CN109509143A - A kind of method of three-dimensional point cloud conversion two dimensional image - Google Patents
A kind of method of three-dimensional point cloud conversion two dimensional image Download PDFInfo
- Publication number
- CN109509143A CN109509143A CN201811281912.5A CN201811281912A CN109509143A CN 109509143 A CN109509143 A CN 109509143A CN 201811281912 A CN201811281912 A CN 201811281912A CN 109509143 A CN109509143 A CN 109509143A
- Authority
- CN
- China
- Prior art keywords
- dimensional
- point cloud
- coordinate
- las
- cylindrical
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000006243 chemical reaction Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000012360 testing method Methods 0.000 claims abstract description 15
- 238000012937 correction Methods 0.000 claims description 3
- 230000003287 optical effect Effects 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 5
- VMXUWOKSQNHOCA-UKTHLTGXSA-N ranitidine Chemical compound [O-][N+](=O)\C=C(/NC)NCCSCC1=CC=C(CN(C)C)O1 VMXUWOKSQNHOCA-UKTHLTGXSA-N 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 244000062793 Sorghum vulgare Species 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 235000019713 millet Nutrition 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/06—Topological mapping of higher dimensional structures onto lower dimensional surfaces
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a kind of methods of three-dimensional point cloud conversion two dimensional image, it include: that object under test three-dimensional point cloud information is obtained by 3 D laser scanning equipment, using three-dimensional scanning device as coordinate center, three Cartesian coordinates are established, and demarcate the cartesian coordinate of every bit in three-dimensional point cloud；Using three-dimensional scanning device as coordinate center, three-dimensional cylindrical coordinate is established, and establish the transformational relation of the cartesian coordinate of every bit and cylindrical coordinates in three-dimensional point cloud, the three-dimensional point cloud in cartesian space coordinate system is corresponded in cylindrical coordinate；By the cylinder unwrapping of three-dimensional cylindrical coordinate, construct two-dimentional cylindrical coordinate system, and establish the transformational relation of the cylindrical coordinates of the cylindrical coordinates of every bit and two-dimentional cylindrical coordinate system in three-dimensional point cloud, three-dimensional point cloud in cylindrical coordinate is corresponded in two-dimentional cylindrical coordinate system, the two-dimensional pixel coordinate of object under test is generated.The present invention can will the obtained three-dimensional point cloud of scanning to be converted to two dimensional image for deliberation, simplify calculating process.
Description
Technical field
The present invention relates to the methods of image conversion art more particularly to a kind of three-dimensional point cloud conversion two dimensional image.
Background technique
3-D scanning technology has been gradually improved at present, applies and obtains significant achievement in various industries, it can obtain atural object table
Face three-dimensional geometry characteristic information detects atural object surface geometry deformation.If converting two dimensional image for a cloud, moreover it is possible to by it and its
The two-dimensional data fusion that his sensor obtains, thus carry out deeper into research.Three-dimensional point cloud is converted into two dimensional image, at present
Main method has upright projection, perspective projection.However, for turn sweep three-dimensional laser scanner acquisition point cloud, this projection side
The huge distortion and error that method can generate, that is, be unable to maximal accuracy for a cloud and project into two dimensional image.
Summary of the invention
A kind of three-dimensional point cloud conversion two dimensional image is provided it is an object of the invention to avoid the deficiencies in the prior art place
Method.
The purpose of the present invention can be realized by using following technical measures, design a kind of three-dimensional point cloud conversion two dimension
The step of method of image, this method includes: to obtain object under test three-dimensional point cloud information by 3 D laser scanning equipment, with three
Scanning device is tieed up as coordinate center, establishes three Cartesian coordinates, and the Descartes for demarcating every bit in three-dimensional point cloud sits
Mark；
Using three-dimensional scanning device as coordinate center, three-dimensional cylindrical coordinate is established, and establish every bit in three-dimensional point cloud
The transformational relation of cartesian coordinate and cylindrical coordinates corresponds to the three-dimensional point cloud in cartesian space coordinate system in cylindrical coordinate；
By the cylinder unwrapping of three-dimensional cylindrical coordinate, two-dimentional cylindrical coordinate system is constructed, and establishes every bit in three-dimensional point cloud
The transformational relation of the cylindrical coordinates of cylindrical coordinates and two-dimentional cylindrical coordinate system, corresponds to two-dimensional columns for the three-dimensional point cloud in cylindrical coordinate
In areal coordinate system, the two-dimensional pixel coordinate of object under test is generated.
