SegmentedFusion: 3D Human Body Reconstruction using Stitched Bounding Boxes
SegmentedFusion: 3D Human Body Reconstruction using Stitched Bounding Boxes
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SegmentedFusion：使用缝合边界框进行 3D 人体重建
DOI：
10.1109/3dv.2018.00031
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
and R. Taniguchi
中科院分区：
文献类型：
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作者：
Y. Shih-Hsuan;D. Thomas;A. Sugimoto;S.-H. Lai;and R. Taniguchi
SegmentedFusion是一种利用单台深度相机的骨骼信息重建非刚性人体三维模型的方法。我们的方法估计了一个密集的体积6D运动场，通过将人体分割成不同的部分并为每个部分建立一个规范空间，将集成模型扭曲成实时帧。这项工作的关键特点是为每个部分创建一个变形和连接的规范体积，并使用它来集成数据。通过混合几个刚性变换，可以有效地表示一个体的密集体积翘曲场。总的来说，SegmentedFusion能够扫描非刚性变形的人体表面，并通过使用消费级深度相机来估计密集的运动场。实验结果表明，SegmentedFusion对帧间快速运动和拓扑变化具有较强的鲁棒性。由于我们的方法不需要事先假设，SegmentedFusion可以应用于广泛的人体运动。
This paper presents SegmentedFusion, a method possessing the capability of reconstructing non-rigid 3D models of a human body by using a single depth camera with skeleton information. Our method estimates a dense volumetric 6D motion field that warps the integrated model into the live frame by segmenting a human body into different parts and building a canonical space for each part. The key feature of this work is that a deformed and connected canonical volume for each part is created, and it is used to integrate data. The dense volumetric warp field of one volume is represented efficiently by blending a few rigid transformations. Overall, SegmentedFusion is able to scan a non-rigidly deformed human surface as well as to estimate the dense motion field by using a consumer-grade depth camera. The experimental results demonstrate that SegmentedFusion is robust against fast inter-frame motion and topological changes. Since our method does not require prior assumption, SegmentedFusion can be applied to a wide range of human motions.