CN107504917B - Three-dimensional size measuring method and device - Google Patents
Three-dimensional size measuring method and device Download PDFInfo
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- CN107504917B CN107504917B CN201710710102.6A CN201710710102A CN107504917B CN 107504917 B CN107504917 B CN 107504917B CN 201710710102 A CN201710710102 A CN 201710710102A CN 107504917 B CN107504917 B CN 107504917B
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Abstract
The invention discloses a three-dimensional size measuring method and device, and relates to the technical field of measurement. The method comprises the following steps: acquiring three-dimensional point cloud data of a target measuring piece, and determining the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance between two adjacent point positions; deleting point cloud data corresponding to the point positions, wherein the distance between the point position and the shot object is greater than a first threshold value, and the distance between two adjacent point positions is greater than a second threshold value, so as to obtain first three-dimensional point cloud data; determining the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface by adopting an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of a shot object; and establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system, and determining the three-dimensional size and volume of the target measurement object according to the three-dimensional model.
Description
Technical Field
The invention relates to the technical field of measurement, in particular to a three-dimensional size measurement method and device.
Background
The automatic and accurate acquisition of the logistics attributes such as the three-dimensional size, the volume, the weight and the bar code of the commodity is facilitated, and the logistics enterprise can achieve higher and faster logistics requirements. At present, in domestic logistics enterprises, the collection and development of product weight and bar code information are relatively mature, weighing equipment such as an electronic scale is used for weighing, bar codes are read by a scanning gun and the like, a good effect can be achieved, but the manual measurement of tools such as a tape measure and the like is generally used in occasions where the three-dimensional size of a product needs to be measured. In the traditional mode, the three-dimensional size measurement of the product has the disadvantages of backward tool, low efficiency, high labor cost, non-uniform error, disputes of both sides of trade caused by the measurement result, and the obtained data is isolated from the whole information flow of the logistics system. With the increasing demands of customers on logistics efficiency and cost settlement, the method is increasingly unable to adapt to modern logistics requirements with high efficiency and accuracy.
Aiming at the acquisition of three-dimensional size information of products, the most adopted technical schemes at present are methods such as (infrared) light curtain measurement, ultrasonic measurement, laser measurement and the like. The three-dimensional size of an irregular product is difficult to measure by the light curtain measurement, and the operation is complex; ultrasonic measurement can only measure the three-dimensional size of a regular product, and measurement of an irregular product is completed by other auxiliary tools, so that the operation is complex and the requirement on the environment is high; laser measurement can be applied to regular and irregular products, but needs an industrial sensor with high price, has high equipment cost and is difficult to popularize and utilize.
In conclusion, the existing three-dimensional information acquisition mainly depends on an industrial sensor, and the problem of high equipment cost exists.
Disclosure of Invention
The embodiment of the invention provides a three-dimensional size measuring method and device, which are used for solving the problem that the existing three-dimensional size information acquisition mainly depends on an industrial sensor and has higher equipment cost.
The embodiment of the invention provides a three-dimensional size measuring method, which comprises the following steps:
acquiring three-dimensional point cloud data of a target measuring piece, and determining the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance between two adjacent point positions;
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a first threshold value and the distance between two adjacent point positions is greater than a second threshold value to obtain first three-dimensional point cloud data;
determining the distance between the shot object and a reference surface and the included angle between the shot object and the reference surface by adopting an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface;
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system, and determining the three-dimensional size and the volume of the target measurement object according to the three-dimensional model.
Preferably, the photographic subject includes any one of:
binocular vision camera, structured light camera, TOF camera.
Preferably, after obtaining the first three-dimensional point cloud data, the method further includes:
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a third threshold value and the distance between two adjacent point positions is greater than a fourth threshold value to obtain second three-dimensional point cloud data;
and deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a fifth threshold value and the distance between two adjacent point positions is greater than a sixth threshold value to obtain the third three-dimensional point cloud data.
Preferably, after the mapping the first three-dimensional point cloud data to the coordinate system of the photographic subject, the method further includes:
mapping the second three-dimensional point cloud data to a coordinate system of the shot object; mapping the third three-dimensional point cloud data to a coordinate system of the shot object;
before the three-dimensional model of the three-dimensional point cloud data is established according to the first three-dimensional point cloud data mapped to the coordinate system, the method further comprises the following steps:
and obtaining a first group of three-dimensional point cloud data, a second group of three-dimensional point cloud data and a third group of three-dimensional point cloud data by adopting a least square method for the first three-dimensional point cloud data, the second three-dimensional point cloud data and the third three-dimensional point cloud data.