Wherein, in the cartesian space coordinate system of foundation, using three-dimensional scanning device as coordinate center, three-dimensional scanning device
Vertical rotating shaft as Z axis；Optical axis along three-dimensional scanning device any level angle is as X-axis；Cylindrical coordinate and Descartes are empty
Between coordinate system origin having the same, cylindrical coordinate is using the Z axis of cartesian space coordinate system as center axis, using r as radius, flute card
The X-axis of your space coordinates is to originate the cylindrical surface of axis.
Wherein, set-point P is object under test surface any point, and cartesian coordinate is (x3d-las, y3d-las, z3d-las), column
Coordinate representation is (r, ξ, z3d-cyl), according to the transfer principle of cartesian coordinate and cylindrical coordinates, the relationship of the two is following formula institute
Show:
Wherein, r is the distance of point P to rotary shaft Z, andξ is the plane of scanning motion where point P
With the plane included angle OXZ, z3d-cylFor the distance of point P to OXY plane.
Wherein, the conversion formula of the point of three Cartesian coordinates midpoint and two-dimentional cylindrical coordinate system are as follows:
Wherein, (x3d-las, y3d-las, z3d-las) indicate three-dimensional point cloud any point cartesian space coordinate；
(x2d-cyl, y2d-cyl) indicate the pixel coordinate of corresponding two-dimentional point cloud chart picture；C indicate camera model master away from；(x0, y0) indicate
The principal point of two-dimentional point cloud chart picture；(Δ x, Δ y) indicate the correction parameter in camera.
Wherein, it further comprises the steps of: and the two-dimensional pixel coordinate of every bit after conversion is further converted into two-dimentional point cloud chart picture
Coordinate.
Wherein, the two-dimensional pixel coordinate of every bit after conversion is converted into two-dimentional point cloud chart as being by following public affairs when coordinate
Formula carries out:
Wherein, x2d-lasIndicate abscissa of the two-dimentional point cloud chart picture in pixel coordinate system；y2d-lasIndicate two-dimentional point cloud chart
As the ordinate in pixel coordinate system；AmIndicate the horizontal resolution in pixel coordinate system；AnIndicate hanging down in pixel coordinate system
Straight resolution ratio.
Wherein, for two-dimentional point cloud chart as midpoint (x2d-las, y2d-las) gray value, calculation formula are as follows:
Color indicates point (x2d-las, y2d-las) gray value, range is at [0-255]；Col indicates (x3d-lasΔy3d-las,
z3d-las) a certain characteristic value；Maxf and minf respectively indicate in three-dimensional point cloud information the maximum value of the characteristic value of corresponding point and
Minimum value.
Wherein, when a pixel corresponds to the point of multiple three-dimensional point clouds, take the maximum point of characteristic value corresponding as pixel
Point；When no point in pixel, the gray value of the pixel is taken as 0.
