Information processing device, information processing method, and computer program

Abstract

To suppress a user's workload with respect to generation of an irregular triangular network model.SOLUTION: An information processing method comprises: acquiring point group data representing a three-dimensional shape of a target area (S110); defining a plurality of sections in the target area (S120); creating an altitude map of the target area showing a representative altitude value of each section by setting a representative altitude value being one altitude value that represents a corresponding section on the basis of one group of coordinate points of the corresponding section shown by the point group data in each section with respect to a plurality of sections (S140); discriminating a change amount that is related to an altitude, as well as, to an adjacent section of the corresponding section in each section on the basis of the altitude map and discriminating a section whose change amount to the adjacent section is equal to or more than a reference amount as a change point (S150); and creating an irregular triangular network model with respect to a three-dimensional shape of the target area by using the change point as a constitution point (S170).SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to an information processing device and an information processing method. [Background technology]

[0002] In recent years, the use of 3D measurement data on the 3D shapes of landforms and other features has been promoted. 3D measurement data is point cloud data that describes the 3D coordinates of a huge number of points. Point clouds have density variations depending on the environment of the measurement site and the characteristics of the equipment.

[0003] Standard work methods and quality assessment methods have been established for the work of extracting topographic relief and feature shapes from 3D measurement data to create digital topographic map data. Changes in elevation of the topographic surface in digital topographic map data are known to be expressed by contour lines or digital topographic models, and one known digital topographic model is the Triangulated Irregular Network (TIN) model.

[0004] Attempts have been made to optimize and reduce the size of 3D measurement data from the viewpoints of the efficiency of calculation of huge amounts of 3D measurement data and standardization of point cloud variations, etc. Known processes for optimizing and reducing the size of 3D measurement data include a noise removal process that removes abnormally prominent elevation values ​​as noise, and a thinning process that equalizes the density of point clouds (see, for example, Patent Document 1).

[0005] When generating a digital terrain model, for example, a TIN model is generated by surveying CAD software using three-dimensional coordinate data of a point cloud extracted by executing the above-mentioned processing on three-dimensional measurement data.

[0006] However, TIN models automatically generated by conventional software often do not adequately represent the gradient changes of real terrain. In general, operators create digital topographical map data by determining the validity of the automatically generated TIN model, correcting the TIN model by setting breaklines, etc., or rearranging the constituent points of the TIN model manually or semi-automatically. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2005-024370 A Summary of the Invention [Problem to be solved by the invention]

[0008] As described above, the process of setting the constituent points of a TIN from 3D measurement data takes a long time. According to the conventional technology, the creation of a TIN model that optimally represents the gradient change of the terrain requires the setting of breaklines and other processes.

[0009] Therefore, according to one aspect of the present disclosure, it is desirable to provide a new technique that can reduce the workload of a user in generating a triangulated irregular network (TIN) model. [Means for solving the problem]

[0010] According to an aspect of the present disclosure, there is provided an information processing device including an acquisition unit, a partition definition unit, an elevation map generation unit, a discrimination unit, and a model generation unit, the acquisition unit being configured to acquire point cloud data representing a three-dimensional shape of a target area by a set of coordinate points in a three-dimensional coordinate system.

[0011] The partition definition unit is configured to define a plurality of partitions in the target area. The elevation map generation unit is configured to generate an elevation map of the target area indicating the representative elevation value for each partition by setting, for each partition, a representative elevation value that is one elevation value that represents the corresponding partition based on a group of coordinate points of the corresponding partition indicated by the point cloud data.

[0012] The discrimination unit is configured to determine, for each section, the amount of change in elevation of the corresponding section relative to the adjacent section by comparing the representative elevation value of the corresponding section with the representative elevation value of an adjacent section that is adjacent to the corresponding section based on the elevation map, and to discriminate sections in which the amount of change relative to the adjacent section is equal to or greater than a standard as change points.

[0013] The model generator is configured to generate a triangulated irregular network (TIN) model of the three-dimensional shape of the target region using the change points as configuration points.

[0014] According to this information processing device, it is possible to generate a good TIN model while reducing the workload on the user. Therefore, according to one aspect of the present disclosure, it is possible to provide a novel technique that can reduce the workload on the user in relation to the generation of a TIN model.