Preferably, the establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system includes:
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first set of three-dimensional point cloud data, the second set of three-dimensional point cloud data and the third set of three-dimensional point cloud data.
An embodiment of the present invention further provides a three-dimensional size measuring apparatus, including:
the first determining unit is used for acquiring three-dimensional point cloud data of a target measuring piece, and determining the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance between two adjacent point positions;
a deleting unit, configured to delete the point cloud data corresponding to the point location where a distance between the point location and the photographed object is greater than a first threshold and a distance between two adjacent point locations is greater than a second threshold, so as to obtain first three-dimensional point cloud data;
the mapping unit is used for determining the distance between the shot object and a reference surface and the included angle between the shot object and the reference surface by adopting an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface;
and the second determining unit is used for establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system and determining the three-dimensional size and the volume of the target measuring object according to the three-dimensional model.
Preferably, the photographic subject includes any one of:
binocular vision camera, structured light camera, TOF camera.
Preferably, the deleting unit is further configured to:
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a third threshold value and the distance between two adjacent point positions is greater than a fourth threshold value to obtain second three-dimensional point cloud data;
and deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a fifth threshold value and the distance between two adjacent point positions is greater than a sixth threshold value to obtain the third three-dimensional point cloud data.
Preferably, the mapping unit is further configured to:
mapping the second three-dimensional point cloud data to a coordinate system of the shot object; mapping the third three-dimensional point cloud data to a coordinate system of the shot object;
the second determination unit is further configured to:
and obtaining a first group of three-dimensional point cloud data, a second group of three-dimensional point cloud data and a third group of three-dimensional point cloud data by adopting a least square method for the first three-dimensional point cloud data, the second three-dimensional point cloud data and the third three-dimensional point cloud data.
Preferably, the second determining unit is specifically configured to:
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first set of three-dimensional point cloud data, the second set of three-dimensional point cloud data and the third set of three-dimensional point cloud data.
In an embodiment of the present invention, a three-dimensional size measurement method is provided, including: acquiring three-dimensional point cloud data of a target measuring piece, and determining the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance between two adjacent point positions; deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a first threshold value and the distance between two adjacent point positions is greater than a second threshold value to obtain first three-dimensional point cloud data; determining the distance between the shot object and a reference surface and the included angle between the shot object and the reference surface by adopting an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface; and establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system, and determining the three-dimensional size and the volume of the target measurement object according to the three-dimensional model. According to the method, three-dimensional point cloud data of a target measurement object is obtained through a shot object, and a three-dimensional model can be built on the processed three-dimensional data through screening and mapping processing of the three-dimensional point cloud data, so that three-dimensional size and volume information of the target measurement object can be obtained from the three-dimensional model. According to the method, the three-dimensional point cloud data of the target measurement piece is acquired by a conventional method, and the information such as the three-dimensional size, the volume and the like of the target measurement piece can be acquired by processing the three-dimensional point cloud data, so that the problem that the existing three-dimensional size information acquisition mainly depends on an industrial sensor, and the three-dimensional size information acquisition cost is high is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a three-dimensional size measurement method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a three-dimensional dimension measuring apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 schematically illustrates a flow chart of a three-dimensional size measurement method according to an embodiment of the present invention. As shown in fig. 1, the method mainly comprises the following steps:
102, deleting the point cloud data corresponding to the point positions, wherein the distance between the point position and the shot object is greater than a first threshold value, and the distance between two adjacent point positions is greater than a second threshold value, so as to obtain first three-dimensional point cloud data;
103, determining the distance between the shot object and a reference surface and the included angle between the shot object and the reference surface by using an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface;
and 104, establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system, and determining the three-dimensional size and the volume of the target measurement object according to the three-dimensional model.
Before describing the three-dimensional size measurement method provided by the embodiment of the present invention, several terms need to be introduced:
1. binocular stereo vision is an important form of machine vision, and is a method for acquiring three-dimensional geometric information of an object by acquiring two images of the object to be measured from different positions by using imaging equipment based on a parallax principle and calculating position deviation between corresponding points of the images. The binocular stereo vision measuring method has the advantages of high efficiency, proper precision, simple system structure, low cost and the like, and is very suitable for online and non-contact product detection and quality control of a manufacturing site.
