“Fusion4D: real-time performance capture of challenging scenes”

  • ©Mingsong Dou, Sameh Khamis, Yury Degtyarev, Philip L. Davidson, Sean Ryan Fanello, Adarsh Kowdle, Christoph Rhemann, David Kim, Jonathan Taylor, Pushmeet Kohli, Vladimir Tankovich, and Shahram Izadi




    Fusion4D: real-time performance capture of challenging scenes

Session/Category Title:   CAPTURING HUMANS




    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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