precision and higher selection confidence for the user.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/FV40052" target="_blank" >FV40052: Test-it-off: robotizované offline testování produktů</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

HRI '22: Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction

ISBN

978-1-6654-0731-1

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

834-838

Název nakladatele

Association for Computing Machinery

Místo vydání

Sapporo, Hokkaido

Místo konání akce

Sapporo

Datum konání akce

7. 3. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000869793600112