Abstract
Recent advancements in 3D scanning technologies enable us to acquire the hand geometry represented as a threedimensional point cloud. Providing accurate 3D hand scanning and accurately extracting its biometrics are of crucial importance for a number of applications in medical sciences, fashion industry, augmented and virtual reality (AR/VR). Traditional methods for hand measurement extraction require manual intervention using a measuring tape, which is time-consuming and highly dependent on the operator’s expertise. In this paper, we propose, to the best of our knowledge, the first deep neural network for automatic hand measurement extraction from a single 3D scan (H-Net). The proposed network follows an encoder-decoder architecture design, taking a point cloud of the hand as input and outputting the reconstructed hand mesh as well as the corresponding measurement values. In order to train the proposed deep model, a novel synthetic dataset of hands in various shapes and poses and their corresponding measurements is proposed. Experimental results on both synthetic data and real scans captured by Occipital Mark I structure sensor demonstrate that the proposed method outperforms the state-of-the-art methods in terms of accuracy and speed.
| Original language | English |
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| Title of host publication | I2MTC 2022 - IEEE International Instrumentation and Measurement Technology Conference |
| Subtitle of host publication | Instrumentation and Measurement under Pandemic Constraints, Proceedings |
| Publisher | IEEE |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-6654-8360-5 |
| ISBN (Print) | 978-1-6654-8361-2 |
| DOIs | |
| Publication status | Published - 30 Jun 2022 |
| Externally published | Yes |
| Event | 2022 IEEE International Instrumentation and Measurement Technology Conference - Ottawa, Canada Duration: 16 May 2022 → 19 May 2022 https://i2mtc2022.ieee-ims.org/ |
Publication series
| Name | Conference Record - IEEE Instrumentation and Measurement Technology Conference |
|---|---|
| ISSN (Print) | 1091-5281 |
Conference
| Conference | 2022 IEEE International Instrumentation and Measurement Technology Conference |
|---|---|
| Abbreviated title | IEEE I2MTC 2022 |
| Country/Territory | Canada |
| City | Ottawa |
| Period | 16/05/22 → 19/05/22 |
| Internet address |
Bibliographical note
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Keywords
- hand measurement extraction
- template fitting
- deep learning
- point cloud
- 3D scanning
- structure sensor Mark I