Data compression device, data compression method, and program

Abstract

The purpose of the present invention is to provide a data compression device, a data compression method, and a program with which it is possible to reduce the amount of point clouds acquired by a three-dimensional laser scanner without affecting the creation of a three-dimensional model.　The data compression device 50 according to the present invention compresses three-dimensional point cloud data that represents the three-dimensional coordinates of points on the surface of an outdoor structure and that is acquired by a three-dimensional laser scanner while moving, the data compression device 50 comprising a point cloud elimination unit (51 and / or 52) for reducing the amount of three-dimensional point cloud data in accordance with a discretionary criterion and calculating a scan line that is eliminated through the reduction in the amount of three-dimensional point cloud data, and an extraction processing unit 53 for creating a three-dimensional model from the reduced three-dimensional point cloud data while omitting the eliminated scan lines that are stored.

Description

[Technical Field]

[0001] The present disclosure relates to a data compression device, a data compression method, and a program for compressing three-dimensional point cloud data representing three-dimensional coordinates of points on the surface of an outdoor structure, the data cloud data being acquired by a three-dimensional laser scanner. [Background technology]

[0002] A technology has been developed for creating a three-dimensional model of an outdoor structure using an on-board three-dimensional laser scanner (Mobile Mapping System: MMS) (see, for example, Patent Document 1). Fig. 3 is a diagram illustrating an MMS. The MMS includes a three-dimensional laser scanner 46 as a measurement unit, a camera 42 as an imaging unit, a GPS (Global Positioning System) receiver 43, an IMU 44 as an inertial measurement unit, an odometer 45 as a running distance meter, a storage medium 47, and a computing device 48.

[0003] While traveling, the MMS performs a three-dimensional survey of the surroundings using a three-dimensional laser scanner 46, camera 42, GPS receiver 43, IMU 44, and odometer 45, and stores the data obtained in a storage medium 47 that serves as a point cloud data storage device. The storage medium 47 is configured, for example, with an HDD (Hard Disk Drive) or SSD (Solid State Drive), and map data of the area to be managed is stored in advance. The camera 42 is a camera whose imaging direction can be arbitrarily changed using a pan-tilt mechanism and whose imaging range can be changed using a zoom function.

[0004] This technology creates a point cloud 10a and a scan line 20a in a space Ar1 where no point clouds exist, as shown in Figure 1, and then creates a 3D model M10 as shown in Figure 2.This makes it possible to improve the recall and precision of the 3D model even when the point cloud is in a raw state (when the vehicle speed is high), thereby achieving good results.

[0005] In Figure 1, reference numeral 10 denotes the point cloud acquired by the 3D laser scanner, and reference numeral 20 denotes the scan line of the 3D laser scanner. A scan line is a line that connects point clouds other than the wall surfaces of cylindrical objects and the ground from the point cloud data with close GPS times (within one rotation of the laser scanner). Also, reference numeral 30 denotes a line showing how points on a scan line correspond to points on other scan lines, but this line is a visual representation and is not used for modeling purposes. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-156179 Summary of the Invention [Problem to be solved by the invention]

[0007] The goal is to store the point cloud acquired by the 3D laser scanner in a database so that the equipment status can be checked later on a PC without having to go to the site. However, MMS does not have a function to change the number of laser irradiation points depending on the vehicle's speed, and a large number of point clouds are acquired when the vehicle is traveling at low speeds. Furthermore, some conventional technologies use not only coordinates but also the time obtained from a satellite positioning system (e.g., GPS) (hereinafter referred to as "GPS time") to create 3D models. Because the point cloud and GPS time are important, it is not possible to appropriately thin out the data, resulting in a huge data volume. Furthermore, when the vehicle is traveling at low speeds or is stopped, points with the same coordinates but different GPS times may occur. Thinning out the points in this manner makes it impossible to create a 3D model, or reduces the accuracy of the 3D model.

[0008] Therefore, in order to solve the above problem, the present invention aims to provide a data compression device, a data compression method, and a program that can thin out point clouds acquired by a 3D laser scanner without affecting the creation of a 3D model. [Means for solving the problem]

[0009] In order to achieve the above object, the data compression device of the present invention prevents the impact on the creation of a 3D model when thinning out point clouds by retaining information on the time at which the point clouds were deleted.

