DexterCap: Affordable and Automated Capture of Complex Hand-Object Interactions
| dc.contributor.author | Liang, Yutong | |
| dc.contributor.author | Xu, Shiyi | |
| dc.contributor.author | Zhang, Yulong | |
| dc.contributor.author | Zhan, Bowen | |
| dc.contributor.author | Zhang, He | |
| dc.contributor.author | Liu, Libin | |
| dc.contributor.editor | Masia, Belen | |
| dc.contributor.editor | Thies, Justus | |
| dc.date.accessioned | 2026-04-17T12:13:52Z | |
| dc.date.available | 2026-04-17T12:13:52Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | Capturing fine-grained hand-object interactions is challenging due to severe self-occlusion from closely spaced fingers and the subtlety of in-hand manipulation motions. Existing optical motion capture systems rely on expensive camera setups and extensive manual post-processing, while low-cost vision-based methods often suffer from reduced accuracy and reliability under occlusion. To address these challenges, we present DexterCap, a low-cost optical capture system for dexterous in-hand manipulation. DexterCap uses dense, character-coded marker patches to achieve robust tracking under severe self-occlusion, together with an automated reconstruction pipeline that requires minimal manual effort. With DexterCap, we introduce DexterHand, a dataset of fine-grained hand-object interactions covering diverse manipulation behaviors and objects, from simple primitives to complex articulated objects such as a Rubik's Cube. We release the dataset and code to support future research on dexterous hand-object interaction. Project website: https://pku-mocca.github.io/Dextercap-Page/ | |
| dc.description.number | 2 | |
| dc.description.sectionheaders | Digital Humans: From Capture to Control | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 45 | |
| dc.identifier.doi | 10.1111/cgf.70330 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 12 pages | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.1111/cgf70330 | |
| dc.identifier.uri | https://doi.org/10.1111/cgf70330 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | |
| dc.rights | CC-BY-4.0 | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | motion capture, hand-object interaction, optical tracking | |
| dc.subject | Computing methodologies | |
| dc.subject | Motion capture | |
| dc.title | DexterCap: Affordable and Automated Capture of Complex Hand-Object Interactions |