CN108680100A - Three-dimensional laser point cloud data and unmanned plane point cloud data matching process - Google Patents
Three-dimensional laser point cloud data and unmanned plane point cloud data matching process Download PDFInfo
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- CN108680100A CN108680100A CN201810186670.5A CN201810186670A CN108680100A CN 108680100 A CN108680100 A CN 108680100A CN 201810186670 A CN201810186670 A CN 201810186670A CN 108680100 A CN108680100 A CN 108680100A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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Abstract
The present invention relates to the matching process of a kind of three-dimensional laser point cloud data and unmanned plane point cloud data, include the following steps：Step S1：The unmanned plane point cloud data of object is obtained by unmanned plane；Step S2：The three-dimensional laser point cloud data of object is obtained by three-dimensional laser scanner；Step S3：The three-dimensional laser point cloud data and unmanned plane point cloud data are converted as same format to；Step S4：Using the unmanned plane point cloud data as referential, it is that the RGB color type based on three dimensional point cloud chooses multiple same places and the point cloud data of the two is established relevant matches in the way of global registration that three-dimensional laser point cloud data, which is mobile,.The present invention acts on：Air-ground integration is realized by point cloud data acquisition process, reduces shortage of data existing for the point cloud data that three-dimensional laser or unmanned plane unidirectionally obtain, more fully object data information is provided for researcher.
Description
Technical field
The present invention relates to the matching process of a kind of three-dimensional laser point cloud data and unmanned plane point cloud data.
Background technology
Currently, three-dimensional laser and unmanned plane point cloud data, due to the needs of research, are often needed in field of forestry fast development
Storey three-dimensional structure information is accurately obtained, how quickly, effectively obtain comprehensive point cloud data seems especially important.
Although the research for obtaining point cloud data using unmanned plane and three-dimensional laser scanner is more universal, unidirectional ground point cloud data or
, often there is the missing of point cloud data in person's aviation point cloud data, can not completely reflect the characteristic information of object.
Invention content
The present invention is improved the above problem, that is, uses that the technical problem to be solved by the present invention is to realize ground, empty
Point cloud data matches, and obtains more complete point cloud data.
Specific embodiments of the present invention are：
A kind of three-dimensional laser point cloud data and unmanned plane point cloud data matching process, which is characterized in that include the following steps：
Step S1：The unmanned plane point cloud data of object is obtained by unmanned plane；
Step S2：The three-dimensional laser point cloud data of object is obtained by three-dimensional laser scanner；
Step S3：The three-dimensional laser point cloud data and unmanned plane point cloud data are converted as same format to；
Step S4：Using the unmanned plane point cloud data as referential, it is to be based on three-dimensional point cloud that three-dimensional laser point cloud data, which is mobile,
The RGB color type of data chooses multiple same places and the point cloud data of the two is established correlation in the way of global registration
Match.
Preferably, the unmanned plane point cloud data is to be encrypted by three encryption of sky, point cloud based on unmanned aerial vehicle remote sensing technology
The unmanned plane point cloud data arrived, data format LAS.
Preferably, the three-dimensional laser point cloud data is the Three Dimensional Ground laser obtained by ground three-dimensional laser scanner
Point cloud data, data format X3S.
Preferably, in step S1 and step S2, respectively by unmanned plane and by three-dimensional laser scanner based on not
Under the conditions of same color, different angle, different reflectivity, point cloud data is obtained to same object.
Preferably, in step s3, the point cloud data of three-dimensional laser scanner and unmanned plane point cloud data are switched to have
The TXT text document formats of identical cartesian coordinate system.
Preferably, when obtaining point cloud data to object, by the matching of multiple culture points of the same name, it is complete to extend to object
Office's matching.
Compared with prior art, the invention has the advantages that：Air-ground one is realized by point cloud data acquisition process
Body reduces shortage of data existing for the point cloud data that three-dimensional laser or unmanned plane unidirectionally obtain, and is provided for researcher more complete
The object data information in face.
Description of the drawings
Fig. 1 is the present embodiment overall procedure schematic diagram；
Fig. 2 is three-dimensional laser point cloud data schematic diagram；
Fig. 3 is unmanned plane point cloud data schematic diagram；
Fig. 4 is the present embodiment point cloud data coordinate value and color information schematic diagram；
Fig. 5 is three-dimensional laser point cloud data figure in the present embodiment；
Fig. 6 is unmanned plane point cloud data figure in the present embodiment；
Fig. 7 is the present embodiment point cloud data matching process schematic diagram.
Specific implementation mode
The present invention will be further described in detail in the following with reference to the drawings and specific embodiments.
