Name
Abstract | ||
|---|---|---|
We propose a new method for the estimation of a 3D shape of non-convex object from an image sequence taken with the object rotating under a fixed light source. First, all the territory candidate of the object is prepared in voxel space. The empty voxels are selected by using the cross-section estimation using a silhouette that is the conventional method. In this method, we think a ray that connects the point of view and silhouette to be tangent of the object and remove the territory that is outside of the ray. However, this method cannot reconstruct the non-convex object, because change is not shown in the silhouette by the dents. Therefore, we remove the part of the dents by using the cross-section estimation using occlusion and shading. For the cross-section estimation using occlusion, we apply a technique similar to the shape from silhouette. That is to say, we think the ray that connects the point of view and occlusion to be the tangent toward the front object of occlusion and remove the territory surrounded by corresponding two tangents of the two neighboring views. For the cross-section estimation using shading, we decide the most suitable position of the surface point in the searched ray, which connects a point of view and the surface and on which the surface point is searched. To decide a suitable position, we examine a change in brightness of backward rays, which connect a voxel and each point of view. At each voxel on the searched ray, the most suitable position is where the degree of agreement with the bi-directional reflectance model is the highest. For demonstrating the effectiveness of the proposed method, we show reconstruction image of non-convex objects, such as balls, or a doll and chair, which are successfully recovered. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/ICPR.2000.905493 | ICPR |
Keywords | Field | DocType |
shape recovery,neighboring view,conventional method,suitable position,non-convex object,territory candidate,new method,front object,cross-section estimation,surface point,surface reconstruction,brightness,image reconstruction,edge detection,reflectivity,silhouette,image texture,microcomputers,cross section,shading | Voxel,Iterative reconstruction,Computer vision,Pattern recognition,Edge detection,Image texture,Computer science,Silhouette,Regular polygon,Tangent,Artificial intelligence,Brightness | Conference |
ISSN | Citations | PageRank |
1051-4651 | 1 | 0.35 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taichi Sato | 1 | 20 | 3.73 |
| Hideo Saito | 2 | 1147 | 169.63 |
| Shinji Ozawa | 3 | 186 | 37.69 |