A low-cost non-intrusive spatial hand tracking pipeline for product-process interaction

J. Gopsill; A. Kukreja; Christopher Michael Jason Cox; C. Snider

doi:10.1017/pds.2024.209

A low-cost non-intrusive spatial hand tracking pipeline for product-process interaction

J. Gopsill^*, A. Kukreja, Christopher Michael Jason Cox, C. Snider

^*Corresponding author for this work

School of Electrical, Electronic and Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

Hands are the sensors and actuators for many design tasks. While several tools exist to capture human interaction and pose, many are expensive and require intrusive measurement devices to be placed on participants and often takes them out of the natural working environment. This paper reports a novel workflow that combines computer vision, several Machine Learning algorithms, and geometric transformations to provide a low-cost non-intrusive means of spatially tracking hands. A ±3mm position accuracy was attained across a series of 3-dimensional follow the path studies.

Original language	English
Title of host publication	Proceedings of the Design Society
Pages	2069-2078
Number of pages	10
Volume	4
DOIs	https://doi.org/10.1017/pds.2024.209
Publication status	Published - 16 May 2024
Event	Design 2024: 18th International Design Conference - Hotel Croatia Cavtat, Cavtat, Dubrovnik, Croatia Duration: 20 May 2024 → 23 May 2024 https://www.designconference.org/

Publication series

Name	Proceedings of the Design Society
Publisher	Cambridge University Press
ISSN (Electronic)	2732-527X

Conference

Conference	Design 2024: 18th International Design Conference
Country/Territory	Croatia
City	Cavtat, Dubrovnik
Period	20/05/24 → 23/05/24
Internet address	https://www.designconference.org/

Bibliographical note

Publisher Copyright:
© The Author(s), 2024.

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10.1017/pds.2024.209Licence: CC BY-NC-ND

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title = "A low-cost non-intrusive spatial hand tracking pipeline for product-process interaction",

abstract = "Hands are the sensors and actuators for many design tasks. While several tools exist to capture human interaction and pose, many are expensive and require intrusive measurement devices to be placed on participants and often takes them out of the natural working environment. This paper reports a novel workflow that combines computer vision, several Machine Learning algorithms, and geometric transformations to provide a low-cost non-intrusive means of spatially tracking hands. A ±3mm position accuracy was attained across a series of 3-dimensional follow the path studies.",

author = "J. Gopsill and A. Kukreja and Cox, {Christopher Michael Jason} and C. Snider",

note = "Publisher Copyright: {\textcopyright} The Author(s), 2024.; Design 2024: 18th International Design Conference ; Conference date: 20-05-2024 Through 23-05-2024",

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month = may,

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doi = "10.1017/pds.2024.209",

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AU - Cox, Christopher Michael Jason

AU - Snider, C.

PY - 2024/5/16

Y1 - 2024/5/16

N2 - Hands are the sensors and actuators for many design tasks. While several tools exist to capture human interaction and pose, many are expensive and require intrusive measurement devices to be placed on participants and often takes them out of the natural working environment. This paper reports a novel workflow that combines computer vision, several Machine Learning algorithms, and geometric transformations to provide a low-cost non-intrusive means of spatially tracking hands. A ±3mm position accuracy was attained across a series of 3-dimensional follow the path studies.

AB - Hands are the sensors and actuators for many design tasks. While several tools exist to capture human interaction and pose, many are expensive and require intrusive measurement devices to be placed on participants and often takes them out of the natural working environment. This paper reports a novel workflow that combines computer vision, several Machine Learning algorithms, and geometric transformations to provide a low-cost non-intrusive means of spatially tracking hands. A ±3mm position accuracy was attained across a series of 3-dimensional follow the path studies.

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U2 - 10.1017/pds.2024.209

DO - 10.1017/pds.2024.209

M3 - Conference Contribution (Conference Proceeding)

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EP - 2078

BT - Proceedings of the Design Society

T2 - Design 2024: 18th International Design Conference

Y2 - 20 May 2024 through 23 May 2024

ER -

A low-cost non-intrusive spatial hand tracking pipeline for product-process interaction

Abstract

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