تقرير
BundleMoCap: Efficient, Robust and Smooth Motion Capture from Sparse Multiview Videos
| العنوان: | BundleMoCap: Efficient, Robust and Smooth Motion Capture from Sparse Multiview Videos |
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| المؤلفون: | Albanis, Georgios, Zioulis, Nikolaos, Kolomvatsos, Kostas |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, Computer Science - Machine Learning |
| الوصف: | Capturing smooth motions from videos using markerless techniques typically involves complex processes such as temporal constraints, multiple stages with data-driven regression and optimization, and bundle solving over temporal windows. These processes can be inefficient and require tuning multiple objectives across stages. In contrast, BundleMoCap introduces a novel and efficient approach to this problem. It solves the motion capture task in a single stage, eliminating the need for temporal smoothness objectives while still delivering smooth motions. BundleMoCap outperforms the state-of-the-art without increasing complexity. The key concept behind BundleMoCap is manifold interpolation between latent keyframes. By relying on a local manifold smoothness assumption, we can efficiently solve a bundle of frames using a single code. Additionally, the method can be implemented as a sliding window optimization and requires only the first frame to be properly initialized, reducing the overall computational burden. BundleMoCap's strength lies in its ability to achieve high-quality motion capture results with simplicity and efficiency. More details can be found at https://moverseai.github.io/bundle/. Comment: Published in European Conference on Visual Media Production (CVMP '23) |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1145/3626495.3626511 |
| URL الوصول: | http://arxiv.org/abs/2311.12679 |
| رقم الأكسشن: | edsarx.2311.12679 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1145/3626495.3626511 |
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