CN115471631A - Three-dimensional point cloud quality judgment method based on real-time grid - Google Patents

Three-dimensional point cloud quality judgment method based on real-time grid Download PDF

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CN115471631A
CN115471631A CN202211161678.9A CN202211161678A CN115471631A CN 115471631 A CN115471631 A CN 115471631A CN 202211161678 A CN202211161678 A CN 202211161678A CN 115471631 A CN115471631 A CN 115471631A
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point cloud
voxels
real
triangular
judging
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孙军
张佰春
吕广志
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Fussen Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00—Manipulating 3D models or images for computer graphics
    • G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/004—Annotating, labelling

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Abstract

The invention relates to the technical field of three-dimensional point cloud quality judgment, and discloses a method for judging the three-dimensional point cloud quality based on a real-time grid, which comprises the following steps: s1, the premise is that the implicit function value based on volume is calculated; s2, traversing all the voxels in the scanning space, and extracting the voxels _ select which can generate a triangular surface; s3, judging that each screened voxel has a plurality of triangular patches, wherein the judging method is implemented by an algorithm MarchingCubes, and searching a lookup table according to eight vertex TSDF values of the voxel; and S4, traversing all the voxels _ select, and generating all the triangular surfaces by adopting a MarchingCubes method. The method for judging the quality of the three-dimensional point cloud based on the real-time grid can be used for judging the quality of the three-dimensional point cloud.

