Interpolating oriented disks in 3D space for constructing high fidelity geometric proxies from point clouds
View Patent ↗An “Oriented Disk Interpolator” provides various techniques for interpolating between points in a point cloud using RGB images (or images in other color spaces) to produce a smooth implicit surface representation that can then be digitally sampled for ray-tracing or meshing to create a high fidelity geometric proxy from the point cloud. More specifically, the Oriented Disk Interpolator uses image color-based consistency to build an implicit surface from oriented points and images of the scene by interpolating disks in 3D space relative to a point cloud of a scene or objects within the scene. The resulting implicit surface is then available for a number of uses, including, but not limited to, constructing a high fidelity geometric proxy.
1. A computer-implemented process for constructing implicit surfaces from point clouds, comprising using a computing device to perform process actions for:
receiving an oriented point cloud, each point in the cloud having a normal direction;
for each point in the cloud, identifying a set of closest neighboring points within a radius around each point;
defining a set of oriented disks, such that for each point in the cloud, a corresponding one of the oriented disks is delimited by the position, normal and radius of the corresponding point;
for each node in a volumetric grid, identifying a corresponding set of neighboring oriented disks as any oriented disk that is closer to the node than the radius of that oriented disk;
for each node having a set of neighboring oriented disks, computing a signed distance as a weighted average of a signed distance to each neighboring oriented disk; and
delimiting an implicit surface corresponding to the oriented point cloud by using the signed distances of each node to construct a signed distance function on the volumetric grid.
2. The computer-implemented process of claim 1 wherein:
a number, n, of closest neighboring points for each point in the oriented point cloud is an adjustable parameter; and
wherein the radius around each point, and thus the radius of each corresponding oriented disk, varies to encompass n neighboring points.
3. The computer-implemented process of claim 1 wherein the radius around each point is computed as a weighted average of the distances to the set of neighboring points.
4. The computer-implemented process of claim 1 further comprising receiving a plurality of color images representing 3D image data of a scene and wherein the oriented point cloud is derived based on the 3D image data.
5. The computer-implemented process of claim 4 further comprising determining oriented disk colors by projecting each oriented disk into each of the color images in which the oriented disk is visible relative to a geometry of corresponding sensor calibration parameters.
6. The computer-implemented process of claim 5 wherein a color of each grid node is determined by projecting each grid node onto each neighboring oriented disk, and computing a bilateral function of the differences of the oriented disk colors and a distance to the oriented disk from the corresponding node.
7. The computer-implemented process of claim 1 further comprising ray-tracing the implicit surface to create a 3D surface visualization of the implicit surface.
8. The computer-implemented process of claim 1 further comprising meshing the implicit surface to create a 3D geometric proxy.
9. The computer-implemented process of claim 1 wherein a density of the nodes in the volumetric grid is an adjustable parameter.
10. A computer-readable memory device having computer executable instructions stored therein for generating implicit surfaces from point clouds, said instructions causing a computing device to execute a method comprising:
constructing a point cloud from 3D image data of a scene and determining a normal for each point to create an oriented point cloud;
for each point in the cloud, identifying a set of the closest n neighboring points around each point and determining a radius around each point as a function of the number and distances of those neighboring points;
defining a set of oriented disks, such that for each point in the cloud, a corresponding one of the oriented disks is delimited by the position, normal and radius of the corresponding point;
for each node in a volumetric grid, identifying a corresponding set of neighboring oriented disks as any oriented disk that is closer to the node than the radius of that oriented disk;
for each node having a set of neighboring oriented disks, computing a signed distance as a function of the distances from the node to each neighboring oriented disk; and
delimiting an implicit surface corresponding to the oriented point cloud by using the signed distances of each node to construct a signed distance function on the volumetric grid.
11. The computer-readable memory device of claim 10 wherein the number, n, of the closest neighboring points is an adjustable parameter.
12. The computer-readable memory device of claim 10 wherein the radius around each point is computed as a weighted average of the distances to the set of neighboring points.
13. The computer-readable memory device of claim 10 further comprising determining oriented disk colors from the 3D image data.
14. The computer-readable memory device of claim 13 wherein a color of each grid node is determined based on the colors of each neighboring oriented disk.
15. The computer-readable memory device of claim 10 further comprising ray-tracing the implicit surface to create a 3D surface visualization of the 3D image data.
16. The computer-readable memory device of claim 10 further comprising meshing the implicit surface to create a 3D geometric proxy of the 3D image data.
17. A computer-implemented process for creating an implicit surface representation of a 3D scene, comprising using a computing device to perform process actions for:
constructing a point cloud from 3D image data of a scene and determining a normal for each point to create an oriented point cloud;
for each point in the cloud, identifying a set of the closest n neighboring points around each point and determining a radius around each point as a function of the number and distances of those neighboring points;
defining a set of oriented disks, such that for each point in the cloud, a corresponding one of the oriented disks is delimited by the position, normal and radius of the corresponding point;
determining oriented disk colors from the 3D image data;
for each node in a volumetric grid, identifying a corresponding set of neighboring oriented disks as any oriented disk that is closer to the node than the radius of that oriented disk;
for each node having a set of neighboring oriented disks, computing a signed distance as a function of the distances from the node to each neighboring oriented disk;
determining a color of each grid node based on the colors of each neighboring oriented disk; and
delimiting an implicit surface corresponding to the oriented point cloud by using the signed distances and colors of each node to construct a signed distance function on the volumetric grid.
18. The computer-implemented process of claim 17 wherein the number, n, of the closest neighboring points is an adjustable parameter.
19. The computer-implemented process of claim 17 wherein the radius around each point is computed as a weighted average of the distances to the set of neighboring points.
20. The computer-implemented process of claim 17 further comprising using the signed distance function to construct a 3D geometric proxy of the 3D image data.