[0010] Specifically, the data compression device according to the present invention is a data compression device that compresses three-dimensional point cloud data representing three-dimensional coordinates of points on the surface of an outdoor structure, the three-dimensional point cloud data being acquired by a moving three-dimensional laser scanner, and includes: a point cloud removal unit that thins out the three-dimensional point cloud data according to an arbitrary criterion and calculates scan lines that have been deleted by thinning out the three-dimensional point cloud data; an extraction processing unit that creates a 3D model from the 3D point cloud data after thinning while skipping the deleted scan lines that are stored; The present invention is characterized by comprising:

[0011] Further, a data compression method according to the present invention is a data compression method for compressing three-dimensional point cloud data representing three-dimensional coordinates of points on the surface of an outdoor structure, the three-dimensional point cloud data being acquired by a three-dimensional laser scanner while moving, the method comprising: thinning the three-dimensional point cloud data according to an arbitrary criterion; Calculating scan lines deleted by thinning out the three-dimensional point cloud data; and Creating a 3D model from the decimated 3D point cloud data while skipping the deleted scan lines stored in the memory. It is characterized by:

[0012] Conventionally, when creating a 3D model, point clouds were detected from a storage medium in the order of GPS time, but if the point cloud was thinned out, it was not possible to detect the point cloud at the desired GPS time, making it impossible to create a 3D model or reducing the accuracy of the 3D model.The data compression device and method according to the present invention can grasp the GPS time of the thinned point cloud, so point cloud detection is not performed for that time, and the point cloud at the unthinned GPS time is detected as the next data.

[0013] Therefore, it is possible to provide a data compression device and a data compression method that can thin out a point cloud acquired by a three-dimensional laser scanner without affecting the creation of a three-dimensional model.

[0014] For example, the arbitrary criterion of the point cloud removal unit can be a criterion determined by the moving speed of the three-dimensional laser scanner.

[0015] For example, the arbitrary criterion of the point cloud removal unit may be a criterion determined based on the type of the outdoor structure.

[0016] The present invention also provides a program for causing a computer to function as the data compression device. The data compression device of the present invention can also be realized by a computer and a program, and the program can be recorded on a recording medium or provided via a network.

[0017] The above inventions can be combined as much as possible. [Effects of the Invention]

[0018] The present invention can provide a data compression device, a data compression method, and a program that can thin out a point cloud acquired by a 3D laser scanner without affecting the creation of a 3D model. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 2 is a diagram illustrating a point cloud and a scan line. [Figure 2] FIG. 10 is a diagram illustrating a three-dimensional model to be created. [Figure 3] FIG. 1 is a diagram illustrating MMS. [Figure 4] 1 is a diagram illustrating a data compression device according to the present invention; [Figure 5] 1A and 1B are diagrams illustrating the concept of point cloud removal performed by a data compression device according to the present invention. [Figure 6] 1 is a diagram illustrating a data compression method according to the present invention; [Figure 7] 1A and 1B are diagrams illustrating the concept of point cloud removal performed by a data compression device according to the present invention. [Figure 8] 1 is a diagram illustrating a data compression method according to the present invention; [Figure 9] 1A and 1B are diagrams illustrating the concept of point cloud removal performed by a data compression device according to the present invention. [Figure 10] 1 is a diagram illustrating a data compression device according to the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0020] The following description of the preferred embodiments of the present invention will be given with reference to the accompanying drawings. The preferred embodiments described below are examples of the present invention, and the present invention is not limited to the preferred embodiments. In this specification and the drawings, components having the same reference numerals are intended to represent the same components.

[0021] (Embodiment 1) 4 is a diagram illustrating a data compression device 50 of this embodiment. The data compression device 50 is a data compression device that compresses three-dimensional point cloud data representing three-dimensional coordinates of points on the surface of an outdoor structure, which data is acquired by a three-dimensional laser scanner while moving, and a point cloud removal unit (at least one of 51 and 52) that thins out the three-dimensional point cloud data according to an arbitrary criterion and calculates scan lines that have been deleted by thinning out the three-dimensional point cloud data; an extraction processing unit 53 that creates a 3D model from the 3D point cloud data after thinning while skipping the deleted scan lines stored therein; Equipped with.

