CN111553970B - Point cloud real-time measurement method based on server - Google Patents
Point cloud real-time measurement method based on server Download PDFInfo
- Publication number
- CN111553970B CN111553970B CN202010422641.1A CN202010422641A CN111553970B CN 111553970 B CN111553970 B CN 111553970B CN 202010422641 A CN202010422641 A CN 202010422641A CN 111553970 B CN111553970 B CN 111553970B
- Authority
- CN
- China
- Prior art keywords
- dimensional
- point cloud
- server
- matrix
- steps
- 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.)
- Active
Links
- 238000000691 measurement method Methods 0.000 title claims abstract description 9
- 238000009877 rendering Methods 0.000 claims abstract description 18
- 238000005259 measurement Methods 0.000 claims abstract description 12
- 238000005516 engineering process Methods 0.000 claims abstract description 10
- 239000011159 matrix material Substances 0.000 claims description 55
- 238000000034 method Methods 0.000 claims description 30
- 230000009466 transformation Effects 0.000 claims description 23
- 239000013598 vector Substances 0.000 claims description 21
- 238000004364 calculation method Methods 0.000 abstract description 21
- 238000012545 processing Methods 0.000 abstract description 8
- 238000004458 analytical method Methods 0.000 abstract description 7
- 230000003993 interaction Effects 0.000 abstract description 7
- 238000012800 visualization Methods 0.000 abstract description 4
- 238000012827 research and development Methods 0.000 abstract description 3
- 238000000926 separation method Methods 0.000 abstract description 3
- 241000350052 Daniellia ogea Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000002592 echocardiography Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000013215 result calculation Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012876 topography Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/10—Geometric effects
- G06T15/20—Perspective computation
- G06T15/205—Image-based rendering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F3/04845—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0487—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Graphics (AREA)
- Human Computer Interaction (AREA)
- Geometry (AREA)
- Architecture (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- Software Systems (AREA)
- Processing Or Creating Images (AREA)
Abstract
The invention relates to the technical field of data processing, and provides a point cloud real-time measurement method based on a server side, wherein the point cloud data is loaded by utilizing a three-dimensional rendering technology, and basic display is carried out on the point cloud data; according to the loaded point cloud data, entering a measurement state, and acquiring relevant parameters of the current three-dimensional view; and transmitting the parameters into the server, and calculating and returning a result meeting the conditions by the server. The traditional measurement mode is converted from the application end mouse pickup interaction to the server end calculation analysis, the problem that the high configuration requirement of a computer is required in the traditional point cloud three-dimensional visualization scene is solved, the application resources of a current computer are saved, the storage and calculation processing are put into the cloud end of the server, the actual application and calculation separation are achieved, the permission control of point cloud data is conveniently increased, and the research and development efficiency is improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a point cloud real-time measurement method based on a server.
Background
Laser radar (LIDAR) is used as a novel data acquisition device, and provides a novel technical scheme for accurate space measurement of a power system. The laser radar can obtain three-dimensional information of the geography, and the geometric airborne platform enables the airborne radar system to be well applied to the operation and maintenance of the power transmission line, and achieves detection of dangerous ground objects of a line channel, fine measurement of distances between power lines, topography analysis of the line channel, tree prediction, cutting plan management, simulation application of working conditions and the like.
The sensors such as the laser radar, the binocular camera or the depth camera can acquire a large amount of high-density three-dimensional point cloud data, and the point cloud data measurement contains rich information such as longitude and latitude coordinates, intensity, multiple echoes, color and the like of each point. The laser radar scanner device commonly used at present, such as Riegl, faro, leica, can generate thousands of points per second, the number of data points obtained by scanning each time can reach thousands of points, even tens of millions and billions are very likely, and the point cloud data loading and mouse pickup interaction are completed at the application end as shown in fig. 2, and finally, the result is returned at the application end, so that the huge data volume brings challenges to the processing and storage of the data.
