Project MultiLeap: Making Multiple Hand Tracking Sensors to Act Like One

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00353691" target="_blank" >RIV/68407700:21240/21:00353691 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/abstract/document/9644262" target="_blank" >https://ieeexplore.ieee.org/abstract/document/9644262</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/AIVR52153.2021.00021" target="_blank" >10.1109/AIVR52153.2021.00021</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Project MultiLeap: Making Multiple Hand Tracking Sensors to Act Like One

Popis výsledku v původním jazyce

We present a concept that provides hand tracking for virtual and extended reality, only with the use of optical sensors, without the need for the user to hold any physical controller. In this article, we propose five new algorithms further to extend our previous research and the possibilities of the hand tracking system whilst also making it more precise. The first algorithm deals with the need to calibrate the tracking system. Thanks to the new approach, we improved tracking precision by 37% over our previous solution. The second algorithm allows us to compute the precision of the hand tracking data when multiple sensors are used. The third algorithm further improves the computation of hand tracking data confidence by correctly handling the edge cases, for example, when the tracked hand is at the edge of the sensor's field of view. The fourth algorithm provides a new way to fuse the hand tracking data by using only the hand tracking data with the highest hand tracking data confidence. The fifth algorithm deals with the issue when the optical sensor misclassifies the hand chirality.

Název v anglickém jazyce

Project MultiLeap: Making Multiple Hand Tracking Sensors to Act Like One

Popis výsledku anglicky

We present a concept that provides hand tracking for virtual and extended reality, only with the use of optical sensors, without the need for the user to hold any physical controller. In this article, we propose five new algorithms further to extend our previous research and the possibilities of the hand tracking system whilst also making it more precise. The first algorithm deals with the need to calibrate the tracking system. Thanks to the new approach, we improved tracking precision by 37% over our previous solution. The second algorithm allows us to compute the precision of the hand tracking data when multiple sensors are used. The third algorithm further improves the computation of hand tracking data confidence by correctly handling the edge cases, for example, when the tracked hand is at the edge of the sensor's field of view. The fourth algorithm provides a new way to fuse the hand tracking data by using only the hand tracking data with the highest hand tracking data confidence. The fifth algorithm deals with the issue when the optical sensor misclassifies the hand chirality.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of 2021 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

ISBN

978-1-6654-3225-2

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

77-83

Název nakladatele

IEEE

Místo vydání

Beijing

Místo konání akce

Taichung

Datum konání akce

15. 11. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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