Description

Three-dimensional point cloud quality judgment method based on real-time grid
Technical Field
The invention relates to the technical field of three-dimensional point cloud quality judgment, in particular to a method for judging the three-dimensional point cloud quality based on real-time grids.
Background
In the field of three-dimensional scanning devices, the workflow of a scanning device is as follows: and reconstructing a 3D point cloud by acquiring 2D image information, splicing the 3D point cloud according to the characteristics of the point cloud to form a complete point cloud under a unified coordinate system, and finally generating a 3D grid by the 3D point cloud to finish the digitization of the real object. In three-dimensional real-time scanning application, WYSIWYG real-time rendering is an important link.
In real-time scanning, a user interacts with two modes, namely point cloud rendering and grid rendering, point cloud rendering is faster than grid rendering, and the requirement of real-time rendering can be met, but in many scenes, a 3D grid is real-time rendering and final output in the field of three-dimensional scanning equipment, and the main reasons are as follows:
(1) 3D mesh is the basis for 3D printing
(2) The 3D grid can effectively reflect the characteristics of the real object through rendering
(3) The 3D mesh has geometrical topological characteristics and can effectively express connectivity.
(4) The 3D grid can effectively carry out texture mapping and truly reflect the surface of an object
Real-time rendering of the 3D mesh can improve scanning quality and enhance user experience.
The 3D grid is rendered in real time in the three-dimensional scanning, the characteristics of scanned data are presented in real time, and the scanning navigation can be effectively improved; the geometric topological characteristic of the method can help the algorithm to timely and effectively remove noise points and avoid the accumulation of noise point data.
Therefore, real-time grid scanning is realized, the scanning accuracy can be improved, the user experience can be greatly enhanced, and the method is a necessary function for many three-dimensional scanning equipment products.
In the actual scanning process, due to the fact that noise is generated due to light, water bubbles, camera calibration and misoperation, the quality (precision) of a partial three-dimensional reconstructed point cloud is poor, and the accuracy of the whole scanning is affected when the quality is serious. However, the judgment of the point cloud quality generally needs to be based on the neighborhood relationship of the point, and the judgment difficulty is large.
The three-dimensional real-time grid is generated by three-dimensional point cloud, the generation process of the three-dimensional real-time grid relates to the neighborhood relation of the point cloud, and the quality of the point cloud can be judged by identifying the quality of the grid in the generation process of the grid and then mapping the grid to the point cloud at the corresponding space position. This is typically solved by rescanning, and more serious cases by cropping and rescanning the scanned portion of data.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a method for judging the quality of three-dimensional point cloud based on real-time grids, which can remove the bad point cloud in time, avoid error accumulation, improve the overall scanning precision and solve the problem that the point cloud with poor local quality generates a relatively smooth grid and gives wrong navigation effect due to the relationship of the neighborhood points in the point cloud adopted by the grid generation and the neighborhood in the prior art.
(II) technical scheme
The invention provides the following technical scheme: a three-dimensional point cloud quality judgment method based on real-time grids comprises the following steps:
s1, calculating all voxels of a space based on the implicit function value of the volume;
s2, traversing and scanning all the voxels in the space, and extracting voxels _ select which can generate a triangular surface in the voxels;
s3, judging that each extracted voxels _ select has a plurality of triangular patches, wherein the judgment method is an algorithm MarchingCubes, and the algorithm MarchingCubes comprises the step of searching and searching the number of the triangular patches of each voxels _ select according to eight vertex TSDF values of voxle;
s4, traversing all the voxels _ select, and generating triangular surfaces of all the voxels _ select by adopting a MarchingCubes method;
s5, traversing all the triangular patches;
s6, rendering and marking the triangular surface patch by using the UI, and displaying the triangular surface with the rendered and marked triangular surface in a striking manner;
s7, performing repeated scanning according to the real-time grid rendering prompt until the triangular surface prompt disappears;
and S8, if repeated scanning is carried out, the triangular surface prompt does not disappear, and the user is prompted to scan the area again after cutting or the scanning environment is improved after cutting.
The method for judging the quality of the three-dimensional point cloud based on the real-time grid can be used for judging the quality of the three-dimensional point cloud, can remove bad point cloud in time, avoids error accumulation, improves the overall scanning precision, and is used for solving the problems that point cloud with poor local quality generates relatively smooth grids due to the relationship of neighborhood points and gives wrong navigation effect in the prior art due to the point cloud adopted by the generation of the grid and the relationship of the neighborhood points.
In a possible embodiment, in S1, the specific steps are as follows:
s1.1, a volume method is to divide a scanning space into tiny cubes called volumes; one scanning space consists of a plurality of voxels;
s1.2, each voxel is provided with eight vertexes, and TSDF values (scalar values) of the eight vertexes of the voxels in the neighborhood of the point cloud are calculated according to the coordinates and the normal direction of the point cloud;
s1.3, the triangle surface of the real-time grid generates all the voxels, and the vertexes of the triangle surface are on 12 edges of the voxels.
In one possible embodiment, the step of computing the voxel of the point cloud neighborhood in S1.2 is as follows:
s1.21, taking the coordinate q (x 1, y1, z 1) of each vertex of the voxel; the coordinate of the point cloud p is p (x 2, y2, z 2), and the normal of p is pn (xn, yn, zn);
s1.22, calculate sdf = (p-q) × q = xn (x 1-x 2) + yn (y 1-y 2) + zn (z 1-z 2);
s1.23, obtaining the TSDF after intercepting sdf, wherein the intercepting rule is that fmin < = sdf and sdf < = fmax, and the fmin and the fmax are set according to the actual situation.
In one possible implementation, the marching cubes algorithm in S3 is used to determine whether there are triangle patches based on the signs of the eight vertices of the voxel.
In a possible implementation, in S3, the specific operation steps are as follows:
s3.1, traversing each triangular surface, and calculating the gradient (the difference of tsdf between two vertexes p1 and p2 of the edge e/the side length of e) of the edge e (p 1 and p 2) where each vertex of the triangular surface is located;
and (3.2) if the gradient of the S3.2 and the e is less than the set threshold, marking the peak.
In one possible embodiment, a triangle patch is marked if a vertex of the triangle is marked in S5.
Compared with the prior art, the invention provides a method for judging the quality of three-dimensional point cloud based on real-time grids, which has the following beneficial effects:
according to the method, the quality of the local grid is judged on the basis of the real-time grid, a prompt is given on a grid rendering interface (for example, a triangular surface with poor quality is displayed in a warning color), and a user can perform repeated scanning according to the prompt until the prompt grid disappears. The method removes the bad point cloud to a certain extent in time, avoids error accumulation and improves the overall scanning precision; the smoothness of scanning is greatly improved, the judgment time of a user is shortened, and the user experience is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
Fig. 1 is a flow chart of point cloud quality detection based on three-dimensional point cloud quality determination of real-time grids.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
As shown in fig. 1, the present invention provides a method for determining quality of a three-dimensional point cloud based on a real-time grid, comprising the following steps:
s1, calculating all voxels of a space based on the implicit function value of the volume;
s1.1, a volume method is to divide a scanning space into tiny cubes called volumes; a scan space consists of many voxels.
S1.2, each voxel is provided with eight vertexes, and the TSDF values (scalar values) of the eight vertexes of the voxels in the neighborhood of the point cloud are calculated according to the coordinates and the normal direction of the point cloud.
The voxel steps of calculating the point cloud neighborhood are as follows:
s1.21, taking the coordinate q (x 1, y1, z 1) of each vertex of the voxel; the coordinate of the point cloud p is p (x 2, y2, z 2), and the normal of p is pn (xn, yn, zn);
s1.22, calculate sdf = (p-q) × q = xn (x 1-x 2) + yn (y 1-y 2) + zn (z 1-z 2);
s1.23, obtaining the TSDF after intercepting sdf, wherein the intercepting rule is that fmin < = sdf and sdf < = fmax, and the fmin and the fmax are set according to the actual situation.
S1.3, the triangle surfaces of the real-time grid are generated by all the voxels, some voxels have no triangle surface, some voxels may be generated by a plurality of triangle surfaces, and the vertexes of the triangle surfaces are on 12 sides of the voxels.
S2, traversing and scanning all the voxels in the space, and extracting voxels _ select which can generate a triangular surface in the voxels;
s3, judging that each extracted voxel _ select has a plurality of triangular patches, wherein the judging method is an algorithm MarchingCubes, and the algorithm MarchingCubes comprises searching and searching the number of the triangular patches of each voxel _ select according to eight vertex TSDF values of the voxl;
s3.1, traversing each triangular surface, and calculating the gradient (the difference of tsdf between two vertexes p1 and p2 of the edge e/the side length of e) of the edge e (p 1 and p 2) where each vertex of the triangular surface is located;
and (3.2) if the gradient of the S3.2 and the e is less than the set threshold, marking the peak.
S4, traversing all the voxels _ select, and generating triangular surfaces of all the voxels _ select by adopting a MarchingCubes method;
s5, traversing all the triangular patches;
if a triangle has a vertex marked, the triangle patch is marked.
S6, rendering and marking the triangular surface patch by using the UI, and displaying the triangular surface with the rendered and marked triangular surface in a striking manner;
s7, performing repeated scanning according to the real-time grid rendering prompt until the triangular surface prompt disappears;
and S8, if repeated scanning is carried out, the triangular surface prompt does not disappear, and the user is prompted to repeatedly scan the area after cutting, or the scanning environment is improved after cutting.
The method for judging the quality of the three-dimensional point cloud based on the real-time grid can be used for judging the quality of the three-dimensional point cloud, and the method for judging the quality of the three-dimensional point cloud has the advantages of timely clearing bad point cloud, avoiding error accumulation, improving the overall scanning precision and solving the problems that in the prior art, due to the point cloud adopted for generating the grid and the neighborhood relationship, relatively smooth grid can be generated due to the neighborhood relationship of the point cloud with poor local quality, and wrong navigation effect is given.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in the embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Claims (6)