2. The binocular stereoscopic vision camera consists of a left camera and a right camera, and can obtain three-dimensional information of a surrounding area of a measured object through visual calculation.
3. A tof (time of flight) camera is one of depth cameras, cannot obtain intensity images as a traditional 2D camera, and can also obtain the distance from each pixel point on a photosensitive device to a corresponding point of a target object in real time. The TOF camera can efficiently capture brightness information and distance information of a dynamic target in real time.
4. SLAM (Simultaneous Localization and mapping) simultaneous positioning and mapping means that a robot creates a map in a completely unknown environment under the adjustment of uncertain self position, and meanwhile, the map is used for autonomous positioning and navigation. In positioning, the robot must know its position in the environment; in mapping, the robot must record the location of features in the environment; the basic principle of establishing an environment map while positioning the robot is that positioning and positioning errors are reduced by a multi-feature matching method through a probability statistics method.
In step 101, three-dimensional point cloud data of a target measurement piece is acquired through a camera, and it should be noted that in the embodiment of the present invention, the camera for acquiring the three-dimensional point cloud data of the target measurement piece may be a binocular vision camera, a structured light camera, or a TOF camera.
After the three-dimensional point cloud data of the target measuring piece is acquired, the three-dimensional point cloud data can be processed through a three-dimensional point cloud data processor, and the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance information between the point cloud data and a plurality of adjacent point cloud data are mainly determined, for example, the three-dimensional point cloud data includes 4 point cloud data and a camera, the distance between the point position distribution corresponding to the 4 point cloud data and the camera needs to be determined through the three-dimensional point cloud data processor, then whether the 4 point cloud data have an adjacent relation is determined, if the first point cloud data is surrounded by the second point cloud data and the third point cloud data, and the first point cloud data, the second point cloud data and the fourth point cloud data are located on the same straight line, the distance between the first point cloud data and the second point cloud data needs to be determined, a distance between the first point cloud data and the third point cloud data and a distance between the second point cloud data and the fourth point cloud data.
In step 102, after the distance between the point position corresponding to the determined point cloud data and the object to be photographed and the distance between two adjacent point positions are determined, a plurality of thresholds may be determined according to actual needs, where the first threshold, the third threshold, and the fifth threshold are used to determine the distance between the point position corresponding to the point cloud data and the object to be photographed, and the second threshold, the fourth threshold, and the sixth threshold are used to determine the distance between two adjacent point positions.
Specifically, point cloud data corresponding to a point position, the distance between the point position and a shot object of which is greater than a first threshold value and the distance between two adjacent point positions of which is greater than a second threshold value, is deleted to obtain first three-dimensional point cloud data; deleting point cloud data corresponding to the point positions, wherein the distance between the point position and the shot object is greater than a third threshold value, and the distance between two adjacent point positions is greater than a fourth threshold value, so as to obtain second three-dimensional point cloud data; and deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a fifth threshold value and the distance between two adjacent point positions is greater than a sixth threshold value to obtain third three-dimensional point cloud data.
In step 103, determining the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface by using an SLAM algorithm on the three-dimensional point cloud data; wherein, the reference surface is a plane for arranging the shot object.
Further, a coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface.
In the embodiment of the invention, the first three-dimensional point cloud data is mapped to the coordinate system of the shot object; mapping the second three-dimensional point cloud data to a coordinate system of the shot object; and mapping the third three-dimensional point cloud data to a coordinate system of the shot object.
Further, the first three-dimensional point cloud data, the second three-dimensional point cloud data and the third three-dimensional point cloud data are subjected to a least square method to obtain a first group of three-dimensional point cloud data, a second group of three-dimensional point cloud data and a third group of three-dimensional point cloud data.
In step 104, a three-dimensional model of the three-dimensional point cloud data is established according to the first set of three-dimensional point cloud data, the second set of three-dimensional point cloud data and the third set of three-dimensional point cloud data, and the three-dimensional size and the volume of the target measurement object are determined according to the three-dimensional model.
After step 104, displaying the three-dimensional size and the volume of the target measurement object through a set display device.