It is different from the prior art, the present invention provides a kind of method of three-dimensional point cloud conversion two dimensional image, the steps of this method
Suddenly include: by 3 D laser scanning equipment obtain object under test three-dimensional point cloud information, using three-dimensional scanning device as coordinate in
The heart establishes three Cartesian coordinates, and demarcates the cartesian coordinate of every bit in three-dimensional point cloud；Using three-dimensional scanning device as
Three-dimensional cylindrical coordinate is established at coordinate center, and the conversion for establishing the cartesian coordinate of every bit and cylindrical coordinates in three-dimensional point cloud is closed
System, the three-dimensional point cloud in cartesian space coordinate system is corresponded in cylindrical coordinate；By the cylinder unwrapping of three-dimensional cylindrical coordinate, structure
Two-dimentional cylindrical coordinate system is built, and establishes turn of the cylindrical coordinates of the cylindrical coordinates of every bit and two-dimentional cylindrical coordinate system in three-dimensional point cloud
Relationship is changed, the three-dimensional point cloud in cylindrical coordinate is corresponded in two-dimentional cylindrical coordinate system, the two-dimensional pixel for generating object under test is sat
Mark.The present invention utilizes the working principle of panorama camera, and the three dimensional point cloud for turning to sweep is converted to two dimensional image, maximum journey
Degree avoids the error of three-dimensional point cloud and two dimensional image, reduces pattern distortion, simplifies calculating process.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of the method for three-dimensional point cloud conversion two dimensional image provided by the invention；
Fig. 2 is setting cartesian space coordinate system in a kind of method of three-dimensional point cloud conversion two dimensional image provided by the invention
Schematic diagram；
Fig. 3 is the signal of setting cylindrical coordinate in a kind of method of three-dimensional point cloud conversion two dimensional image provided by the invention
Figure；
Fig. 4 is will be in cartesian space coordinate system in a kind of method of three-dimensional point cloud conversion two dimensional image provided by the invention
Three-dimensional point cloud project in the two-dimentional cylinder in cylindrical coordinate the schematic diagram for forming two-dimentional point cloud chart picture；
Fig. 5 is flat from the XY of XYZ cylindrical coordinate in a kind of method of three-dimensional point cloud conversion two dimensional image provided by the invention
Face sectional view；
Fig. 6 is that a kind of three-dimensional point cloud provided by the invention is converted radius in the method for two dimensional image as the cylinder unwrapping of c
The schematic diagram of the two-dimentional cylindrical coordinate system constructed afterwards；
Fig. 7 be in a kind of method of three-dimensional point cloud conversion two dimensional image provided by the invention pixel in cylindrical coordinate system
Pixel grid in position view.
Specific embodiment
Further more detailed description is made to technical solution of the present invention With reference to embodiment.Obviously, it is retouched
The embodiment stated is only a part of the embodiments of the present invention, instead of all the embodiments.Based on the embodiments of the present invention,
Those of ordinary skill in the art's every other embodiment obtained without creative labor, all should belong to
The scope of protection of the invention.
Refering to fig. 1, Fig. 1 is a kind of flow diagram of the method for three-dimensional point cloud conversion two dimensional image provided by the invention.
The step of this method includes:
S110: by 3 D laser scanning equipment obtain object under test three-dimensional point cloud information, using three-dimensional scanning device as
Three Cartesian coordinates are established at coordinate center, and demarcate the cartesian coordinate of every bit in three-dimensional point cloud.
In the present invention, the image of object under test is made of multiple points, therefore by the picture number of object under test
According to being named as point cloud data.Wherein, three dimensional point cloud is three dimensional point cloud, and two-dimensional image data is two-dimentional point cloud data.
3 D laser scanning equipment is that scanning imagery, imager coordinate are three-dimensional cartesian coordinates under cylindrical coordinate with linear array mode, is sat
Mark system is by being determined inside 3 D laser scanning equipment.As shown in Fig. 2, O is the GuangDian Center of scanner, that is, put cloud coordinate system
Origin；Z axis is the vertical rotating shaft of scanner；X-axis is the optical axis along scanner any level angle, for example, first level angle or
Compass built in person's any moment all points to the direction in north；Y-axis just gives X-axis and Z axis, and is formed by according to right-handed coordinate system
Axis；One_frame indicates the plane of scanning motion of the scanner light beam in same angle from the top down, far and near different according to atural object, obtains
The point cloud data of the different cylinders taken.If point P is arbitrary point cloud on the face one_frame, cartesian coordinate is represented by
(x3d-las, y3d-las, z3d-las)。
S120: using three-dimensional scanning device as coordinate center, three-dimensional cylindrical coordinate is established, and establish each in three-dimensional point cloud
The cartesian coordinate of point and the transformational relation of cylindrical coordinates, correspond to cylindrical coordinate for the three-dimensional point cloud in cartesian space coordinate system
In.
Thus Three Dimensional Ground laser scanning system constructs a cylindrical coordinate, as shown in Figure 3 with the scanning of linear array cylinder mode.
The coordinate system and cartesian cartesian coordinate system XYZ origin having the same, using Z axis as center axis, r is radius, and X-axis is starting axis
Cylindrical surface.