[0022] The MMS separates data (acceleration data D1, distance D2, position and time D3) acquired by various measuring devices (IMU 44, laser scanner 46, camera 42, odometer 45, GPS receiver 43) into point cloud data D4 and image data D5, and inputs them to the data compression device 50. The image data D5 is stored as is in the storage medium 47. If the data compression device 50 is equipped with a point cloud removal unit 51, the point cloud data D4 is input to the point cloud removal unit 51. If the data compression device 50 is not equipped with the point cloud removal unit 51, the point cloud data D4 is stored as is in the storage medium 47.

[0023] The point cloud removal unit 51 removes unnecessary point clouds from the point cloud data D4 based on an arbitrary criterion. Here, the arbitrary criterion of the point cloud removal unit 51 is a criterion determined by the movement speed of the 3D laser scanner. Figure 5 is a diagram illustrating the concept of point cloud removal performed by the point cloud removal unit 51.

[0024] The point cloud removal unit 51 calculates the speed at the time of measurement from the GPS measurement time (any other time can be used as long as it can represent the acquisition time of each point) and the distance traveled by the MMS, and applies a thinning rate for each speed. For example, as shown in FIG. 5, the point cloud removal unit 51 removes many point clouds (point clouds 10 on scan lines 20-2 and 20-3) when moving at a low speed, and does not remove any point clouds 10 when moving at a high speed. By having the point cloud removal unit 51 remove point clouds 10 for each speed, it is possible to compress the data volume while maintaining the accuracy of the model.

[0025] 6 is a flowchart illustrating the point cloud deletion method performed by the point cloud removal unit 51. The point cloud removal unit 51 acquires GPS information included in the point cloud data D4 (step S11). The GPS information is the acquisition time (e.g., T1, T2) and acquisition position (e.g., X1, X2) at which the point was acquired. The point cloud removal unit 51 calculates the speed of the MMS (step S12). Specifically, it calculates (X2-X1) / (T2-T1).

[0026] The point cloud removal unit 51 removes the point clouds according to a rule determined for each vehicle speed (step S13). The rule may be as follows: Point clouds are removed by combining these rules. (1) Point cloud deletion proportional to vehicle speed Calculate the maximum speed at which 3D modeling is possible from the point cloud, and adjust the number of scan lines when traveling at different speeds to match that number. If the speed is half the maximum, the number of scan lines should be reduced to half, and if the speed is one-third, the number should be reduced to one-third. If the speed is 0, the same location is being measured, so they can be deleted all at once. For example, suppose you need to travel at 60 km / h or less to model a utility pole. When traveling at 30 km / h, the number of scan lines that can be obtained is twice that at 60 km / h, so delete the scan lines obtained at 30 km / h so that they are halved. (2) Maintaining the lowest point cloud density Calculating the deflection value of a cable requires precision, so a certain amount of point cloud is necessary. Since deleting too many points will result in a deterioration in precision, the point cloud is deleted while satisfying the condition (minimum point cloud density) that allows calculation of a deflection value equivalent to that calculated by the conventional method. (3) Set point cloud density The point cloud is removed for each scan line (each rotation of the laser scanner) or within the processing time until the point density reaches a set percentage.

[0027] After deleting the point cloud, the point cloud removal unit 51 calculates and stores the number of deleted scan lines. The calculated number of scan lines is used in the processing of the extraction processing unit 53, which will be described later (data D7). The point cloud removal unit 51 stores the deleted point cloud (thinned point cloud D4a) in the storage medium 47.

[0028] As shown in FIG. 4, the point cloud removal unit 51 does not remove the point cloud in real time when acquiring the point cloud, but removes the point cloud after the measurement is completed and before the point cloud data is stored in the storage medium 47.

[0029] The extraction processing unit 53 determines the object (type of outdoor structure) of the point cloud data D6 stored in the storage medium 47, and notifies the point cloud removal unit 52 of the type of outdoor structure along with the point cloud data (data D8). The point cloud removal unit 52 removes unnecessary point clouds based on an arbitrary criterion, and re-stores only the necessary point clouds in the storage medium 47 (thinned point cloud data D9). Here, the arbitrary criterion of the point cloud removal unit 52 is a criterion determined by the type of outdoor structure.

