Fusion4D: Real-time Performance Capture of Challenging Scenes. We contribute a new pipeline for live multi-view performance capture, generating temporally coherent high-quality reconstructions in real-time. Our algorithm supports both incremental reconstruction, improving the surface estimation over time, as well as parameterizing the nonrigid scene motion. Our approach is highly robust to both large frame-to-frame motion and topology changes, allowing us to reconstruct extremely challenging scenes. We demonstrate advantages over related real-time techniques that either deform an online generated template or continually fuse depth data nonrigidly into a single reference model. Finally, we show geometric reconstruction results on par with offline methods which require orders of magnitude more processing time and many more RGBD cameras.
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References in zbMATH (referenced in 2 articles )
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- Xin Chen, Anqi Pang, Wei Yang, Yuexin Ma, Lan Xu, Jingyi Yu: SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos (2021) arXiv
- Lu, Feixiang; Zhou, Bin; Lu, Feng; Zhang, Yu; Chen, Xiaowu; Zhao, Qinping: Reconstructing non-rigid object with large movement using a single depth camera (2018)