Patent application number 201910646107.6 entitled "three-dimensional point cloud data storage and query method and device" discloses obtaining three-dimensional point cloud data, dividing the obtained three-dimensional point cloud data into a plurality of subsets, wherein each subset comprises a plurality of data blocks, storing the divided three-dimensional point cloud data in a block table, wherein row data blocks in the block table are listed as divided subsets, and constructing and storing data indexes by rows and columns of the block table. According to the method, the three-dimensional point cloud data are divided into the subsets and stored in the block table, and when the three-dimensional point cloud data are read, data meeting the requirements can be searched in each divided subset, so that the searching efficiency is improved, and long waiting time is not needed when the three-dimensional point cloud data are read. However, the application still has the problem of huge data volume of point cloud, the stored system still can be burdened, resources of a CPU or a GPU are consumed in the storage and query processes, if the CPU is adopted for picking up, the computing capacity of the current computer is required to be particularly high, and the points meeting the conditions can be screened out only by tens of thousands of times of cycle traversal; if the GPU is adopted for picking up, the computer is required to have a display card configuration, although the calculation is faster than that of the CPU, the result calculation result needs the GPU and the CPU to transmit data, the memory of the GPU is consumed, and if the number of points is more, a display card with high memory is also required.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a real-time point cloud measuring method based on a server, converts the traditional measuring mode from the interactive pickup of an application end mouse to the calculation and analysis of the server, and solves the problem that a computer is required to have high configuration requirements in the traditional three-dimensional point cloud visualization scene.
In order to achieve the above object, the embodiment of the present invention provides the following technical solutions:
a point cloud real-time measurement method based on a server side comprises the following steps:
step S1: loading point cloud data by utilizing a three-dimensional rendering technology, and performing basic display on the point cloud data;
step S2: according to the loaded point cloud data, entering a measurement state, and acquiring relevant parameters of the current three-dimensional view;
step S3: and transmitting the parameters into the server, and calculating and returning a result meeting the conditions by the server.
Furthermore, to specifically describe the manner of loading point cloud data and performing basic display on the point cloud data by using the three-dimensional rendering technology, the method specifically includes: and the point cloud data loaded by the three-dimensional rendering technology is used as three-dimensional space points, the three-dimensional space point set is subjected to geometric transformation and projected onto the three-dimensional coordinates, and then the three-dimensional coordinates are cut and projected onto the two-dimensional coordinates through matrix transformation for basic display.
Further, the step of performing basic display by clipping the three-dimensional coordinates and projecting the clipped three-dimensional coordinates onto the two-dimensional coordinates through matrix transformation includes:
model matrix transformation is carried out on the three-dimensional coordinates after cutting to obtain a world coordinate system;
performing Project matrix on the world coordinate system to obtain a view coordinate system;
the view coordinate system is subjected to a Viewer matrix to obtain a clipping coordinate system;
and performing view port transformation on the clipping coordinate system to obtain two-dimensional coordinates.
Further, to describe in detail the specific step of entering a measurement state according to the loaded point cloud data, acquiring relevant parameters of the current three-dimensional view, the step S2 specifically includes the following steps:
step S2-1: acquiring screen coordinates (u, v) of a position clicked by a mouse;
step S2-2: acquiring the file name or the data number of the loaded point cloud data in the current display range;
step S2-3: and acquiring rendering parameters of the three-dimensional view in the current display range.
Further, for describing in detail the step of obtaining the screen coordinates (u, v) of the position of the mouse click, the method specifically includes:
step S2-1 (a): the w component is added to the three-dimensional coordinates (x, y, z) to be changed into vectors (x, y, z, l);
step S2-1 (b): sequentially multiplying the transformed Model matrix, project matrix and Viewer matrix to vectors (x, y, z, l) to obtain four-dimensional vectors, performing homogeneous division on the four-dimensional vectors, and dividing all components of the vectors (x, y, z, l) by w components;
step S2-1 (c): and performing Viewport matrix transformation by using the x component and the y component to obtain screen coordinates (u, v) of the position clicked by the mouse.
Further, for describing in detail the step of obtaining the screen coordinates (u, v) of the position clicked by the mouse, the method specifically includes:
and obtaining two-dimensional coordinates, multiplying the Model matrix, the Project matrix, the Viewer matrix and the Viewport matrix to obtain a Model view projection matrix, and obtaining screen coordinates (u, v) of the clicking position of the mouse by using matrix parameters.