If P is a bit on cylindrical surface, cartesian coordinate is (x3d-las, y3d-las, z3d-las), cylindrical coordinates (r, ξ,
z3d-cyl), then according to the transfer principle of cartesian coordinate and cylindrical coordinates, the relationship between them is shown in following formula:
Wherein r be point P to rotary shaft Z distance andξ is one_frame and OXZ plane
Angle, z3d-cylFor the distance of point P to OXY plane.
For 3 D laser scanning equipment with the scanning of linear array cylinder mode, point cloud coordinate system is cartesian cartesian coordinate system, according to
Three-dimensional point cloud in cartesian space coordinate system is projected to column and sat by the image-forming principle of scanner imaging model and panorama camera
In two-dimentional cylinder in mark system, two-dimentional point cloud chart picture is formed.As shown in figure 4, a little projecting to shape on cylindrical surface in three-dimensional point cloud
At a pixel, if point P (r, ξ, z3d-cyl) project on the cylinder of radius c, then generate P3d-cyl(c, ξ, z3d-cyl)。
S130: by the cylinder unwrapping of three-dimensional cylindrical coordinate, two-dimentional cylindrical coordinate system is constructed, and is established each in three-dimensional point cloud
The transformational relation of the cylindrical coordinates of the cylindrical coordinates of point and two-dimentional cylindrical coordinate system, corresponds to two for the three-dimensional point cloud in cylindrical coordinate
It ties up in cylindrical coordinate system, generates the two-dimensional pixel coordinate of object under test.
In cylindrical coordinates, from the X/Y plane sectional view of XYZ cylindrical coordinate it is found that as shown in figure 5, Z value is identical same flat
Millet cake cloud (large circle point), projects on the circle of radius c, is formed pixel (dot), such as one point P of three-dimensional point cloud (r, ξ,
z3d-cyl) corresponding two-dimensional points cloud P3d-cyl(c, ξ, z3d-cyl)。
Three-dimensional point cloud P (x as a result,3d-las, y3d-las, z3d-las) with corresponding cylindrical surface projecting point P3d-cyl(c, ξ, z3d-cyl)
Relationship may be expressed as:
Wherein c be point cloud two dimensional image master away from；ξ is one_frame and the plane included angle OXZ, is represented byz3d-cylFor the distance of point P to OXY plane.
The cylinder unwrapping for being c by radius constructs two-dimentional cylindrical coordinate system O2d-cylX2d-cylY2d-cyl, as shown in Figure 6.
The conversion formula of three-dimensional point cloud and two-dimensional points cloud plane coordinate system is as follows:
Wherein (x3d-las, y3d-las, z3d-las) indicate some cloud coordinates；(x2d-cyl, y2d-cyl) indicate that point cloud coordinate is corresponding
The pixel coordinate of two-dimentional point cloud chart picture；C indicate camera model master away from；(x0, y0) indicate the principal point of two-dimentional point cloud chart picture；(Δ x,
Δ y) indicates the correction parameter in camera.
Coordinate of the pixel in cylindrical coordinate system is substantially position of the point in pixel grid, and value is integer form,
As shown in Figure 7.And the calculated two-dimensional points cloud coordinate (x of above-mentioned formula institute2d-cyl, y2d-cyl) value be real number form, need to pass through
Following form conversion generates final two-dimentional point cloud chart picture, as shown by the following formula.
Wherein, x2d-lasIndicate abscissa of the two-dimentional point cloud chart picture in pixel coordinate system；y2d-lasIndicate two-dimentional point cloud chart
As the ordinate in pixel coordinate system；AmIndicate the horizontal resolution in pixel coordinate system；AnIndicate hanging down in pixel coordinate system
Straight resolution ratio.
For two-dimentional point cloud chart as midpoint (x2d-las, y2d-las) pixel value by its corresponding cloud (x3d-las, y3d-las,
z3d-las) characteristic value determine that value can be the letter such as angle (normal vector and plane), curvature, echo strength and color of this point
Breath, formula are as follows:
Color indicates point (x2d-las, y2d-las) gray value, range is in [0-255；Col indicates (x3d-las, y3d-las,
z3d-las) a certain characteristic value；Maxf and minf respectively indicates the maximum value and minimum value of this feature value in point cloud data.When one
When corresponding to multiple clouds in a pixel, take maximum cloud of characteristic value as the pixel corresponding points cloud；When a point cloud no in pixel
When, the gray value of the pixel is taken as 0.