1. A three-dimensional point cloud quality judgment method based on real-time grids comprises the following steps:
s1, calculating all voxels of a space based on the implicit function value of the volume;
s2, traversing and scanning all the voxels in the space, and extracting voxels _ select which can generate a triangular surface in the voxels;
s3, judging that each extracted voxels _ select has a plurality of triangular patches, wherein the judgment method is an algorithm MarchingCubes, and the algorithm MarchingCubes comprises the step of searching and searching the number of the triangular patches of each voxels _ select according to eight vertex TSDF values of voxle;
s4, traversing all the voxels _ select, and generating triangular surfaces of all the voxels _ select by adopting a MarchingCubes method;
s5, traversing all the triangular patches;
s6, rendering and marking the triangular surface patch by using the UI, and displaying the triangular surface with the rendered and marked triangular surface in a striking manner;
s7, performing repeated scanning according to the real-time grid rendering prompt until the triangular surface prompt disappears;
and S8, if repeated scanning is carried out, the triangular surface prompt does not disappear, and the user is prompted to scan the area again after cutting or the scanning environment is improved after cutting.
2. The method for judging the quality of the three-dimensional point cloud based on the real-time grid according to claim 1, wherein in S1, the specific steps are as follows:
s1.1, dividing a scanning space into small cubes called voxel; one scanning space consists of a plurality of voxels;
s1.2, each voxel is provided with eight vertexes, and TSDF values of the eight vertexes of the voxels in the point cloud neighborhood are calculated according to the coordinates and the normal direction of the point cloud;
s1.3, the triangle surface of the real-time grid generates all the voxels, and the vertexes of the triangle surface are on 12 edges of the voxels.
3. The method for judging the quality of the three-dimensional point cloud based on the real-time grid as claimed in claim 2, wherein the step of calculating the voxel of the point cloud neighborhood in S1.2 is as follows:
s1.21, taking the coordinate q (x 1, y1, z 1) of each vertex of the voxel; the coordinate of the point cloud p is p (x 2, y2, z 2), and the normal of p is pn (xn, yn, zn);
s1.22, calculating sdf = (p-q) × q = xn (x 1-x 2) + yn (y 1-y 2) + zn (z 1-z 2);
s1.23, obtaining the TSDF after the sdf is truncated, wherein the truncation rule is that fmin < = sdf and sdf < = fmax, and the fmin and the fmax are set according to the actual situation.
4. The method of claim 1, wherein a marching cubes algorithm is used in S3 to determine whether there is a triangle patch according to the signs of eight vertices of a voxel.
5. The method for judging the quality of the three-dimensional point cloud based on the real-time grid according to claim 4, wherein in S3, the specific operation steps are as follows:
s3.1, traversing each triangular surface, and calculating the gradient of an edge e (p 1, p 2) where each vertex of the triangular surface is located;
s3.2, when the gradient of e is smaller than a set threshold, marking the vertex.
6. The method of claim 1, wherein if a vertex of a triangle is marked in step S5, the triangle patch is marked.
CN202211161678.9A 2022-09-22 2022-09-22 Three-dimensional point cloud quality judgment method based on real-time grid Pending CN115471631A (en)

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