Further, in order to perfect the step of acquiring the relevant parameters of the three-dimensional view, the step S2 further includes:
step S2-4: and forming a number set by acquiring file names or data numbers of the loaded point cloud data in all the display ranges, and taking the number set as a parameter record.
Further, in order to describe the step of transmitting the parameters to the server in detail, the server calculates and returns the result satisfying the condition, and the step S3 specifically includes the following steps:
step S3-1: transmitting the number set and the rendering parameters to a server;
step S3-2: the server analyzes the parameters and acquires point cloud data according to the analyzed parameters of the numbered set;
step S3-3: and converting the point cloud data into screen coordinates by utilizing a three-dimensional coordinate projection principle, and calculating and returning points meeting the conditions by the server according to rules to form a coordinate point or point set.
Further, for detailing the point that the server calculates according to the rule and returns to satisfy the condition, a coordinate point or point set is formed, which includes:
and according to the parameters of the mouse position, the server processes the point closest to the current mouse position parameters or the point within the self-defined space distance to form a coordinate point or point set.
Furthermore, in order to perfect the point cloud real-time measurement method based on the server side, the method further comprises the step S4: the application end obtains the result returned by the server end and displays the result.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the existing mode of converting the mouse pickup interaction of the application terminal into the calculation analysis of the server terminal, and the interaction is changed into a service API interface based on the method of measuring the server terminal, so that the calculation efficiency is higher by utilizing the resources of the server; in the calculation process, the point cloud data can be loaded by utilizing a three-dimensional rendering technology, and basic display is carried out on the point cloud data; then, according to the loaded point cloud data, entering a measurement state, and acquiring relevant parameters of the current three-dimensional view; the parameters are transmitted into a server, and the server calculates and returns a result meeting the conditions; the whole calculation processing process solves the problem that the traditional point cloud three-dimensional visualization scene needs to be required to be configured higher, simultaneously saves application resources of a current computer, places storage and calculation processing in the cloud of a server, achieves separation of actual application and calculation, facilitates the increase of authority control of point cloud data, and improves research and development efficiency.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for computing and analyzing a server according to the present invention;
FIG. 2 is a flow chart of a prior art application-side mouse pickup interaction method;
FIG. 3 is a flow chart of a method for measuring point cloud in real time according to an embodiment of the present invention;
FIG. 4 is a flow chart of acquiring relevant parameters of a three-dimensional view according to an embodiment of the present invention;
FIG. 5 is a flow chart of the calculation and analysis of the server side of the present invention;
FIG. 6 is a flow chart of three-dimensional coordinate transformation two-dimensional coordinate according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present invention.
Examples:
the invention is realized by the following technical scheme, as shown in fig. 1, a point cloud real-time measurement method based on a server side, which converts the traditional measurement mode from the interaction of the mouse pickup of an application side to the calculation and analysis of the server side, and comprises the following steps as shown in fig. 3:
step S1: and loading the point cloud data by utilizing a three-dimensional rendering technology, and performing basic display on the point cloud data.
And the point cloud data loaded by the three-dimensional rendering technology is used as three-dimensional space points, the three-dimensional space point set is subjected to geometric transformation and projected onto the three-dimensional coordinates, and then the three-dimensional coordinates are cut and projected onto the two-dimensional coordinates through matrix transformation for basic display.
Specifically, the step of performing basic display by clipping the three-dimensional coordinates and projecting the clipped three-dimensional coordinates onto the two-dimensional coordinates through matrix transformation, as shown in fig. 6, includes:
model matrix transformation is carried out on the three-dimensional coordinates after cutting to obtain a world coordinate system;
performing Project matrix on the world coordinate system to obtain a view coordinate system;
the view coordinate system is subjected to a Viewer matrix to obtain a clipping coordinate system;
and performing view port transformation on the clipping coordinate system to obtain two-dimensional coordinates.
Step S2: and entering a measurement state according to the loaded point cloud data, and acquiring relevant parameters of the current three-dimensional view.
Since the point cloud data is three-dimensional space points and the computer display screen is two-dimensional, the three-dimensional coordinates need to be converted into the coordinates of the two-dimensional space by displaying the three-dimensional point cloud data on the computer.