[0030] FIG. 7 is a diagram illustrating the concept of point cloud removal performed by the point cloud removal unit 52. Using data D8 from the extraction processing unit 53, the point cloud removal unit 52 calculates the density of the point cloud 10 and removes points until the required point cloud density is reached. For example, as shown in FIG. 7, the point cloud removal unit 52 imagines a vertically long box 35 whose major axis is parallel to the corresponding line axis 30 and calculates the point cloud density within it. The point cloud removal unit 52 then removes points until the point cloud reaches the desired density. When calculating equipment information for small-diameter equipment such as cables, a high-density point cloud is required, so it is preferable to change the point cloud density for each piece of equipment. By having the point cloud removal unit 52 set the desired point cloud density for each piece of equipment, the data volume can be compressed while maintaining the accuracy of the model.

[0031] 8 is a flowchart illustrating a point cloud deletion method performed by the point cloud removal unit 52. The point cloud removal unit 52 determines whether the point cloud data D6 extracted by the extraction processing unit 53 is used for creating a 3D model (step S21). If the point cloud data D6 is a point cloud used for creating a 3D model, the point cloud removal unit 52 calculates the point cloud density (step S22).

[0032] The point cloud removal unit 52 removes the point clouds up to a certain point cloud density in accordance with a rule (step S23). Here, the point cloud removal unit 52 determines which object the point cloud data D6 is used to create a 3D model of (such as a utility pole, cable, or closure), and then leaves the point clouds with the point cloud density necessary for the object and deletes the rest. The rule is a point cloud density determined for each object.

[0033] By using equipment inspection technology using point clouds, such as that described in Patent Document 1, it is possible to determine whether a point cloud is being used to create a model. Specifically, whether it is a wall or a cylindrical object can be determined from the shape of the scan line, and if it is a cylindrical object, it is possible to automatically distinguish it as a utility pole, mast, cable, etc. from its thickness and angle. Here, utility poles and masts can be modeled even if their point cloud density is lower than that of cables. For this reason, a rule is set that sets a high point cloud density for cables and a low point cloud density for utility poles and masts (point cloud density of cables > point cloud density of utility poles and masts). For example, a rule is set such that the point cloud density for cables is 100 and the point cloud density for utility poles is 50. In other words, the number of deleted points is reduced for objects with a small number of obtainable point clouds, such as cables, and the number of deleted points is increased for objects with a large number of obtainable point clouds, such as utility poles.

[0034] After deleting the point clouds, the point cloud removal unit 52 calculates and stores the number of deleted scan lines. The calculated number of scan lines is used in processing by the extraction processing unit 53, which will be described later (data D11).

[0035] On the other hand, if the point clouds are not used to create a 3D model, the point cloud removal unit 52 removes the point clouds so that the point cloud density becomes a collectively determined value (which may be 0 if the point clouds are not used for other purposes such as reproducing a landscape) (step S25). For example, the point cloud removal unit 52 removes point clouds other than the target facilities that are not required for 3D modeling (for example, the walls and ground of a house). When the point cloud deletion is complete, the point cloud removal unit 52 overwrites the original point cloud in the storage medium 47 with the thinned point cloud data D9 (step S26).

[0036] The extraction processing unit 53 generates a 3D model using the thinned point cloud data overwritten on the storage medium 47 and inputs it to the GIS unit 54 (3D model data D10). The GIS unit 54 extracts corresponding image data from the storage medium 47 (image data D12). The GIS unit 54 superimposes the 3D model D10 and the image data D12 and inputs it to the information calculation unit 55 (data D13). The information calculation unit 55 calculates various equipment information (pole deflection, cable slack, etc.).

[0037] If the point cloud removal unit 51 or the point cloud removal unit 52 deletes the point cloud, the following problems occur when generating a three-dimensional model. As shown in Figure 1, the conventional technology creates a point cloud 10a and a scan line 20a in space Ar1, and references the GPS time of points one revolution later in the laser scanner's rotation to create them. The conventional technology uses this function to estimate the GPS time of points that will be one revolution later based on the laser scanner's rotation speed, and then searches for and connects points on the corresponding line axis 30 that are close to that time. If the scan line were to be deleted, there would be no points with GPS times one revolution later, and connection would be impossible using the conventional technology.