According to the above point cloud camera model, by multiple coordinate transform, three-dimensional point cloud is generated into two-dimentional point cloud chart picture.
It is different from the prior art, the present invention provides a kind of method of three-dimensional point cloud conversion two dimensional image, the steps of this method
Suddenly include: by 3 D laser scanning equipment obtain object under test three-dimensional point cloud information, using three-dimensional scanning device as coordinate in
The heart establishes three Cartesian coordinates, and demarcates the cartesian coordinate of every bit in three-dimensional point cloud；Using three-dimensional scanning device as
Three-dimensional cylindrical coordinate is established at coordinate center, and the conversion for establishing the cartesian coordinate of every bit and cylindrical coordinates in three-dimensional point cloud is closed
System, the three-dimensional point cloud in cartesian space coordinate system is corresponded in cylindrical coordinate；By the cylinder unwrapping of three-dimensional cylindrical coordinate, structure
Two-dimentional cylindrical coordinate system is built, and establishes turn of the cylindrical coordinates of the cylindrical coordinates of every bit and two-dimentional cylindrical coordinate system in three-dimensional point cloud
Relationship is changed, the three-dimensional point cloud in cylindrical coordinate is corresponded in two-dimentional cylindrical coordinate system, the two-dimensional pixel for generating object under test is sat
Mark.The present invention can will the obtained three dimensional point cloud of scanning to be converted to two-dimensional image data for deliberation, simplify and calculated
Journey.
The above is only embodiments of the present invention, are not intended to limit the scope of the invention, all to utilize the present invention
Equivalent structure or equivalent flow shift made by specification and accompanying drawing content is applied directly or indirectly in other relevant technologies
Field is included within the scope of the present invention.
Claims (8)
1. a kind of method of three-dimensional point cloud conversion two dimensional image characterized by comprising
Object under test three-dimensional point cloud information is obtained by 3 D laser scanning equipment, using three-dimensional scanning device as coordinate center,
Three Cartesian coordinates are established, and demarcate the cartesian coordinate of every bit in three-dimensional point cloud；
Using three-dimensional scanning device as coordinate center, three-dimensional cylindrical coordinate is established, and establish the flute card of every bit in three-dimensional point cloud
The transformational relation of your coordinate and cylindrical coordinates, the three-dimensional point cloud in cartesian space coordinate system is corresponded in cylindrical coordinate；
By the cylinder unwrapping of three-dimensional cylindrical coordinate, two-dimentional cylindrical coordinate system is constructed, and the column for establishing every bit in three-dimensional point cloud is sat
Three-dimensional point cloud in cylindrical coordinate is corresponded to two-dimentional cylinder and sat by the transformational relation of mark and the cylindrical coordinates of two-dimentional cylindrical coordinate system
In mark system, the two-dimensional pixel coordinate of object under test is generated.
2. the method for three-dimensional point cloud conversion two dimensional image according to claim 1, which is characterized in that the Descartes of foundation is empty
Between in coordinate system, using three-dimensional scanning device as coordinate center, the vertical rotating shaft of three-dimensional scanning device is as Z axis；Along three-dimensional
The optical axis at scanning device any level angle is as X-axis；Cylindrical coordinate and cartesian space coordinate system origin having the same, column are sat
Mark system is using the Z axis of cartesian space coordinate system as center axis, and using r as radius, the X-axis of cartesian space coordinate system is starting axis
Cylindrical surface.
3. the method for three-dimensional point cloud conversion two dimensional image according to claim 1, which is characterized in that set-point P is to be measured
Body surface any point, cartesian coordinate are (x3d-las,y3d-las,z3d-las), cylindrical coordinates is expressed as (r, ξ, z3d-cyl), according to
The transfer principle of cartesian coordinate and cylindrical coordinates, the relationship of the two are shown in following formula:
Wherein r is the distance of point P to rotary shaft Z, andξ is the plane of scanning motion and OXZ where point P
Plane included angle, z3d-cylFor the distance of point P to OXY plane.