As shown in fig. 4, a specific screen coordinate (u, v) of the position clicked by the mouse is obtained at the application end, at this time, the measurement work is performed from the application end into the server end, since the point cloud data operation object is a four-dimensional vector, the three-dimensional coordinate (x, y, z) needs to be supplemented with a w component and changed into a vector (x, y, z, l), then the Model matrix, project matrix and view matrix transformed in the step S1 are multiplied to the vector (x, y, z, l) in turn, the obtained four-dimensional vector is divided by the w component, that is, all components in the four-dimensional vector are divided by the w component, and then the x component and the y component in the four-dimensional vector are utilized to perform the view port matrix transformation, so as to obtain the screen coordinate (u, v) of the position clicked by the mouse.
As another embodiment, firstly performing view port transformation on three-dimensional coordinates (x, y, z) of point cloud data to obtain two-dimensional coordinates under clipping coordinates, and then multiplying Model matrix, project matrix, viewer matrix and Viewport matrix to obtain a Model view projection matrix, and obtaining screen coordinates (u, v) of a position clicked by a mouse by using the matrix parameters.
After the screen coordinates (u, v) of the position clicked by the mouse are obtained by using any one of the two modes, the file name or the data number of the loaded point cloud data in the current display range of the application end is obtained, the data number can be called as a data ID, and the data ID is used as a unique mark of the point cloud data, namely, a plurality of positions clicked by the mouse form the point cloud data with the data number. And further acquiring file names or data IDs of the loaded point cloud data in all the display ranges to form an ID set as a parameter record.
And finally, obtaining rendering parameters of the three-dimensional view in the current display range, wherein the rendering parameters comprise camera parameters, a view transformation matrix and the like, and the view transformation matrix is the Model matrix, the Project matrix, the Viewer matrix and the Viewport matrix. The relevant parameters of the current three-dimensional view described in step S2 thus include the ID set parameters and the rendering parameters of the three-dimensional view.
Step S3: and transmitting the parameters into the server, and calculating and returning a result meeting the conditions by the server.
As shown in fig. 5, the application end transmits the ID set parameters and the rendering parameters of the three-dimensional view to the server end from the application end, the server end analyzes the parameters, and can quickly find corresponding point cloud data according to the analyzed point cloud data ID, and then calculate and return the result meeting the conditions by using the three-dimensional coordinate projection principle. The storage and calculation processing is carried out in the cloud of the processor, the application and calculation are separated, a high-configuration computer is not needed, the application resource of the computer is saved, the calculation efficiency is higher, and the situations of calculation errors, loss and the like of point cloud data caused by overlarge occupied computer memory are avoided.
In detail, after converting the point cloud data into screen coordinates by using the three-dimensional coordinate projection principle, according to the parameters of the mouse position, the server side forms a coordinate point or a point set which is the result of meeting the condition from the point closest to the current mouse position parameters or the point within the distance of meeting the user-defined control.
Step S4: the application end obtains the result returned by the server end and displays the result.
According to the invention, the existing mode of converting the mouse pickup interaction of the application terminal into the calculation analysis of the server terminal is converted into a service API interface based on the measurement method of the server terminal, the resource of the server is utilized, the calculation efficiency is higher, the problem that the configuration is required to be higher in the traditional three-dimensional point cloud visualization scene is solved, the application resource of the current computer is saved, the storage and calculation processing is put into the cloud of the server, the actual application and calculation separation is realized, the authority control of point cloud data is conveniently increased, and the research and development efficiency is improved.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A point cloud real-time measurement method based on a server side is characterized by comprising the following steps of: the method comprises the following steps:
step S1: loading point cloud data by utilizing a three-dimensional rendering technology, and performing basic display on the point cloud data;
step S2: according to the loaded point cloud data, entering a measurement state, and acquiring relevant parameters of the current three-dimensional view;
step S3: the parameters are transmitted into a server, and the server calculates and returns a result meeting the conditions;
