3D Shape Modeling by Deformable Models. Ye Duan
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1 3D Shape Modeling by Deformable Models Ye Duan
2 Previous Work Shape Reconstruction from 3D data. Volumetric image datasets. Unorganized point clouds. Interactive Mesh Editing.
3 Vertebral Dataset
4 Vertebral Model
5 Model Refinement
6 Two Tori Tori
7 Two Tori Tori
8 Sharp Features
9 Sharp Features
10 Sharp Features
11 Sharp Features
12 Previous Work Shape Reconstruction from 3D data. Volumetric image datasets. Unorganized point clouds. Interactive Mesh Editing.
13 Interactive Mesh Editing CSG Operations. Mesh Warping. Sketch Based Editing. i
14 CSG Operations
15 CSG Operations
16 CSG Operations
17 CSG Operations
18 CSG Operations
19 Mesh Warping
20 Free hand Sketching
21 Free hand Sketching
22 Mannequin
23 Mannequin
24 Bunny
25 Bunny
26 Bunny Adaptively Refined Shape
27 Eight Tori
28 Eight Tori
29 Current Work Shape reconstruction from segmented volumetric data Shape reconstruction from MRI volumetric data Shape reconstruction from single view 2D images Shape reconstruction from multiple view 2D images
30 A Region Growing Based Iso Surface Extraction Algorithm
31 Result
32 Result
33 Result
34 Result
35 Result
36 Result
37 Result
38 Result
39 Result Comparison Our algorithm Marching Cubes algorithm
40 Results Comparison Marching Cubes algorithm Our algorithm
41 Results Comparison Our algorithm Marching Cubes algorithm
42 Current Work Shape reconstruction from segmented volumetric data Shape reconstruction from MRI volumetric data Shape reconstruction from single view 2D images Shape reconstruction from multiple view 2D images
43 A Semi-automatic 3D Brain Structure Segmentation Algorithm from MRI Integrates region-based method with boundary based method. Combines PDE-based level-set surface evolution with affinitybased clustering method. Clustering provides a good initializationiti and avoids locall minima. More efficient computation, closer to equilibrium, faster convergence.
44 Algorithm Pipeline
45
46 Deformation Initialized with seed cluster. Deform the seed by implicit PDE-based level-set method. Initialize the voxel grid by labeling each voxel as inside or outside of the seed. Build signed distance field from the binary voxel grid by fast sweeping method.
47 Deformation
48 3D Image Segmentation Results
49 3D Shape Analysis Top: right ventricle Bottom: left ventricle p=0 p>=0.05 left: average ventricle shapes of two groups overlaid; middle: significance map of raw p-values; right: significance map of p-values after FDR correction
50 Current Work Shape reconstruction from segmented volumetric data Shape reconstruction from MRI volumetric data Shape reconstruction from single view 2D images Shape reconstruction from multiple view 2D images
51 Color Photometric Stereo for Albedo and dshape Reconstruction ti
52 Experiment: Rebel400 & Penguin Captured images: Incandescent light of ~3000 K No saturations l 1 =(10.7,6.2,30) l 2 = (-10.7,6.2,30) l 3 = (0,-12.4,30) (cm) Albedos c r c g c b
53 Experiment: Penguin Comparison of reconstructed shapes Roland PIX-4 (measured) Rebel400 Coolpix950
54 Experiment: CP950 & Penguin Reconstructed object from the shape and albedo
55 Experiment: Rebel400 & Horse Captured images: Incandescent light of ~3000 K No saturations l 1 =(11,6.1,30) l 2 = (-11,5.8,30) l 3 = (0,-13.7,30) (cm) Albedos c r c g c b
56 Experiment: Rebel400 & Horse (w r,w g,w b )=(1,0,0) (0,1,0) (0,0,1) (w r,w g,w b )=(1, 1, 1) (E{i r }, E{i g }, E{i b }) =(1.26, 1, 0.77) albedo
57 Experiment: Rebel400 & Horse Reconstructed object from the shape and albedo
58 Experiment: Rebel400 & Horse
59 Outline Shape reconstruction from segmented volumetric data Shape reconstruction from MRI volumetric data Shape reconstruction from single view 2D images Shape reconstruction from multiple view 2D images
60 Multiple View 2D Images
61 Buddha
62 Progressive Reconstruction
63 Mug
64 Middlebury Benchmark datasets
65 Reconstruction Results on the 4 Benchmark datasets
66 Running time and reconstruction accuracy Dataset Running time (mins: secs) # of input images accuracy Temple Ring 33: % Temple Sparse Ring 29: % Dino Ring 36: % Dino Sparse Ring 32: %
67 3D Building Reconstruction Using Multi-view Aerial Images
68 Feature extraction and matching
69 Camera Pose Rectification
70 Preliminary Results
71 Building Reconstruction Using Multi-view Aerial Images
72 LIDAR point data processing Classification Segmentation Compression Surface reconstruction
73 LIDAR point data processing Ground based LIDAR Airborne LIDAR
74 Ground basedlidar Scan
75 Hierarchical LIDAR Data Segmentation (a) (b) (c) (a) Original LIDAR data; (b) Floor (blue color), ceiling (green color), and vertical walls (red, cyan and magenta colors) identified; (c) Individual objects extracted (shown in different colors).
76 3D Interior Building Visualization Three different views of the same scene
77 Virtual Navigation
78 Floor Plan Generation
79 Airborne LIDAR point data
80
81 Classification Results
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