4. the method for three-dimensional point cloud conversion two dimensional image according to claim 1, which is characterized in that three-dimensional cartesian coordinate
It is the conversion formula of the point of midpoint and two-dimentional cylindrical coordinate system are as follows:
Wherein (x3d-las,y3d-las,z3d-las) indicate three-dimensional point cloud any point cartesian space coordinate；(x2d-cyl,
y2d-cyl) indicate the pixel coordinate of corresponding two-dimentional point cloud chart picture；C indicate camera model master away from；(x0,y0) indicate two-dimensional points cloud
The principal point of image；(Δ x, Δ y) indicate the correction parameter in camera.
5. the method for three-dimensional point cloud according to claim 1 conversion two dimensional image, which is characterized in that further comprise the steps of: by
The two-dimensional pixel coordinate of every bit is further converted into two-dimentional point cloud chart as coordinate after conversion.
6. the method for three-dimensional point cloud conversion two dimensional image according to claim 5, which is characterized in that by every bit after conversion
Two-dimensional pixel coordinate be converted to two-dimentional point cloud chart as being to carry out when coordinate by following formula:
Wherein, x2d-lasIndicate abscissa of the two-dimentional point cloud chart picture in pixel coordinate system；y2d-lasIndicate that two-dimentional point cloud chart picture exists
Ordinate in pixel coordinate system；AmIndicate the horizontal resolution in pixel coordinate system；AnIndicate vertical point in pixel coordinate system
Resolution.
7. the method for three-dimensional point cloud conversion two dimensional image according to claim 6, which is characterized in that for two-dimentional point cloud chart
As midpoint (x2d-las,y2d-las) gray value, calculation formula are as follows:
Wherein, color indicates point (x2d-las,y2d-las) gray value, range is at [0-255]；Col indicates (x3d-las,y3d-las,
z3d-las) a certain characteristic value；Maxf and minf respectively indicate in three-dimensional point cloud information the maximum value of the characteristic value of corresponding point and
Minimum value.
8. the method for three-dimensional point cloud conversion two dimensional image according to claim 7, which is characterized in that when a pixel is corresponding
When the point of multiple three-dimensional point clouds, take the maximum point of characteristic value as the corresponding point of pixel；When no point in pixel, the pixel
Gray value is taken as 0.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811281912.5A CN109509143A (en) | 2018-10-31 | 2018-10-31 | A kind of method of three-dimensional point cloud conversion two dimensional image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811281912.5A CN109509143A (en) | 2018-10-31 | 2018-10-31 | A kind of method of three-dimensional point cloud conversion two dimensional image |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109509143A true CN109509143A (en) | 2019-03-22 |
Family
ID=65747136
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811281912.5A Pending CN109509143A (en) | 2018-10-31 | 2018-10-31 | A kind of method of three-dimensional point cloud conversion two dimensional image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109509143A (en) |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110435156A (en) * | 2019-09-09 | 2019-11-12 | 安徽卓锐三维科技有限公司 | A kind of dicing method for realizing 3D printing in revolving body arc-shaped surface based on RPM technology |
| CN110450406A (en) * | 2019-09-09 | 2019-11-15 | 安徽卓锐三维科技有限公司 | A method of 3D printing is realized in revolving body arc-shaped surface based on RPM technology |
| CN110916707A (en) * | 2019-12-18 | 2020-03-27 | 上海皓桦科技股份有限公司 | Two-dimensional bone image acquisition method, system and device |
| CN111091594A (en) * | 2019-10-17 | 2020-05-01 | 贝壳技术有限公司 | Multi-point cloud plane fusion method and device |
| CN111369610A (en) * | 2020-03-05 | 2020-07-03 | 山东交通学院 | Point cloud data gross error positioning and eliminating method based on credibility information |
| CN111612892A (en) * | 2020-05-22 | 2020-09-01 | 西安飞机工业（集团）有限责任公司 | Point cloud coordinate construction method |