As shown in Figure 1, in the present embodiment, including the following steps：
Step S1：The unmanned plane point cloud data of object is obtained by unmanned plane；
Step S2：The three-dimensional laser point cloud data of object is obtained by three-dimensional laser scanner；
Step S3：Three-dimensional laser point cloud data and unmanned plane point cloud data are converted as same format to；
Step S4：Using unmanned plane point cloud data as referential, three-dimensional laser point cloud data, which is mobile, is, by being based on three-dimensional point cloud
The RGB color type of data chooses multiple same places and the point cloud data of the two is established correlation in the way of global registration
Match.
As shown in Fig. 2, in the present embodiment, three-dimensional laser point cloud data is obtained by ground three-dimensional laser scanner
Three Dimensional Ground laser point cloud data, by the point cloud data of three-dimensional laser scanner by grid pretreatment, thick splicing, essence splicing life
At multi-level point cloud data, data format X3S.
As shown in figure 3, unmanned plane point cloud data is based on unmanned aerial vehicle remote sensing technology, encrypted by three encryption of sky, point cloud
The unmanned plane point cloud data arrived, data format LAS.
In the present embodiment, in step S1 and step S2, respectively by unmanned plane and by three-dimensional laser scanner in base
Under the conditions of different colours, different angle, different reflectivity, point cloud data is obtained to same object.
In step s3, the point cloud data of three-dimensional laser scanner and unmanned plane point cloud data are switched to have identical flute card
The TXT text document formats of your coordinate system.
When obtaining point cloud data to object, by the matching of multiple culture points of the same name, object global registration is extended to.
Specifically, in the present embodiment, first, the three-dimensional laser point cloud number of object is obtained by three-dimensional laser scanner
According to；The pretreatments such as format conversion, the denoising of point cloud, splicing, the three-dimensional laser point needed are carried out according to the mating software of instrument
Cloud data（Fig. 2）, by the three-dimensional laser point cloud data point of use cloud processing software Stonex Reconstructor export of importing
For the format of text document, to carry out subsequent processing；
Secondly, the unmanned plane point cloud data that object is obtained by unmanned plane carries out sky three according to the relevant software of unmanned plane and adds
The processing such as close, point cloud encryption obtain required unmanned plane point cloud data（Fig. 3）.
The point cloud data of the two is converted under unified format using cyclone Point Cloud Processings software, including is sat
Mark information and color（RGB）Information（Fig. 4）, the RGB color type based on three dimensional point cloud chooses 3 culture points of the same name, sharp
With global registration, using the coordinate system of the ground three-dimensional laser point cloud data of acquisition as reference pattern（Fig. 5）, by unmanned plane point cloud
The coordinate system of data is set as Move Mode（Fig. 6）, so that the point cloud data of the two is carried out relevant matches, obtain complete target
Object point cloud data information, as shown in Figure 7.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification should all belong to the covering scope of the present invention.
Claims (6)
1. a kind of three-dimensional laser point cloud data and unmanned plane point cloud data matching process, which is characterized in that include the following steps：
Step S1：The unmanned plane point cloud data of object is obtained by unmanned plane；
Step S2：The three-dimensional laser point cloud data of object is obtained by three-dimensional laser scanner；
Step S3：Convert the three-dimensional laser point cloud data and unmanned plane point cloud data to same format；
Step S4：Using the unmanned plane point cloud data as referential, it is to be based on three-dimensional point cloud that three-dimensional laser point cloud data, which is mobile,
The RGB color type of data chooses multiple same places and the point cloud data of the two is established correlation in the way of global registration
Match.
2. three-dimensional laser point cloud data according to claim 1 and unmanned plane point cloud data matching process, it is characterised in that：
The unmanned plane point cloud data is based on unmanned aerial vehicle remote sensing technology, is encrypted by sky three, the unmanned plane point cloud that point cloud is encrypted
Data, data format LAS.
3. three-dimensional laser point cloud data according to claim 1 and unmanned plane point cloud data matching process, it is characterised in that：
The three-dimensional laser point cloud data is the Three Dimensional Ground laser point cloud data obtained by ground three-dimensional laser scanner, data lattice
Formula is X3S.
4. according to the three-dimensional laser point cloud data required described in 1 and unmanned plane point cloud data matching process, it is characterised in that：In step
In rapid S1 and step S2, respectively by unmanned plane and by three-dimensional laser scanner based on different colours, different angle, difference
Reflectivity under the conditions of, to same object obtain point cloud data.
5. according to the three-dimensional laser point cloud data required described in 1 and unmanned plane point cloud data matching process, it is characterised in that：In step
In rapid S3, the point cloud data of three-dimensional laser scanner and unmanned plane point cloud data are switched to have identical cartesian coordinate system
TXT text document formats.