Based on the same inventive concept, the embodiment of the invention provides a three-dimensional size measuring device, and as the principle of solving the technical problem of the device is similar to that of a three-dimensional size measuring method, the implementation of the device can refer to the implementation of the method, and repeated details are omitted.
Fig. 2 is a schematic structural diagram of a three-dimensional size measuring apparatus according to an embodiment of the present invention, and as shown in fig. 2, the apparatus includes a first determining unit 21, a deleting unit 22, a mapping unit 23, and a second determining unit 24.
A first determining unit 21, configured to acquire three-dimensional point cloud data of a target measurement object, and determine a distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a photographed object and a distance between two adjacent point positions;
a deleting unit 22, configured to delete the point cloud data corresponding to the point location where the distance between the point location and the photographed object is greater than a first threshold and the distance between two adjacent point locations is greater than a second threshold, so as to obtain first three-dimensional point cloud data;
a mapping unit 23, configured to determine a distance between the object and a reference surface and an included angle between the object and the reference surface by using a SLAM algorithm for the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface;
and the second determining unit 24 is used for establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system, and determining the three-dimensional size and the volume of the target measurement object according to the three-dimensional model.
Preferably, the photographic subject includes any one of:
binocular vision camera, structured light camera, TOF camera.
Preferably, the deleting unit 22 is further configured to:
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a third threshold value and the distance between two adjacent point positions is greater than a fourth threshold value to obtain second three-dimensional point cloud data;
and deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a fifth threshold value and the distance between two adjacent point positions is greater than a sixth threshold value to obtain the third three-dimensional point cloud data.
Preferably, the mapping unit 23 is further configured to:
mapping the second three-dimensional point cloud data to a coordinate system of the shot object; mapping the third three-dimensional point cloud data to a coordinate system of the shot object;
the second determination unit is further configured to:
and obtaining a first group of three-dimensional point cloud data, a second group of three-dimensional point cloud data and a third group of three-dimensional point cloud data by adopting a least square method for the first three-dimensional point cloud data, the second three-dimensional point cloud data and the third three-dimensional point cloud data.
Preferably, the second determining unit 24 is specifically configured to:
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first set of three-dimensional point cloud data, the second set of three-dimensional point cloud data and the third set of three-dimensional point cloud data.
It should be understood that the above three-dimensional size measuring device includes only the units logically divided according to the functions implemented by the apparatus device, and in practical applications, the above units may be stacked or separated. The functions of the three-dimensional size measuring device provided in this embodiment correspond to those of the three-dimensional size measuring method provided in the above embodiment one to one, and for the more detailed processing flow implemented by the device, detailed description is already given in the above method embodiment, and detailed description is not given here.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A three-dimensional measurement method, comprising:
acquiring three-dimensional point cloud data of a target measuring piece, and determining the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance between two adjacent point positions;
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a first threshold value and the distance between two adjacent point positions is greater than a second threshold value to obtain first three-dimensional point cloud data;
determining the distance between the shot object and a reference surface and the included angle between the shot object and the reference surface by adopting an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface;
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system, and determining the three-dimensional size and the volume of the target measurement object according to the three-dimensional model.
2. The method of claim 1, wherein the photographic subject comprises any one of:
binocular vision camera, structured light camera, TOF camera.
3. The method of claim 1, wherein after obtaining the first three-dimensional point cloud data, further comprising:
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a third threshold value and the distance between two adjacent point positions is greater than a fourth threshold value to obtain second three-dimensional point cloud data;
and deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a fifth threshold value and the distance between two adjacent point positions is greater than a sixth threshold value to obtain the third three-dimensional point cloud data.
4. The method of claim 3, wherein after mapping the first three-dimensional point cloud data to the coordinate system of the photographic subject, further comprising:
mapping the second three-dimensional point cloud data to a coordinate system of the shot object; mapping the third three-dimensional point cloud data to a coordinate system of the shot object;
before the three-dimensional model of the three-dimensional point cloud data is established according to the first three-dimensional point cloud data mapped to the coordinate system, the method further comprises the following steps:
and obtaining a first group of three-dimensional point cloud data, a second group of three-dimensional point cloud data and a third group of three-dimensional point cloud data by adopting a least square method for the first three-dimensional point cloud data, the second three-dimensional point cloud data and the third three-dimensional point cloud data.