| CN111639626A (en) * | 2020-06-11 | 2020-09-08 | 深圳市泰沃德自动化技术有限公司 | Three-dimensional point cloud data processing method and device, computer equipment and storage medium |
| CN114078326A (en) * | 2020-08-19 | 2022-02-22 | 北京万集科技股份有限公司 | Collision detection method, device, visual sensor and storage medium |
| CN114485385A (en) * | 2020-10-23 | 2022-05-13 | 广东天机工业智能系统有限公司 | Workpiece coordinate system calibration method, device and system |
| WO2022166961A1 (en) * | 2021-02-08 | 2022-08-11 | 荣耀终端有限公司 | Large-scale point cloud-oriented two-dimensional regular plane projection and encoding and decoding method |
| CN115412721A (en) * | 2021-05-26 | 2022-11-29 | 荣耀终端有限公司 | Point cloud two-dimensional regularization plane projection method and device |
| CN115641553B (en) * | 2022-12-26 | 2023-03-10 | 太原理工大学 | Online detection device and method for invaders in heading machine working environment |
| CN115937483A (en) * | 2022-12-05 | 2023-04-07 | 中科美络科技股份有限公司 | Method and device for transforming three-dimensional object in two-dimensional image based on virtual reality |
| CN116228529A (en) * | 2023-05-10 | 2023-06-06 | 南京天洑软件有限公司 | B2B surface generation method and device based on coordinate transformation |
| CN115412721B (en) * | 2021-05-26 | 2024-05-28 | 荣耀终端有限公司 | Point cloud two-dimensional regularized plane projection method and device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105809615A (en) * | 2016-03-10 | 2016-07-27 | 广州欧科信息技术股份有限公司 | Point cloud data imaging method |
| CN109214982A (en) * | 2018-09-11 | 2019-01-15 | 大连理工大学 | A kind of three-dimensional point cloud imaging method based on bicylindrical projection model |
-
2018
- 2018-10-31 CN CN201811281912.5A patent/CN109509143A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105809615A (en) * | 2016-03-10 | 2016-07-27 | 广州欧科信息技术股份有限公司 | Point cloud data imaging method |
| CN109214982A (en) * | 2018-09-11 | 2019-01-15 | 大连理工大学 | A kind of three-dimensional point cloud imaging method based on bicylindrical projection model |
Non-Patent Citations (2)
| Title |
|---|
| XIAO ZHANG: "Automatic Fusion of Hyperspectral Images and Laser Scans Using Feature Points", 《JOURNAL OF SENSORS》 * |
| 张晓: "基于改进正态分布变换算法的点云配准", 《激光与光电子学进展》 * |
Cited By (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110435156A (en) * | 2019-09-09 | 2019-11-12 | 安徽卓锐三维科技有限公司 | A kind of dicing method for realizing 3D printing in revolving body arc-shaped surface based on RPM technology |
| CN110450406A (en) * | 2019-09-09 | 2019-11-15 | 安徽卓锐三维科技有限公司 | A method of 3D printing is realized in revolving body arc-shaped surface based on RPM technology |
| CN111091594A (en) * | 2019-10-17 | 2020-05-01 | 贝壳技术有限公司 | Multi-point cloud plane fusion method and device |
| CN111091594B (en) * | 2019-10-17 | 2023-04-11 | 如你所视(北京)科技有限公司 | Multi-point cloud plane fusion method and device |
| CN110916707A (en) * | 2019-12-18 | 2020-03-27 | 上海皓桦科技股份有限公司 | Two-dimensional bone image acquisition method, system and device |
| CN110916707B (en) * | 2019-12-18 | 2023-06-27 | 上海皓桦科技股份有限公司 | Two-dimensional bone image acquisition method, system and device |
| CN111369610A (en) * | 2020-03-05 | 2020-07-03 | 山东交通学院 | Point cloud data gross error positioning and eliminating method based on credibility information |
| CN111369610B (en) * | 2020-03-05 | 2022-09-06 | 山东交通学院 | Point cloud data gross error positioning and eliminating method based on credibility information |
| CN111612892A (en) * | 2020-05-22 | 2020-09-01 | 西安飞机工业（集团）有限责任公司 | Point cloud coordinate construction method |
| CN111639626A (en) * | 2020-06-11 | 2020-09-08 | 深圳市泰沃德自动化技术有限公司 | Three-dimensional point cloud data processing method and device, computer equipment and storage medium |
| CN111639626B (en) * | 2020-06-11 | 2021-09-17 | 深圳市泰沃德技术有限公司 | Three-dimensional point cloud data processing method and device, computer equipment and storage medium |
| CN114078326A (en) * | 2020-08-19 | 2022-02-22 | 北京万集科技股份有限公司 | Collision detection method, device, visual sensor and storage medium |
| CN114485385A (en) * | 2020-10-23 | 2022-05-13 | 广东天机工业智能系统有限公司 | Workpiece coordinate system calibration method, device and system |
