Local Scale Adaptation to Hand Shape Model for Accurate and Robust Hand Tracking
| dc.contributor.author | Kalshetti, Pratik | en_US |
| dc.contributor.author | Chaudhuri, Parag | en_US |
| dc.contributor.editor | Dominik L. Michels | en_US |
| dc.contributor.editor | Soeren Pirk | en_US |
| dc.date.accessioned | 2022-08-10T15:19:44Z | |
| dc.date.available | 2022-08-10T15:19:44Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The accuracy of hand tracking algorithms depends on how closely the geometry of the mesh model resembles the user's hand shape. Most existing methods rely on a learned shape space model; however, this fails to generalize to unseen hand shapes with significant deviations from the training set. We introduce local scale adaptation to augment this data-driven shape model and thus enable modeling hands of substantially different sizes. We also present a framework to calibrate our proposed hand shape model by registering it to depth data and achieve accurate and robust tracking. We demonstrate the capability of our proposed adaptive shape model over the most widely used existing hand model by registering it to subjects from different demographics. We also validate the accuracy and robustness of our tracking framework on challenging public hand datasets where we improve over state-of-the-art methods. Our adaptive hand shape model and tracking framework offer a significant boost towards generalizing the accuracy of hand tracking. | en_US |
| dc.description.number | 8 | |
| dc.description.sectionheaders | Capture, Tracking, and Facial Animation | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 41 | |
| dc.identifier.doi | 10.1111/cgf.14637 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 219-229 | |
| dc.identifier.pages | 11 pages | |
| dc.identifier.uri | https://doi.org/10.1111/cgf.14637 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf14637 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
| dc.subject | CCS Concepts: Computing methodologies --> Mesh models; Parametric curve and surface models; Motion capture | |
| dc.subject | Computing methodologies | |
| dc.subject | Mesh models | |
| dc.subject | Parametric curve and surface models | |
| dc.subject | Motion capture | |
| dc.title | Local Scale Adaptation to Hand Shape Model for Accurate and Robust Hand Tracking | en_US |