the method for carrying out basic display on the point cloud data by utilizing the three-dimensional rendering technology comprises the following steps of: the method comprises the steps of utilizing point cloud data loaded by a three-dimensional rendering technology as three-dimensional space points, carrying out geometric transformation and projection on a three-dimensional space point set to a three-dimensional coordinate, cutting the three-dimensional coordinate, and then carrying out basic display on the three-dimensional coordinate projected to a two-dimensional coordinate through matrix transformation;
the step of performing basic display by projecting the three-dimensional coordinates onto the two-dimensional coordinates through matrix transformation after cutting the three-dimensional coordinates comprises the following steps:
model matrix transformation is carried out on the three-dimensional coordinates after cutting to obtain a world coordinate system;
performing Project matrix on the world coordinate system to obtain a view coordinate system;
the view coordinate system is subjected to a Viewer matrix to obtain a clipping coordinate system;
then performing view port transformation on the clipping coordinate system to obtain two-dimensional coordinates;
the step S2 specifically includes the following steps:
step S2-1: acquiring screen coordinates (u, v) of a position clicked by a mouse;
step S2-2: acquiring the file name or the data number of the loaded point cloud data in the current display range;
step S2-3: acquiring rendering parameters of a three-dimensional view in a current display range;
the step of obtaining the screen coordinates (u, v) of the position clicked by the mouse specifically comprises the following steps:
step S2-1 (a): the w component is added to the three-dimensional coordinates (x, y, z) to be changed into vectors (x, y, z, l);
step S2-1 (b): sequentially multiplying the transformed Model matrix, project matrix and Viewer matrix to vectors (x, y, z, l) to obtain four-dimensional vectors, performing homogeneous division on the four-dimensional vectors, and dividing all components of the vectors (x, y, z, l) by w components;
step S2-1 (c): performing Viewport matrix transformation by using the x component and the y component to obtain screen coordinates (u, v) of the position clicked by the mouse;
the step of obtaining the screen coordinates (u, v) of the position clicked by the mouse specifically comprises the following steps:
step S2-1 (a): the w component is added to the three-dimensional coordinates (x, y, z) to be changed into vectors (x, y, z, l);
step S2-1 (b): sequentially multiplying the transformed Model matrix, project matrix and Viewer matrix to vectors (x, y, z, l) to obtain four-dimensional vectors, performing homogeneous division on the four-dimensional vectors, and dividing all components of the vectors (x, y, z, l) by w components;
step S2-1 (c): and performing Viewport matrix transformation by using the x component and the y component to obtain screen coordinates (u, v) of the position clicked by the mouse.
2. The method for measuring the point cloud based on the server side in real time according to claim 1, wherein the method comprises the following steps: the step of obtaining the screen coordinates (u, v) of the position clicked by the mouse specifically comprises the following steps:
and obtaining two-dimensional coordinates, multiplying the Model matrix, the Project matrix, the Viewer matrix and the Viewport matrix to obtain a Model view projection matrix, and obtaining screen coordinates (u, v) of the clicking position of the mouse by using matrix parameters.
3. The method for measuring the point cloud based on the server side in real time according to claim 1, wherein the method comprises the following steps: the step S2 further includes:
step S2-4: and forming a number set by acquiring file names or data numbers of the loaded point cloud data in all the display ranges, and taking the number set as a parameter record.
4. The method for measuring the point cloud based on the server side in real time according to claim 3, wherein the method comprises the following steps: the step S3 specifically comprises the following steps:
step S3-1: transmitting the number set and the rendering parameters to a server;
step S3-2: the server analyzes the parameters and acquires point cloud data according to the analyzed parameters of the numbered set;
step S3-3: and converting the point cloud data into screen coordinates by utilizing a three-dimensional coordinate projection principle, and calculating and returning points meeting the conditions by the server according to rules to form a coordinate point or point set.
5. The method for measuring the point cloud based on the server side in real time according to claim 4, wherein the method comprises the following steps: the server calculates and returns points meeting the conditions according to the rules to form a coordinate point or point set, and the method comprises the following steps:
and according to the parameters of the mouse position, the server processes the point closest to the current mouse position parameters or the point within the self-defined space distance to form a coordinate point or point set.