| CN114485385B (en) * | 2020-10-23 | 2023-07-07 | 广东天机工业智能系统有限公司 | Workpiece coordinate system calibration method, device and system |
| WO2022166961A1 (en) * | 2021-02-08 | 2022-08-11 | 荣耀终端有限公司 | Large-scale point cloud-oriented two-dimensional regular plane projection and encoding and decoding method |
| CN114915790A (en) * | 2021-02-08 | 2022-08-16 | 荣耀终端有限公司 | Two-dimensional regularization plane projection and coding and decoding method for large-scale point cloud |
| CN114915790B (en) * | 2021-02-08 | 2024-04-12 | 荣耀终端有限公司 | Two-dimensional regularized plane projection and encoding and decoding method for large-scale point cloud |
| CN115412721A (en) * | 2021-05-26 | 2022-11-29 | 荣耀终端有限公司 | Point cloud two-dimensional regularization plane projection method and device |
| CN115412721B (en) * | 2021-05-26 | 2024-05-28 | 荣耀终端有限公司 | Point cloud two-dimensional regularized plane projection method and device |
| CN115937483A (en) * | 2022-12-05 | 2023-04-07 | 中科美络科技股份有限公司 | Method and device for transforming three-dimensional object in two-dimensional image based on virtual reality |
| CN115641553B (en) * | 2022-12-26 | 2023-03-10 | 太原理工大学 | Online detection device and method for invaders in heading machine working environment |
| CN116228529A (en) * | 2023-05-10 | 2023-06-06 | 南京天洑软件有限公司 | B2B surface generation method and device based on coordinate transformation |
| CN116228529B (en) * | 2023-05-10 | 2023-09-08 | 南京天洑软件有限公司 | B2B surface generation method and device based on coordinate transformation |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109509143A (en) | A kind of method of three-dimensional point cloud conversion two dimensional image | |
| CN109029284B (en) | A kind of three-dimensional laser scanner based on geometrical constraint and camera calibration method | |
| US10690492B2 (en) | Structural light parameter calibration device and method based on front-coating plane mirror | |
| CN104142157B (en) | A kind of scaling method, device and equipment | |
| CN109945853B (en) | Geographic coordinate positioning system and method based on 3D point cloud aerial image | |
| CN108389232B (en) | Geometric correction method for irregular surface projection image based on ideal viewpoint | |
| CN100470590C (en) | Camera calibration method and calibration apparatus thereof | |
| CN104335005B (en) | 3D is scanned and alignment system | |
| CN104395932B (en) | Method for registering data | |
| CN107884767A (en) | A kind of method of binocular vision system measurement ship distance and height | |
| CN104574406B (en) | A kind of combined calibrating method between 360 degree of panorama laser and multiple vision systems | |
| CN100449459C (en) | Calibrating method for single camera virtual mouse system | |
| CN108592884B (en) | A kind of general linear array satellite core line image generating method | |
| CN107316325A (en) | A kind of airborne laser point cloud based on image registration and Image registration fusion method | |
| CN109186491A (en) | Parallel multi-thread laser measurement system and measurement method based on homography matrix | |
| CN108416812A (en) | A kind of scaling method of single camera mirror image binocular vision system | |
| CN107680139A (en) | Universality calibration method of telecentric binocular stereo vision measurement system | |
| CN109919911A (en) | Moving three dimension method for reconstructing based on multi-angle of view photometric stereo | |
| CN108759669A (en) | A kind of self-positioning 3-D scanning method and system in interior | |
| CN107155341A (en) | 3 D scanning system and framework | |
| CN111091076B (en) | Tunnel limit data measuring method based on stereoscopic vision | |
| CN106500626A (en) | A kind of mobile phone stereoscopic imaging method and three-dimensional imaging mobile phone | |
| CN109373912A (en) | A kind of non-contact six-freedom displacement measurement method based on binocular vision | |
| CN108362205A (en) | Space ranging method based on fringe projection | |
| CN109285195A (en) | Distortion correction method and its application pixel-by-pixel of monocular optical projection system based on large scale target |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190322 |
|
| WD01 | Invention patent application deemed withdrawn after publication |