5. The method of claim 4, wherein the building a three-dimensional model of the three-dimensional point cloud data from the first three-dimensional point cloud data mapped to the coordinate system comprises:
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first set of three-dimensional point cloud data, the second set of three-dimensional point cloud data and the third set of three-dimensional point cloud data.
6. A three-dimensional measuring device, comprising:
the first determining unit is used for acquiring three-dimensional point cloud data of a target measuring piece, and determining the distance between a point position corresponding to each point cloud data included in the three-dimensional point cloud data and a shot object and the distance between two adjacent point positions;
a deleting unit, configured to delete the point cloud data corresponding to the point location where a distance between the point location and the photographed object is greater than a first threshold and a distance between two adjacent point locations is greater than a second threshold, so as to obtain first three-dimensional point cloud data;
the mapping unit is used for determining the distance between the shot object and a reference surface and the included angle between the shot object and the reference surface by adopting an SLAM algorithm on the three-dimensional point cloud data; mapping the first three-dimensional point cloud data to a coordinate system of the shot object; the coordinate system of the shot object is determined according to the distance between the shot object and the reference surface and the included angle between the shot object and the reference surface;
and the second determining unit is used for establishing a three-dimensional model of the three-dimensional point cloud data according to the first three-dimensional point cloud data mapped to the coordinate system and determining the three-dimensional size and the volume of the target measuring object according to the three-dimensional model.
7. The apparatus of claim 6, wherein the photographic subject comprises any one of:
binocular vision camera, structured light camera, TOF camera.
8. The apparatus of claim 6, wherein the deletion unit is further to:
deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a third threshold value and the distance between two adjacent point positions is greater than a fourth threshold value to obtain second three-dimensional point cloud data;
and deleting the point cloud data corresponding to the point positions of which the distance between the point position and the shot object is greater than a fifth threshold value and the distance between two adjacent point positions is greater than a sixth threshold value to obtain the third three-dimensional point cloud data.
9. The apparatus of claim 8, wherein the mapping unit is further configured to:
mapping the second three-dimensional point cloud data to a coordinate system of the shot object; mapping the third three-dimensional point cloud data to a coordinate system of the shot object;
the second determination unit is further configured to:
and obtaining a first group of three-dimensional point cloud data, a second group of three-dimensional point cloud data and a third group of three-dimensional point cloud data by adopting a least square method for the first three-dimensional point cloud data, the second three-dimensional point cloud data and the third three-dimensional point cloud data.
10. The apparatus of claim 9, wherein the second determining unit is specifically configured to:
and establishing a three-dimensional model of the three-dimensional point cloud data according to the first set of three-dimensional point cloud data, the second set of three-dimensional point cloud data and the third set of three-dimensional point cloud data.
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| CN108519051A (en) * | 2018-03-29 | 2018-09-11 | 中铁十局集团桥梁有限公司 | A kind of box beam measurement method and device |
| CN110515054B (en) * | 2019-08-23 | 2021-07-23 | 斯坦德机器人（深圳）有限公司 | Filtering method and device, electronic equipment and computer storage medium |
| CN111307037B (en) * | 2020-04-14 | 2022-10-14 | 深圳市异方科技有限公司 | Handheld volume measuring device based on 3D camera |
| CN112733641A (en) * | 2020-12-29 | 2021-04-30 | 深圳依时货拉拉科技有限公司 | Object size measuring method, device, equipment and storage medium |
| CN113295089B (en) * | 2021-04-07 | 2024-04-26 | 深圳市异方科技有限公司 | Carriage volume rate measuring method based on visual inertia SLAM |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106056643A (en) * | 2016-04-27 | 2016-10-26 | 武汉大学 | Point cloud based indoor dynamic scene SLAM (Simultaneous Location and Mapping) method and system |
| CN106127770A (en) * | 2016-06-27 | 2016-11-16 | 感知控股集团有限公司 | Contour measuring method and system |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106056643A (en) * | 2016-04-27 | 2016-10-26 | 武汉大学 | Point cloud based indoor dynamic scene SLAM (Simultaneous Location and Mapping) method and system |
| CN106127770A (en) * | 2016-06-27 | 2016-11-16 | 感知控股集团有限公司 | Contour measuring method and system |
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