6. according to the three-dimensional laser point cloud data required described in 4 and unmanned plane point cloud data matching process, it is characterised in that：To mesh
When marking object acquisition point cloud data, by the matching of multiple culture points of the same name, object global registration is extended to.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020156273A1 (en) * | 2019-02-02 | 2020-08-06 | 南京林业大学 | Method for digital surveying and mapping and three-dimensional visualization in garden space |
| CN111866484A (en) * | 2019-04-30 | 2020-10-30 | 华为技术有限公司 | Point cloud encoding method, point cloud decoding method, point cloud encoding device, point cloud decoding device, and storage medium |
| WO2021046716A1 (en) * | 2019-09-10 | 2021-03-18 | 深圳市大疆创新科技有限公司 | Method, system and device for detecting target object and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103426165A (en) * | 2013-06-28 | 2013-12-04 | 吴立新 | Precise registration method of ground laser-point clouds and unmanned aerial vehicle image reconstruction point clouds |
| CN103017653B (en) * | 2012-11-27 | 2015-06-24 | 武汉海达数云技术有限公司 | Registration and measurement method of spherical panoramic image and three-dimensional laser scanning point cloud |
| CN105157602A (en) * | 2015-07-13 | 2015-12-16 | 西北农林科技大学 | Remote three-dimensional scanning system and method based on machine vision |
| CN105809681A (en) * | 2016-03-04 | 2016-07-27 | 清华大学 | Single camera based human body RGB-D data restoration and 3D reconstruction method |
| CN105825543A (en) * | 2016-03-31 | 2016-08-03 | 武汉大学 | Multi-view dense point cloud generation method and system based on low-altitude remote sensing images |
| CN105973145A (en) * | 2016-05-19 | 2016-09-28 | 深圳市速腾聚创科技有限公司 | Movable type three dimensional laser scanning system and movable type three dimensional laser scanning method |
| CN106056563A (en) * | 2016-05-20 | 2016-10-26 | 首都师范大学 | Airborne laser point cloud data and vehicle laser point cloud data fusion method |
| CN106933786A (en) * | 2017-03-07 | 2017-07-07 | 福建农林大学 | A kind of three-dimensional laser point cloud data rapid voxel processing method |
-
2018
- 2018-03-07 CN CN201810186670.5A patent/CN108680100B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103017653B (en) * | 2012-11-27 | 2015-06-24 | 武汉海达数云技术有限公司 | Registration and measurement method of spherical panoramic image and three-dimensional laser scanning point cloud |
| CN103426165A (en) * | 2013-06-28 | 2013-12-04 | 吴立新 | Precise registration method of ground laser-point clouds and unmanned aerial vehicle image reconstruction point clouds |
| CN105157602A (en) * | 2015-07-13 | 2015-12-16 | 西北农林科技大学 | Remote three-dimensional scanning system and method based on machine vision |
| CN105809681A (en) * | 2016-03-04 | 2016-07-27 | 清华大学 | Single camera based human body RGB-D data restoration and 3D reconstruction method |
| CN105825543A (en) * | 2016-03-31 | 2016-08-03 | 武汉大学 | Multi-view dense point cloud generation method and system based on low-altitude remote sensing images |
| CN105973145A (en) * | 2016-05-19 | 2016-09-28 | 深圳市速腾聚创科技有限公司 | Movable type three dimensional laser scanning system and movable type three dimensional laser scanning method |
| CN106056563A (en) * | 2016-05-20 | 2016-10-26 | 首都师范大学 | Airborne laser point cloud data and vehicle laser point cloud data fusion method |
| CN106933786A (en) * | 2017-03-07 | 2017-07-07 | 福建农林大学 | A kind of three-dimensional laser point cloud data rapid voxel processing method |
Non-Patent Citations (2)
| Title |
|---|
| 阚酉浔: "基于多源测量数据融合的三维实景重建结束研究", 《中国优秀博士学位论文全文数据库 基础科学辑》 * |
| 陈鉴知: "矿区高分辨率空间数据的获取及在土地复垦管理中的应用", 《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020156273A1 (en) * | 2019-02-02 | 2020-08-06 | 南京林业大学 | Method for digital surveying and mapping and three-dimensional visualization in garden space |
| CN111866484A (en) * | 2019-04-30 | 2020-10-30 | 华为技术有限公司 | Point cloud encoding method, point cloud decoding method, point cloud encoding device, point cloud decoding device, and storage medium |
| WO2021046716A1 (en) * | 2019-09-10 | 2021-03-18 | 深圳市大疆创新科技有限公司 | Method, system and device for detecting target object and storage medium |
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