[0015] According to an aspect of the present disclosure, the partition definition unit may be configured to define the plurality of partitions by partitioning the target region into a grid along a horizontal plane. The plurality of partitions may be defined to be arranged at equal intervals.

[0016] By dividing the target area into equally spaced grid-like sections and setting a representative elevation value for each section, it is possible to reduce the effects of variations in point cloud density and generate an appropriate triangulated irregular network (TIN) model.

[0017] According to one aspect of the present disclosure, the elevation map generating unit may be configured to set, for each section, the lowest elevation value in the corresponding section as the representative elevation value of the corresponding section. Noise often occurs as an abnormally prominent elevation value, and noise rarely appears as a low elevation value. Therefore, by setting the lowest elevation value for each section as the representative elevation value, it is possible to generate a triangulated irregular network (TIN) model while suppressing the effect of noise contained in the point cloud data.

[0018] According to an aspect of the present disclosure, the discrimination unit may be configured to discriminate, as a change point, a section whose change amount with respect to an adjacent section is equal to or greater than a predetermined threshold value. By discriminating change points in this manner, it is possible to generate an appropriate triangulated irregular network (TIN) model without setting unnecessary configuration points and by reducing the number of configuration points.

[0019] According to one aspect of the present disclosure, the determination unit can be configured to determine the amount of change by calculating the difference between the representative elevation value of the corresponding section and the representative elevation value of the adjacent section as the amount of change.

[0020] According to one aspect of the present disclosure, the partition definition unit may be configured to define a plurality of partitions by partitioning the target area in a grid pattern along a horizontal plane in a first direction and a second direction perpendicular to the first direction.

[0021] The discrimination unit may discriminate a section whose amount of change in elevation relative to an adjacent section in a first direction is equal to or greater than a reference value as a first change point, and may discriminate a section whose amount of change in elevation relative to an adjacent section in a second direction is equal to or greater than a reference value as a second change point. The model generation unit may be configured to generate a triangulated irregular network (TIN) model using the first change point and the second change point as constituent points.

[0022] By setting the configuration points in this manner, it is possible to generate a triangulated irregular network (TIN) model that appropriately captures the undulations in the first and second directions.

[0023] According to an aspect of the present disclosure, a computer program may be provided for causing a computer to function as at least a part of the acquisition unit, the partition definition unit, the elevation map generation unit, the discrimination unit, and the model generation unit in the above-mentioned information processing device. The computer program may be recorded in a computer-readable recording medium. According to an aspect of the present disclosure, an information processing method corresponding to the above-mentioned information processing device may be provided.

[0024] According to an aspect of the present disclosure, there may be provided an information processing method executed by a computer, the information processing method may include acquiring point cloud data representing a three-dimensional shape of a target area by a set of coordinate points in a three-dimensional coordinate system.

[0025] The information processing method may further include defining a plurality of partitions in the target area. The information processing method may further include generating an elevation map of the target area indicating the representative elevation value for each partition by setting, for each partition, a representative elevation value that is one elevation value representative of the corresponding partition based on a group of coordinate points of the corresponding partition indicated by the point cloud data.

[0026] The information processing method may further include, for each section, determining the amount of change in elevation of the corresponding section relative to the adjacent section by comparing the representative elevation value of the corresponding section with the representative elevation value of an adjacent section that is adjacent to the corresponding section based on the elevation map, and determining as a change point a section in which the amount of change relative to the adjacent section is equal to or greater than a standard.

[0027] The information processing method may further include generating a triangulated irregular network (TIN) model for the three-dimensional shape of the target region using the change points as constituent points. According to this information processing method, it is possible to reduce the workload of a user in generating the triangulated irregular network (TIN) model. [Brief description of the drawings]

[0028] [Figure 1] FIG. 1 is a block diagram illustrating a configuration of an information processing device. [Diagram 2] 11 is a flowchart showing TIN-related processing executed by a processor. [Diagram 3] FIG. 1 is an explanatory diagram regarding partitioning of a target region. [Figure 4] 11 is a flowchart showing a change point determination process executed by a processor. [Diagram 5] FIG. 1 is a diagram conceptually explaining a TIN model having gradient change points as component points. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0029] Exemplary embodiments of the present disclosure will now be described with reference to the drawings. 1 is configured to generate a triangulated irregular network (TIN) model from three-dimensional measurement data relating to features such as topography. The information processing device 10 includes a processor 11, a memory 13, a storage 15, a display unit 17, an operation unit 18, and a data input / output unit 19.

