DEVICE AND METHOD FOR REMOVING NOISE POINTS IN POINT CLOUDS

• US 20150109290A1
• Filed: 10/21/2014
• Published: 04/23/2015
• Est. Priority Date: 10/22/2013
• Status: Abandoned Application

• Current Assignee: Futaihua Industry (Shenzhen) Co., Ltd. (Hon Hai Precision Industry Co., Ltd.), Hon Hai Precision Industry Co., Ltd.
• Original Assignee: Futaihua Industry (Shenzhen) Co., Ltd. (Hon Hai Precision Industry Co., Ltd.), Hon Hai Precision Industry Co., Ltd.
• Inventors: CHANG, CHIH-KUANG, WU, XIN-YUAN, XIE, PENG
• Application Number:
  US14/519,308
• Publication Number:
  US 20150109290A1
• Time in Patent Office: Days
• US Class Current: 345/420
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 17/20 Finite element generation, e.g. wire-frame surface description, tesselation
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2210/56 Particle system, point based geometry or rendering
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

In a noise points removing method, a point cloud of an object and predetermined parameters relating to the point cloud are received. The point cloud is triangulated to construct a triangular mesh surface, then, the point cloud is divided into a plurality of subsets according to the triangular mesh surface and the predetermined parameters. Each of the subsets of selected one by one, point distances between each point in the selected subsets and all points in adjacent subsets of the selected subsets and subset distances between the selected subset and each of the adjacent subsets according to the point distances are computed. Noise points can be determined according to a number of points in the each of the subsets, the predetermined parameters, and the subset distances, and then be removed.

Claims

1. A method of removing noise points, the method executable by at least one processor of a computing device, and comprising:

receiving a point cloud of an object and predetermined parameters relating to the point cloud;

triangulating points in the point cloud and constructing a triangular mesh surface;

dividing the point cloud into a plurality of subsets according to the triangular mesh surface and the predetermined parameters;

selecting one of the plurality of subsets, computing point distances between each point in the selected subset and all points in adjacent subsets of the selected subset, and computing subset distances between the selected subset and each of the adjacent subsets according to the point distances;

determining noise points in the plurality of subsets according to a number of points in the each of the plurality of subsets, the predetermined parameters, and the subset distances, and generating a filter point cloud by removing the noise points from the point cloud; and

rendering a visual representation of the filtered point cloud on a display device.

2. The method according to claim 1, wherein the adjacent subsets are subsets that comprise one or more points which are in the same triangles with points in the selected subset.

3. The method according to claim 1, wherein the subset distance is the minimum point distance between the selected subset and each of the adjacent subsets.

4. The method according to claim 1, wherein the predetermined parameters comprises a predetermined point distance and a predetermined point number.

5. The method according to claim 4, wherein the point cloud is divided into a plurality of subsets by:

selecting a point in the point cloud, and putting the selected point into a subset;

computing a distance between the selected point and adjacent points of the selected point in the point cloud, the adjacent points comprising points that are in a same triangle with the selected point;

determining one or more of the adjacent points whose distance to the selected point is less than the predetermine point distance, filtering the adjacent points, and putting the filtered adjacent points into the subset; and

returning to selecting another point in the point cloud until all points in the subset have been selected.

6. The method according to claim 4, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number.

7. The method according to claim 4, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number, and the subset distance between the subset and at least one of the adjacent subsets is greater than a predetermined subset distance.

8. A computing device, comprising:

a display device;

a control device; and

a storage device storing one or more programs which, when executed by the control device, causes the control device to;

receive a point cloud of an object and predetermined parameters relating to the point cloud;

triangulate points in the point cloud and constructing a triangular mesh surface;

divide the point cloud into a plurality of subsets according to the triangular mesh surface and the predetermined parameters;

select one of the plurality of subsets, compute point distances between each point in the selected subset and all points in adjacent subsets of the selected subset, and compute subset distances between the selected subset and each of the adjacent subsets according to the point distances;

determine noise points in the plurality of subsets according to a number of points in the each of the plurality of subsets, the predetermined parameters, and the subset distances, and generate a filter point cloud by removing the noise points from the point cloud; and

rendering a visual representation of the filtered point cloud on the display device.

9. The computing device according to claim 8, wherein the adjacent subsets are subsets that comprise one or more points which are in the same triangles with points in the selected subset.

10. The computing device according to claim 8, wherein the subset distance is the minimum point distance between the selected subset and each of the adjacent subsets.

11. The computing device according to claim 8, wherein the predetermined parameters comprises a predetermined point distance and a predetermined point number.

12. The computing device according to claim 11, the one or more programs when executed by the control device, further causes the control device to:

select a point in the point cloud, and putting the selected point into a subset;

compute a distance between the selected point and adjacent points of the selected point in the point cloud, the adjacent points comprising points that are in a same triangle with the selected point;

determine one or more of the adjacent points whose distance to the selected point is less than the predetermine point distance, filter the adjacent points, and put the filtered adjacent points into the subset; and

return to selecting another point in the point cloud until all points in the subset have been selected.

13. The computing device according to claim 11, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number.

14. The computing device according to claim 11, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number, and the subset distance between the subset and at least one of the adjacent subsets is greater than a predetermined subset distance.

15. A non-transitory storage medium having stored thereon instructions that, when executed by a processor of a computing device, causes the processor to perform a method of removing noise points, wherein the method comprises:

receiving a point cloud of an object and predetermined parameters relating to the point cloud;

triangulating points in the point cloud and constructing a triangular mesh surface;

dividing the point cloud into a plurality of subsets according to the triangular mesh surface and the predetermined parameters;

selecting one of the plurality of subsets, computing point distances between each point in the selected subset and all points in adjacent subsets of the selected subset, and computing subset distances between the selected subset and each of the adjacent subsets according to the point distances;

determining noise points in the plurality of subsets according to a number of points in the each of the plurality of subsets, the predetermined parameters, and the subset distances, and generating a filter point cloud by removing the noise points from the point cloud; and

rendering a visual representation of the filtered point cloud on a display device.

16. The non-transitory storage medium according to claim 15, wherein the predetermined parameters comprises a predetermined point distance and a predetermined point number.

17. The non-transitory storage medium according to claim 15, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number.

18. The non-transitory storage medium according to claim 17, wherein the point cloud is divided into a plurality of subsets by:

selecting a point in the point cloud, and putting the selected point into a subset;

computing a distance between the selected point and adjacent points of the selected point in the point cloud, the adjacent points comprising points that are in a same triangle with the selected point;

determining one or more of the adjacent points whose distance to the selected point is less than the predetermine point distance, filtering the adjacent points, and putting the filtered adjacent points into the subset; and

returning to selecting another point in the point cloud until all points in the subset have been selected.

19. The non-transitory storage medium according to claim 17, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number.

20. The method according to claim 17, wherein all points in the subset are considered as the noise points when the number of points in the subset is less than the predetermined point number, and the subset distance between the subset and at least one of the adjacent subsets is greater than a predetermined subset distance.