[0038] This problem will be explained in detail in Figure 9. Figure 9(A) shows the state of the point cloud before deletion, and Figure 9(B) shows the state of the point cloud after deletion. Tn (n is a natural number) is the GPS time, and the GPS time difference is s (T(n+1)-Tn=s).

[0039] Assume that the scan line 20 transitions as shown by GPS times (T1 to T6) (FIG. 9(A)). Now, assume that the points at GPS times T2 and T3 are deleted (FIG. 9(B)). In the prior art, since a point cloud is searched for s seconds later, if the scan line 20 at time T2 that follows the scan line 20 at time T1 is no longer present, the points cannot be connected. For this reason, in the prior art, only the points at times T4 to T6 are connected.

[0040] In the data compression device 50 of this embodiment, the point cloud removal units (51, 52) calculate the number of deleted scan lines, and the extraction processing unit 53 determines which points should be connected based on the calculated number of scan lines. For this reason, the data compression device 50 stores information on the number of deleted scan lines, and operates not to search for a point cloud having the deleted GPS time in order to connect the point at the time of interest with the point having GPS time information (number of deleted lines + 1) cycles later.

[0041] Specifically, the data compression device 50 has information that the point clouds at times T2 and T3 have been deleted, and understands that after time T1 it needs to search for the point cloud at time T4. That is, it searches for the point cloud s × (number of deleted scan lines 2 + 1) = 3s seconds later. As a result, the data compression device 50 can connect the point clouds at times T1 and T4, and can connect all the point clouds from times T1 to T6.

[0042] Therefore, the data compression device 50 can create pseudo scan lines and point clouds even after deleting the point clouds, thereby ensuring the accuracy of model creation.

[0043] The data compression device 50 includes at least one of a point cloud removal unit 51 and a point cloud removal unit 52.

[0044] (Embodiment 2) The data compression device 50 can also be realized by a computer and a program, and the program can be recorded on a recording medium or provided via a network. 10 shows a block diagram of a system 100. The system 100 includes a computer 105 connected to a network 135.

[0045] Network 135 is a data communications network. Network 135 may be a private or public network and may include any or all of the following: (a) a personal area network, e.g., covering a room; (b) a local area network, e.g., covering a building; (c) a campus area network, e.g., covering a campus; (d) a metropolitan area network, e.g., covering a city; (e) a wide area network, e.g., covering an area spanning city, region, or country boundaries; or (f) the Internet. Communications are conducted over network 135 by electronic and optical signals.

[0046] Computer 105 includes a processor 110 and memory 115 connected to processor 110. Although computer 105 is depicted herein as a stand-alone device, it is not limited to such, but rather may be connected to other devices not shown in a distributed processing system.

[0047] Processor 110 is an electronic device made up of logic circuits that responds to and carries out instructions.

[0048] The memory 115 is a tangible computer-readable storage medium on which a computer program is encoded. In this regard, the memory 115 stores data and instructions, i.e., program code, that can be read and executed by the processor 110 to control its operation. The memory 115 can be implemented as a random access memory (RAM), a hard drive, a read-only memory (ROM), or a combination thereof. One component of the memory 115 is a program module 120.

[0049] The program modules 120 contain instructions for controlling the processor 110 to perform the processes described herein. Although operations are described herein as being performed by the computer 105 or a method or process or sub-process thereof, those operations are actually performed by the processor 110.

[0050] The term "module" is used herein to refer to a functional operation that may be embodied as either a stand-alone component or an integrated configuration of multiple subcomponents. Thus, program module 120 may be implemented as a single module or as multiple modules operating in coordination with one another. Furthermore, although program module 120 is described herein as being installed in memory 115 and therefore implemented in software, it may be implemented in any of hardware (e.g., electronic circuitry), firmware, software, or a combination thereof.

[0051] Although program module 120 is shown as already loaded into memory 115, it may also be configured to reside on storage device 140 for later loading into memory 115. Storage device 140 is a tangible, computer-readable storage medium that stores program module 120. Examples of storage device 140 include compact discs, magnetic tape, read-only memory, optical storage media, a memory unit consisting of a hard drive or multiple parallel hard drives, and a universal serial bus (USB) flash drive. Alternatively, storage device 140 may be random access memory or another type of electronic storage device located in a remote storage system (not shown) and connected to computer 105 via network 135.