[0030] The processor 11 generates a TIN model by executing processing in accordance with a computer program stored in the storage 15. The memory 13 includes a RAM, and is used as a working memory when the processor 11 executes processing.

[0031] The storage 15 includes a hard disk drive and / or a solid state drive, and stores computer programs and data used when executing processes according to the computer programs. The computer programs stored in the storage 15 include a computer program for generating a TIN model from three-dimensional measurement data.

[0032] The display unit 17 is controlled by the processor 11 and configured to display various information to a user who operates the information processing device 10. An example of the display unit 17 is a liquid crystal display. The operation unit 18 is configured to input an operation signal from the user to the information processing device 10 to the processor 11. An example of the operation unit 18 is a keyboard and a pointing device.

[0033] The data input / output unit 19 is configured to be capable of inputting and outputting data to and from an external device. The data input / output unit 19 may include a communication interface capable of communicating with an external device via wired or wireless communication. The data input / output unit 19 may include a USB interface capable of reading and writing data to a USB memory, and / or a media reader / writer capable of reading and writing data to a card-type recording medium.

[0034] In this information processing device 10, when a command to generate a TIN model is input by the user via the operation unit 18, the processor 11 executes the TIN-related processing shown in FIG. 2 in accordance with a computer program, thereby generating a TIN model based on the three-dimensional measurement data specified by the user.

[0035] 2 is started, the processor 11 acquires the three-dimensional measurement data specified by the user when the generation command is input (S110). The three-dimensional measurement data can be generated using technologies such as a terrestrial laser scanner (TLS), a mobile mapping system (MMS), a survey drone (unmanned aerial vehicle, UAV), and SLAM (simultaneous localization and mapping). The generated three-dimensional measurement data is input in advance to the information processing device 10 via the data input / output unit 19 and stored in the storage 15.

[0036] The acquired three-dimensional measurement data is three-dimensional point cloud data that represents the three-dimensional shape of features such as the topography in the target area using a point cloud. The three-dimensional measurement data describes each measurement point using three-dimensional coordinates. Here, the XYZ coordinate system having an X-axis, a Y-axis, and a Z-axis is used as the three-dimensional coordinate system. In other words, the three-dimensional coordinates of each measurement point that constitutes the point cloud are expressed in XYZ coordinates.

[0037] The XY plane corresponds to the horizontal plane, and the Z axis corresponds to the height direction from the horizontal plane. In what follows, each point that makes up the point cloud in the three-dimensional coordinate system will be referred to as a coordinate point. In other words, three-dimensional measurement data represents the three-dimensional shape of the target area by a set of coordinate points in the three-dimensional coordinate system.

[0038] In S110, the processor 11 reads the specified three-dimensional measurement data from the storage 15, thereby obtaining the three-dimensional measurement data.

[0039] In the next step S120, the processor 11 sets a rectangular region on the XY plane that includes all of the points located on the XY plane when the points represented by the three-dimensional measurement data are orthogonally projected onto the XY plane as the target region, and partitions the target region into a grid pattern. Through this partitioning, the processor 11 defines a plurality of partitions in the target region that are arranged at equal intervals in the X-axis direction and in the Y-axis direction perpendicular to the X-axis direction.

[0040] 3, the processor 11 can partition the target area into a grid by dividing the target area in the X-axis direction and the Y-axis direction at preset intervals. Each partition can be, for example, a square partition with one side being 1 meter wide.

[0041] The shape and size of the plots are not limited to these and may be square plots with sides of 30 centimeters, 50 centimeters, or 2 meters wide, or may be rectangular plots. The plot size depends, for example, on the accuracy of the TIN model required.

[0042] In the next step S130, the processor 11 generates an elevation value list for each partition of the target area based on the three-dimensional measurement data. The elevation value list is data that describes, as an elevation value, the Z coordinate of each coordinate point indicated by the three-dimensional measurement data for a group of coordinate points located in the corresponding partition.

[0043] The elevation value list may describe elevation values ​​of all coordinate points within a corresponding block along with the block ID of the corresponding block. The block ID may be a unique identification code assigned to each block when the target area is divided.

[0044] In the next step S140, the processor 11 sets the representative elevation value of each section in the target area based on the elevation value list of the corresponding section, and generates an elevation map. The elevation map is data describing the representative elevation value of each section in the target area.

