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• W2894878561 abstract "We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from just a single RGB video. We propose a novel two-stage analysis-by-synthesis optimization whose formulation and implementation are designed for high performance. In the first stage, a skinned template model is jointly fitted to background subtracted input video, 2D and 3D skeleton joint positions found using a deep neural network, and a set of sparse facial landmark detections. In the second stage, dense non-rigid 3D deformations of skin and even loose apparel are captured based on a novel real-time capable algorithm for non-rigid tracking using dense photometric and silhouette constraints. Our novel energy formulation leverages automatically identified material regions on the template to model the differing non-rigid deformation behavior of skin and apparel. The two resulting non-linear optimization problems per frame are solved with specially tailored data-parallel Gauss-Newton solvers. To achieve real-time performance of over 25Hz, we design a pipelined parallel architecture using the CPU and two commodity GPUs. Our method is the first real-time monocular approach for full-body performance capture. Our method yields comparable accuracy with off-line performance capture techniques while being orders of magnitude faster." @default.
• W2894878561 created "2018-10-12" @default.
• W2894878561 creator A5005789795 @default.
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• W2894878561 creator A5039500794 @default.
• W2894878561 creator A5056083424 @default.
• W2894878561 creator A5076908763 @default.
• W2894878561 date "2019-03-13" @default.
• W2894878561 modified "2023-09-27" @default.
• W2894878561 title "LiveCap" @default.
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