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DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Automatic Posing of a Meshed Human Model Using Point Clouds Lei Wang Joint work with Tamal K. Dey, Huamin.

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Presentation on theme: "DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Automatic Posing of a Meshed Human Model Using Point Clouds Lei Wang Joint work with Tamal K. Dey, Huamin."— Presentation transcript:

1 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Automatic Posing of a Meshed Human Model Using Point Clouds Lei Wang Joint work with Tamal K. Dey, Huamin Wang and Bo Fu

2 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Problem Statement Low-end scanning devices are becoming popular. But quality of their output… Reconstruct from problematic human scans by deforming a prior high quality template mesh

3 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Related Work Model-based Registration Parametric human body models Registration without a Model Manual intervention Non-rigid registration by nonlinear optimization Isometric deformations: keep geodesic distance unchanged

4 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Our Method: Outline computing correspondences posingoutput

5 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Computing Correspondences

6 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Computing Correspondences The Global Point Signature (GPS) framework by [Rustamov 2007]: Apply Gaussian-weighted Graph Laplacian on the adjacency graph of input point cloud Graph Laplacian GPS in dimension 1, 2 and 3

7 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Computing Correspondences GPS is invariant under isometric deformation We choose only the first three eigenfunctions

8 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Computing Correspondences Correspondences are expanded from 5 extremums of aligned GPS embeddings

9 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Posing Template Mesh Formulated as an energy minimization problem: is the internal energy of template mesh ○ measures difference between template and the point cloud Solved by Invertible FEM [Irving et al. 2004]

10 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING It has two stages Point cloud alignment: deformed by input point cloud Posing Template Mesh Initial alignment: deformed by correspondence

11 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Posing Template Mesh For efficiency, posing is performed on a simplified template mesh, called control mesh Deformed template is recovered by Mean Value Coordinates [Ju et al. 2005], i.e., weighted sum of the control mesh

12 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Results

13 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Results

14 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Results

15 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Results (a) input scan (b) our method (c) SCAPE

16 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Results can be used to control the body size

17 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Supplementary Video

18 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Discussion An automatic approach to align a detailed template mesh with human point clouds in different poses Robust to noise and occlusions Sensitive to topological change Can not handle details like fingers Does not run in real-time

19 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Q & A Thank you!

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