[0045] In S140, the processor 11 can treat the coordinate point showing the lowest elevation value in the corresponding section as the representative point and set the representative elevation value to the elevation value of the representative point. Coordinate points corresponding to noise included in the three-dimensional measurement data often show elevation values ​​higher than the correct elevation value. Therefore, by setting the representative elevation value to the lowest elevation value, it is highly likely that the representative elevation value can be set without referring to the coordinate points of noise in the section.

[0046] In the next step S150, processor 11 executes the change point determination process shown in Fig. 4. When the change point determination process starts, processor 11 selects a row to be processed in the target area (S210). Here, a group of partitions arranged in the X-axis direction in the target area is referred to as a row, and a group of partitions arranged in the Y-axis direction is referred to as a column. Processor 11 can sequentially select rows to be processed by repeating the process of S210.

[0047] After the row to be processed is selected in S210, in the next step S220, processor 11 selects a partition to be processed from the row to be processed. By repeating the process of S220, processor 11 can select partitions to be processed in sequence in one direction along the X-axis direction from the group of partitions corresponding to the row to be processed.

[0048] When the processing target partition is selected in S220, the processor 11 calculates the amount of gradient change between the processing target partition and an X-direction adjacent partition that is adjacent to the processing target partition in the X-axis direction (S230).

[0049] For example, processor 11 can calculate the gradient change amount by treating a partition adjacent to the partition to be processed in the selection direction as an X-direction adjacent partition, or by treating a partition adjacent to the partition to be processed in the direction opposite to the selection direction as an X-direction adjacent partition.

[0050] When the representative elevation value of the section to be processed is Z1 and the representative elevation value of the adjacent section in the X direction is Z2, the processor 11 can calculate the absolute value of the difference between the elevation values ​​Z1 and Z2, |Z1-Z2| (Z=|Z1-Z2|), as the gradient change amount Z. In this way, the processor 11 compares the representative elevation value of the section to be processed with the representative elevation value of the adjacent section, thereby determining the gradient change amount Z of the section to be processed relative to the adjacent section as the change in elevation.

[0051] In the next step S240, processor 11 determines whether the gradient change amount is equal to or greater than a preset threshold. If processor 11 determines that the gradient change amount is equal to or greater than the threshold (Yes in S240), processor 11 determines in the next step S250 that the processing target section is a gradient change point in the X-axis direction. Then, the processing of S260 is executed.

[0052] If the processor 11 determines that the gradient change amount is less than the threshold value (No in S240), it proceeds to the process of S260 without executing the process of S250, that is, without determining that the processing target section is a gradient change point.

[0053] According to this embodiment, when there is no adjacent partition in the X direction corresponding to the partition to be processed, the processor 11 can determine that the gradient change amount is zero and make a negative determination in S240.

[0054] In S260, processor 11 determines whether or not the partition located at the end of the X-axis direction in the target row has been selected as the target partition. In other words, processor 11 determines whether or not all partitions constituting the target row have been selected as the target partition. If the determination in S260 is negative, processor 11 returns to the process of S220 and switches the target partition to the next partition in the target row. Processor 11 then executes the processes from S230 onward for the new target partition.

[0055] If the determination in S260 is affirmative, processor 11 determines whether or not all rows have been selected as rows to be processed (S270). If it is determined that no rows have been selected (No in S270), processor 11 returns to the process of S210 and switches the row to be processed to the next row. After that, processor 11 executes the processes from S220 onward for the new row to be processed.

[0056] If it is determined in S270 that all rows have been selected as rows to be processed (Yes in S270), then in S310, processor 11 selects columns to be processed. Processor 11 can sequentially select columns to be processed by repeating the process of S310.

[0057] After the column to be processed is selected in S310, in the following S320, processor 11 selects a partition to be processed from the column to be processed. By repeating the process of S320, processor 11 can select the partition to be processed in sequence in one direction along the Y-axis direction from the group of partitions corresponding to the column to be processed.

[0058] When the processing target section is selected in S320, the processor 11 calculates the amount of gradient change between the processing target section and a Y-direction adjacent section that is an adjacent section in the Y-axis direction to the processing target section (S330).

