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A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras
This article presents a novel method for measuring contact points in human–object interaction. Research in multiple prehension-related fields, e.g., action planning, affordance, motor function, ergonomics, and robotic grasping, benefits from accurate and precise measurements of contact points betwee...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883210/ https://www.ncbi.nlm.nih.gov/pubmed/35237668 http://dx.doi.org/10.3389/frobt.2021.800131 |
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author | Hakala, Jussi Häkkinen, Jukka |
author_facet | Hakala, Jussi Häkkinen, Jukka |
author_sort | Hakala, Jussi |
collection | PubMed |
description | This article presents a novel method for measuring contact points in human–object interaction. Research in multiple prehension-related fields, e.g., action planning, affordance, motor function, ergonomics, and robotic grasping, benefits from accurate and precise measurements of contact points between a subject’s hands and objects. During interaction, the subject’s hands occlude the contact points, which poses a major challenge for direct optical measurement methods. Our method solves the occlusion problem by exploiting thermal energy transfer from the subject’s hand to the object surface during interaction. After the interaction, we measure the heat emitted by the object surface with four high-resolution infrared cameras surrounding the object. A computer-vision algorithm detects the areas in the infrared images where the subject’s fingers have touched the object. A structured light 3D scanner produces a point cloud of the scene, which enables the localization of the object in relation to the infrared cameras. We then use the localization result to project the detected contact points from the infrared camera images to the surface of the 3D model of the object. Data collection with this method is fast, unobtrusive, contactless, markerless, and automated. The method enables accurate measurement of contact points in non-trivially complex objects. Furthermore, the method is extendable to measuring surface contact areas, or patches, instead of contact points. In this article, we present the method and sample grasp measurement results with publicly available objects. |
format | Online Article Text |
id | pubmed-8883210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88832102022-03-01 A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras Hakala, Jussi Häkkinen, Jukka Front Robot AI Robotics and AI This article presents a novel method for measuring contact points in human–object interaction. Research in multiple prehension-related fields, e.g., action planning, affordance, motor function, ergonomics, and robotic grasping, benefits from accurate and precise measurements of contact points between a subject’s hands and objects. During interaction, the subject’s hands occlude the contact points, which poses a major challenge for direct optical measurement methods. Our method solves the occlusion problem by exploiting thermal energy transfer from the subject’s hand to the object surface during interaction. After the interaction, we measure the heat emitted by the object surface with four high-resolution infrared cameras surrounding the object. A computer-vision algorithm detects the areas in the infrared images where the subject’s fingers have touched the object. A structured light 3D scanner produces a point cloud of the scene, which enables the localization of the object in relation to the infrared cameras. We then use the localization result to project the detected contact points from the infrared camera images to the surface of the 3D model of the object. Data collection with this method is fast, unobtrusive, contactless, markerless, and automated. The method enables accurate measurement of contact points in non-trivially complex objects. Furthermore, the method is extendable to measuring surface contact areas, or patches, instead of contact points. In this article, we present the method and sample grasp measurement results with publicly available objects. Frontiers Media S.A. 2022-02-14 /pmc/articles/PMC8883210/ /pubmed/35237668 http://dx.doi.org/10.3389/frobt.2021.800131 Text en Copyright © 2022 Hakala and Häkkinen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Hakala, Jussi Häkkinen, Jukka A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras |
title | A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras |
title_full | A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras |
title_fullStr | A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras |
title_full_unstemmed | A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras |
title_short | A Method for Measuring Contact Points in Human–Object Interaction Utilizing Infrared Cameras |
title_sort | method for measuring contact points in human–object interaction utilizing infrared cameras |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883210/ https://www.ncbi.nlm.nih.gov/pubmed/35237668 http://dx.doi.org/10.3389/frobt.2021.800131 |
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