[0052] System 100 further includes data source 150A and data source 150B, collectively referred to herein as data sources 150, that are communicatively connected to network 135. In practice, data sources 150 may include any number of data sources, i.e., one or more data sources. Data sources 150 may include unstructured data and may include social media.

[0053] The system 100 further includes a user device 130 operated by the user 101 and connected to the computer 105 via a network 135. The user device 130 includes an input device, such as a keyboard or a voice recognition subsystem, that allows the user 101 to communicate information and command selections to the processor 110. The user device 130 also includes an output device, such as a display device or a printer or a voice synthesizer. A cursor control, such as a mouse, trackball, or touch-sensitive screen, allows the user 101 to manipulate a cursor on the display device to communicate further information and command selections to the processor 110.

[0054] The processor 110 outputs the results 122 of the execution of the program modules 120 to the user device 130. Alternatively, the processor 110 can provide the output to a storage device 125, such as a database or memory, or via a network 135 to a remote device not shown.

[0055] 6 or 8 may be the program module 120. The system 100 can be operated as the point cloud removal unit (51, 52) of the data compression device 50.

[0056] The terms "comprising" or "comprising" should be interpreted as specifying the presence of the stated features, integers, steps or components, but not excluding the presence of one or more other features, integers, steps or components or groups thereof. The terms "a" and "an" are indefinite articles and therefore do not exclude embodiments having a plurality thereof.

[0057] (Other embodiments) The present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit of the present invention. In short, the present invention is not limited to the above-described embodiment, and the components can be modified and embodied in the implementation stage without departing from the spirit of the present invention.

[0058] Furthermore, various inventions can be formed by appropriately combining the multiple components disclosed in the above embodiments. For example, some components may be omitted from all the components shown in the embodiments. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0059] 42: Camera 43: GPS receiver 44:IMU(Inertial Measurement Unit) 45: Odometer 46: Laser scanner 47:Storage medium 48: Arithmetic device 50: Data compression device 51, 52: Point cloud removal part 53: Extraction processing unit 54: GIS Department (Geographic Information System) 55: Information calculation unit 100: System 101:User 105: Computer 110: Processor 115: Memory 120: Program module 122:Result 125: Storage device 130: User device 135: Network 140: Storage device 150: Data source

Claims

1. A data compression device that compresses three-dimensional point cloud data representing three-dimensional coordinates of points on the surface of an outdoor structure, the three-dimensional point cloud data being acquired by a moving three-dimensional laser scanner, comprising: a point cloud removal unit that thins out the three-dimensional point cloud data according to an arbitrary criterion and calculates the number of scan lines deleted by thinning out the three-dimensional point cloud data; an extraction processing unit that creates a three-dimensional model from the three-dimensional point cloud data after thinning out so as not to search for the three-dimensional point cloud data that has been deleted based on the stored number of deleted scan lines; A data compression device comprising:

2. 2. The data compression device according to claim 1, wherein the arbitrary criterion of the point cloud removal unit is determined by the moving speed of the three-dimensional laser scanner.

3. 2. The data compression device according to claim 1, wherein the arbitrary criterion of the point cloud removal unit is a criterion determined based on the type of the outdoor structure.

4. A data compression method for compressing three-dimensional point cloud data representing three-dimensional coordinates of points on the surface of an outdoor structure, the three-dimensional point cloud data being acquired by a moving three-dimensional laser scanner, comprising: thinning the three-dimensional point cloud data according to an arbitrary criterion; Calculating the number of scan lines deleted by thinning out the three-dimensional point cloud data; and A three-dimensional model is created from the three-dimensional point cloud data after thinning so as not to search for the three-dimensional point cloud data deleted based on the stored number of deleted scan lines. A data compression method characterized by:

5. 5. The data compression method according to claim 4, wherein the arbitrary criterion is determined by the moving speed of the three-dimensional laser scanner.

6. 5. The data compression method according to claim 4, wherein the arbitrary criterion is a criterion determined based on the type of the outdoor structure.

7. A program for causing a computer to function as the data compression device according to any one of claims 1 to 3.

Images