[0059] For example, processor 11 can calculate the amount of gradient change by treating a partition adjacent to the partition to be processed in the selection direction as the Y-direction adjacent partition. Alternatively, processor 11 can calculate the amount of gradient change by treating a partition adjacent to the partition to be processed in the direction opposite to the selection direction of the partition to be processed as the Y-direction adjacent partition. Processor 11 can calculate, as the amount of gradient change, the absolute value of the difference between the elevation value of the partition to be processed and the elevation value of the adjacent partition in the Y direction, as in the process at S230.

[0060] In the next step S340, processor 11 determines whether the amount of gradient change is equal to or greater than a preset threshold. If processor 11 determines that the amount of gradient change is equal to or greater than the threshold (Yes in S340), processor 11 determines in the next step S350 that the section to be processed is a gradient change point in the Y-axis direction. Then, processor 11 executes the process of S360. If processor 11 determines that the amount of gradient change is less than the threshold (No in S340), processor 11 executes the process of S360 without executing the process of S350.

[0061] If there is no adjacent section in the Y direction corresponding to the section to be processed, the processor 11 can determine that the gradient change amount is zero and make a negative determination in S340.

[0062] In S360, processor 11 determines whether or not the section located at the end of the processing target column in the Y-axis direction has been selected as the processing target section. In other words, processor 11 determines whether or not all of the sections constituting the processing target column have been selected as the processing target section. If the determination in S360 is negative, processor 11 returns to the processing of S320 and switches the processing target section to the next section in the processing target column. After that, processor 11 executes the processing from S330 onwards.

[0063] If the determination in S360 is affirmative, processor 11 determines whether or not all columns have been selected as columns to be processed (S370). If it is determined that all columns have not been selected (No in S370), processor 11 returns to the process of S310 and switches the column to be processed to the next column. After that, processor 11 executes the processes from S320 onward for the new column to be processed.

[0064] When processor 11 determines in S370 that all columns have been selected as processing examples (Yes in S370), it ends the change point determination process. In this manner, in the change point determination process, sections corresponding to gradient change points are determined in the X-axis direction and the Y-axis direction.

[0065] 4 is completed (S150), the processor 11 generates change point group data describing the three-dimensional coordinates of each change point for the group of change points in the next S160 (see FIG. 2). The group of change points here includes a group of gradient change points in the X-axis direction and a group of gradient change points in the Y-axis direction.

[0066] In the change point cloud data, for each change point, the representative elevation value of the section in which the corresponding change point is located is described as the Z coordinate as the three-dimensional coordinate of the corresponding change point, and the center coordinates of the corresponding section are described as the XY coordinate. According to another example, in the change point cloud data, for each change point, the XYZ coordinates of the representative point corresponding to the representative elevation value of the corresponding section may be described as the three-dimensional coordinate of the corresponding change point.

[0067] When generating the change point cloud data, the processor 11 can also regard the four sections corresponding to the four corners of the target area as gradient change points, and describe the three-dimensional coordinates of the corresponding gradient change points in the change point cloud data.

[0068] In the following S170, the processor 11 generates a TIN model based on the change point group data generated in S160. The generated TIN model is a TIN model that has each of the change points as one component point.

[0069] That is, the processor 11 uses the change points as constituent points to generate a TIN model for the three-dimensional shape of the target area. An existing program module may be used to generate the TIN model. FIG. 5 conceptually illustrates an example of the TIN model generated in S170.

[0070] In the following S180, the processor 11 outputs the TIN model generated in S170. The processor 11 can record the TIN model as a data file in the storage 15. The processor 11 can output the TIN model as an image to the user via the display unit 17. Thereafter, the processor 11 ends the TIN-related processing shown in FIG.

[0071] According to the information processing device 10 of the present embodiment described above, by setting the representative elevation value for each section as described above and extracting gradient change points, it is possible to remove noise contained in the three-dimensional measurement data and convert the three-dimensional measurement data into change point cloud data so as to appropriately thin out the point cloud represented by the three-dimensional measurement data.

[0072] Therefore, according to this embodiment, it is possible to reduce the amount of time required for manual point cloud thinning and noise removal, which has conventionally been required as preparatory work for generating a TIN model.

[0073] According to this embodiment, by generating change point cloud data using the above method, it is possible to suppress the loss of information on characteristic points related to gradient changes, reduce the point cloud density, and generate an appropriate TIN model. For example, according to this embodiment, even unevenness with a gradient change in a certain direction can be identified as a gradient change point, and a TIN model suitable for creating a topographical map can be generated.

[0074] In this way, the information processing device 10 of the present embodiment can generate an appropriate TIN model while reducing the workload of the user caused by manual work.

[0075] In other words, the information processing device 10 can be configured to change the threshold value and the block size according to an instruction from the user inputted through the operation unit 18. According to this configuration, the user can construct a TIN model that satisfies the required accuracy by adjusting the threshold value used to distinguish the gradient change point and adjusting the block size.

[0076] [Other embodiments] The present disclosure is not limited to the above-described embodiment, and can adopt various aspects. For example, in the above embodiment, the target area is partitioned into a grid pattern. However, the target area may be partitioned only in the X-axis direction or the Y-axis direction. The partitions do not have to be square or rectangular, and may be triangular or polygonal with more than one side. The partitions do not have to be defined at equal intervals.

[0077] The representative elevation value does not have to be the minimum elevation value of the corresponding section, and may be a statistical quantity such as the average or median of the elevation values ​​in the corresponding section.

[0078] The function of one component in the above embodiments may be distributed among multiple components. The functions of multiple components may be integrated into one component. Part of the configuration of the above embodiments may be omitted. At least part of the configuration of the above embodiments may be added to or substituted for the configuration of another of the above embodiments. All aspects included in the technical idea identified from the wording of the claims are embodiments of the present disclosure.

[0079] [Technical idea disclosed in this specification] It can be understood that the present specification discloses the following technical ideas. [Item 1] an acquisition unit configured to acquire point cloud data representing a three-dimensional shape of a target area by a set of coordinate points in a three-dimensional coordinate system; a partition definition unit configured to define a plurality of partitions in the target region; an elevation map generating unit configured to generate an elevation map of the target area indicating the representative elevation value for each of the plurality of partitions by setting, for each partition, a representative elevation value that is one elevation value that represents the corresponding partition based on a group of coordinate points of the corresponding partition indicated by the point cloud data; a discrimination unit configured to, for each of the sections, determine an amount of change in elevation of the corresponding section relative to the adjacent section by comparing the representative elevation value of the corresponding section with the representative elevation value of an adjacent section that is adjacent to the corresponding section based on the elevation map, and to discriminate a section in which the amount of change relative to the adjacent section is equal to or greater than a reference value as a change point; a model generator configured to generate a triangulated irregular network (TIN) model of the three-dimensional shape of the target region using the change points as configuration points; An information processing device comprising: [Item 2] 2. The information processing device according to item 1, wherein the partition definition unit defines a plurality of partitions arranged at equal intervals as the plurality of partitions by partitioning the target area into a lattice shape along a horizontal plane. [Item 3] 3. The information processing device according to item 1 or 2, wherein the elevation map generating unit sets, for each of the partitions, the lowest elevation value in the corresponding partition as the representative elevation value of the corresponding partition. [Item 4] 4. The information processing device according to any one of items 1 to 3, wherein the discrimination unit discriminates, as the change point, a section in which the amount of change with respect to the adjacent section is equal to or greater than a predetermined threshold value. [Item 5] 5. The information processing device according to any one of items 1 to 4, wherein the discrimination unit discriminates the amount of change by calculating a difference between a representative elevation value of the corresponding section and a representative elevation value of the adjacent section as the amount of change. [Item 6] the partition definition unit defines the plurality of partitions by partitioning the target area in a lattice shape along a horizontal plane in a first direction and a second direction perpendicular to the first direction; the discrimination unit discriminates a section in which an amount of change in altitude relative to an adjacent section in the first direction is equal to or greater than a reference value as a first change point, and discriminates a section in which an amount of change in altitude relative to an adjacent section in the second direction is equal to or greater than a reference value as a second change point; 2. The information processing device according to item 1, wherein the model generation unit is configured to generate the triangulated irregular network (TIN) model by using the first change point and the second change point as constituent points. [Item 7] A computer program for causing a computer to function as the acquisition unit, the partition definition unit, the elevation map generation unit, the discrimination unit, and the model generation unit in the information processing device according to any one of items 1 to 6. [Item 8] 1. A computer-implemented information processing method, comprising: Obtaining point cloud data that represents a three-dimensional shape of a target area by a set of coordinate points in a three-dimensional coordinate system; defining a plurality of zones in the region of interest; generating an elevation map of the target area showing the representative elevation value for each of the plurality of partitions by setting, for each partition, a representative elevation value that is one elevation value that represents the corresponding partition based on a group of coordinate points of the corresponding partition indicated by the point cloud data; based on the elevation map, for each of the sections, comparing the representative elevation value of the corresponding section with the representative elevation value of an adjacent section that is adjacent to the corresponding section to determine an amount of change in elevation of the corresponding section relative to the adjacent section, and determining a section in which the amount of change relative to the adjacent section is equal to or greater than a standard as a change point; generating a triangulated irregular network (TIN) model of the three-dimensional shape of the target region using the change points as configuration points; An information processing method comprising: [Explanation of symbols]

[0080] 10...information processing device, 11...processor, 13...memory, 15...storage, 17...display unit, 18...operation unit, 19...data input / output unit.

Claims

1. an acquisition unit configured to acquire point cloud data representing a three-dimensional shape of a target area by a set of coordinate points in a three-dimensional coordinate system; a partition definition unit configured to define a plurality of partitions in the target region; an elevation map generating unit configured to generate an elevation map of the target area indicating the representative elevation value for each of the plurality of partitions by setting, for each partition, a representative elevation value that is one elevation value that represents the corresponding partition based on a group of coordinate points of the corresponding partition indicated by the point cloud data; a discrimination unit configured to, for each of the sections, determine an amount of change in elevation of the corresponding section relative to the adjacent section by comparing the representative elevation value of the corresponding section with the representative elevation value of an adjacent section that is adjacent to the corresponding section based on the elevation map, and to discriminate a section in which the amount of change relative to the adjacent section is equal to or greater than a reference value as a change point; a model generator configured to generate a triangulated irregular network (TIN) model for a three-dimensional shape of the target region using the change points as configuration points; An information processing device comprising:

2. The information processing apparatus according to claim 1 , wherein the partition definition unit defines, as the plurality of partitions, a plurality of partitions arranged at equal intervals by partitioning the target area into a lattice shape along a horizontal plane.

3. The information processing apparatus according to claim 1 , wherein the elevation map generating section sets, for each of the sections, the lowest elevation value in the corresponding section as the representative elevation value of the corresponding section.

4. The information processing apparatus according to claim 1 , wherein the determining unit determines, as the change point, a section in which the amount of change with respect to the adjacent section is equal to or greater than a predetermined threshold value.

5. The information processing apparatus according to claim 1 , wherein the determining unit determines the amount of change by calculating a difference between the representative elevation value of the corresponding section and the representative elevation value of the adjacent section as the amount of change.

6. the partition definition unit defines the plurality of partitions by partitioning the target area in a lattice shape along a horizontal plane in a first direction and a second direction perpendicular to the first direction; the discrimination unit discriminates a section in which an amount of change in altitude relative to an adjacent section in the first direction is equal to or greater than a reference value as a first change point, and discriminates a section in which an amount of change in altitude relative to an adjacent section in the second direction is equal to or greater than a reference value as a second change point; The information processing apparatus according to claim 1 , wherein the model generating unit is configured to generate the triangulated irregular network (TIN) model by using the first change points and the second change points as constituent points.

7. A computer program for causing a computer to function as the acquisition unit, the partition definition unit, the elevation map generation unit, the discrimination unit, and the model generation unit in an information processing device according to any one of claims 1 to 6.

8. 1. A computer-implemented information processing method, comprising: Obtaining point cloud data that represents a three-dimensional shape of a target area by a set of coordinate points in a three-dimensional coordinate system; defining a plurality of zones in the region of interest; generating an elevation map of the target area showing the representative elevation value for each of the plurality of partitions by setting, for each partition, a representative elevation value that is one elevation value that represents the corresponding partition based on a group of coordinate points of the corresponding partition indicated by the point cloud data; based on the elevation map, for each of the sections, comparing the representative elevation value of the corresponding section with the representative elevation value of an adjacent section that is adjacent to the corresponding section to determine an amount of change in elevation of the corresponding section relative to the adjacent section, and determining a section in which the amount of change relative to the adjacent section is equal to or greater than a standard as a change point; generating a triangulated irregular network (TIN) model of the three-dimensional shape of the target region using the change points as configuration points; An information processing method comprising:

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