A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method
Abstract Hand contact data, reflecting the intricate behaviours of human hands during object operation, exhibits significant potential for analysing hand operation patterns to guide the design of hand-related sensors and robots, and predicting object properties. However, these potential applications...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04770-x |
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| author | Zelin Chen Hanlu Chen Yiming Ouyang Chenhao Cao Wei Gao Qiqiang Hu Hu Jin Shiwu Zhang |
| author_facet | Zelin Chen Hanlu Chen Yiming Ouyang Chenhao Cao Wei Gao Qiqiang Hu Hu Jin Shiwu Zhang |
| author_sort | Zelin Chen |
| collection | DOAJ |
| description | Abstract Hand contact data, reflecting the intricate behaviours of human hands during object operation, exhibits significant potential for analysing hand operation patterns to guide the design of hand-related sensors and robots, and predicting object properties. However, these potential applications are hindered by the constraints of low resolution and incomplete capture of the hand contact data. Leveraging a non-contact and high-precision 3D scanning method for surface capture, a high-resolution and whole-body hand contact dataset, named as Ti3D-contact, is constructed in this work. The dataset, with an average resolution of 0.72 mm, contains 1872 sets of texture images and 3D models. The contact area during hand operation is whole-body painted on gloves, which are captured as the high-resolution original hand contact data through a 3D scanner. Reliability validation on Ti3D-contact is conducted and hand movement classification with 95% precision is achieved using the acquired hand contact dataset. The properties of high-resolution and whole-body capturing make the acquired dataset exhibit a promising potential application in hand posture recognition and hand movement prediction. |
| format | Article |
| id | doaj-art-d3aa5d83b22149cf9cc41362c8800b51 |
| institution | DOAJ |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-d3aa5d83b22149cf9cc41362c8800b512025-08-20T02:51:23ZengNature PortfolioScientific Data2052-44632025-03-0112111710.1038/s41597-025-04770-xA high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning methodZelin Chen0Hanlu Chen1Yiming Ouyang2Chenhao Cao3Wei Gao4Qiqiang Hu5Hu Jin6Shiwu Zhang7Institute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaDepartment of Biomedical Engineering, City University of Hong KongInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaAbstract Hand contact data, reflecting the intricate behaviours of human hands during object operation, exhibits significant potential for analysing hand operation patterns to guide the design of hand-related sensors and robots, and predicting object properties. However, these potential applications are hindered by the constraints of low resolution and incomplete capture of the hand contact data. Leveraging a non-contact and high-precision 3D scanning method for surface capture, a high-resolution and whole-body hand contact dataset, named as Ti3D-contact, is constructed in this work. The dataset, with an average resolution of 0.72 mm, contains 1872 sets of texture images and 3D models. The contact area during hand operation is whole-body painted on gloves, which are captured as the high-resolution original hand contact data through a 3D scanner. Reliability validation on Ti3D-contact is conducted and hand movement classification with 95% precision is achieved using the acquired hand contact dataset. The properties of high-resolution and whole-body capturing make the acquired dataset exhibit a promising potential application in hand posture recognition and hand movement prediction.https://doi.org/10.1038/s41597-025-04770-x |
| spellingShingle | Zelin Chen Hanlu Chen Yiming Ouyang Chenhao Cao Wei Gao Qiqiang Hu Hu Jin Shiwu Zhang A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method Scientific Data |
| title | A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method |
| title_full | A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method |
| title_fullStr | A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method |
| title_full_unstemmed | A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method |
| title_short | A high-resolution and whole-body dataset of hand-object contact areas based on 3D scanning method |
| title_sort | high resolution and whole body dataset of hand object contact areas based on 3d scanning method |
| url | https://doi.org/10.1038/s41597-025-04770-x |
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