6. The method for measuring point cloud based on a server according to any one of claims 1 to 5, wherein the method comprises the following steps: further comprising step S4: the application end obtains the result returned by the server end and displays the result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010422641.1A CN111553970B (en) | 2020-05-19 | 2020-05-19 | Point cloud real-time measurement method based on server |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010422641.1A CN111553970B (en) | 2020-05-19 | 2020-05-19 | Point cloud real-time measurement method based on server |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111553970A CN111553970A (en) | 2020-08-18 |
| CN111553970B true CN111553970B (en) | 2024-02-20 |
Family
ID=72003539
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010422641.1A Active CN111553970B (en) | 2020-05-19 | 2020-05-19 | Point cloud real-time measurement method based on server |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111553970B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102044084A (en) * | 2009-10-22 | 2011-05-04 | 上海杉达学院 | Two-dimensional plane expression method of three-dimensional graph |
| WO2016082252A1 (en) * | 2014-11-27 | 2016-06-02 | 苏州福丰科技有限公司 | Airport security check method through three-dimensional face recognition based on cloud server |
| CN105808672A (en) * | 2016-03-01 | 2016-07-27 | 重庆市勘测院 | Browser based mass three-dimensional point cloud data release method |
-
2020
- 2020-05-19 CN CN202010422641.1A patent/CN111553970B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102044084A (en) * | 2009-10-22 | 2011-05-04 | 上海杉达学院 | Two-dimensional plane expression method of three-dimensional graph |
| WO2016082252A1 (en) * | 2014-11-27 | 2016-06-02 | 苏州福丰科技有限公司 | Airport security check method through three-dimensional face recognition based on cloud server |
| CN105808672A (en) * | 2016-03-01 | 2016-07-27 | 重庆市勘测院 | Browser based mass three-dimensional point cloud data release method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111553970A (en) | 2020-08-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112115198B (en) | Urban remote sensing intelligent service platform | |
| US8793107B2 (en) | Accuracy-based significant point derivation from dense 3D point clouds for terrain modeling | |
| Zhong et al. | Spatiotemporal visualisation: A survey and outlook | |
| CN112528508B (en) | Electromagnetic visualization method and device | |
| CN109059949B (en) | Shortest path calculation method and device | |
| CN111683388B (en) | Near-field radiation attenuation test method and three-dimensional display system | |
| KR20180053724A (en) | Method for encoding bright-field content | |
| CN114140592A (en) | High-precision map generation method, device, equipment, medium and automatic driving vehicle | |
| CN116308185A (en) | Visual progress input and early warning method for constructional engineering | |
| CN116384020A (en) | Digital twin substation space layout method integrating multidimensional semantic information | |
| CN102565554B (en) | Method for generating three-dimensional lightning positioned place flash point distribution map | |
| CN111553970B (en) | Point cloud real-time measurement method based on server | |
| CN113034679A (en) | Real-time dynamic three-dimensional visual display method for power transmission line | |
| CN110322553B (en) | Method and system for lofting implementation of laser radar point cloud mixed reality scene | |
| CN115424261A (en) | Warehouse point cloud semantic segmentation method and device, computer equipment and storage medium | |
| CN111353007B (en) | Geographic element pickup method, coding method and device based on vector slicing and electronic equipment | |
| CN113483661B (en) | Point cloud data acquisition method, device, equipment and storage medium | |
| CN113822892B (en) | Evaluation method, device and equipment of simulated radar and computer storage medium | |
| CN116597102A (en) | Asset map automatic scaling method and system | |
| CN116188565A (en) | Position area detection method, device, apparatus, storage medium and program product | |
| CN112000729B (en) | GIS system for electric power engineering | |
| CN109509234B (en) | Urban building group high-definition grid map vectorization-based method | |
| CN107845136B (en) | Terrain flattening method for three-dimensional scene | |
| CN112231430A (en) | Map data management method and device | |
| Xiong et al. | Depth map recovery based on optimal scheduling of invalid point filling |
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 | ||
| CB02 | Change of applicant information |
Address after: Room 2301-2308, third floor, building 2, incubator, Zhongguancun Software Park, Dongbeiwang, Haidian District, Beijing 100094 Applicant after: Beijing Digital Green Earth Technology Co.,Ltd. Address before: Room 2301-2308, third floor, building 2, incubator, Zhongguancun Software Park, Dongbeiwang, Haidian District, Beijing 100094 Applicant before: BEIJING GREENVALLEY TECHNOLOGY Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |