Data processing system, data processing method, and data processing program

Abstract

To enable easy extraction of point cloud data for a target object from point cloud data that includes surrounding objects, etc. [Solution] The data processing system 100 decomposes the point cloud data in the original data, which includes point cloud data obtained by a positioning device 16 that measures the position of reflection points by irradiating a target area with light and receiving the reflected light reflected at the reflection points, and image data of the target area in which each point data constituting the point cloud data is associated with a pixel, into separate point cloud data for each object present in the target area, and generates decomposed data which is point cloud data for each object. The data processing system 100 identifies the decomposed data for a specified object from the decomposed data for each object, and the partial data consisting of pixels from the image data included in the original data that are associated with the decomposed data for the specified object.

Description

Technical Field

[0001] This disclosure relates to a technique for handling three-dimensional point cloud data.

Background Art

[0002] Three-dimensional point cloud data of an object is obtained using a positioning device such as a LiDAR camera. LiDAR is an abbreviation for Light Detection And Ranging. For example, Patent Document 1 describes obtaining point cloud data by a positioning device and measuring the size of an object.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When point cloud data is obtained by a positioning device, point cloud data of the entire space irradiated with light is obtained. That is, not only the object for which point cloud data is desired, but also surrounding objects, the floor, the wall, etc. have their point cloud data obtained. It is conceivable to consider the layout when the object is placed in another location using the point cloud data of the object. However, in order to extract the point cloud data of the object from the point cloud data including surrounding objects, etc., it is necessary to perform processing and cutting using dedicated software, which is time-consuming. An object of this disclosure is to enable easy extraction of point cloud data of an object from point cloud data including surrounding objects, etc.

Means for Solving the Problems

[0005] The data processing system according to this disclosure is A positioning device that measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and a decomposition unit that decomposes the point cloud data in the original data, which includes point cloud data obtained by a positioning device that measures the position of the reflection point by irradiating the target area with light and receiving the reflected light reflected at the reflection point, into object-specific point cloud data for each object present in the target area, and generates decomposed data which is decomposed data for each object. A correspondence data identification unit identifies the decomposition data for a specified object from the decomposition data for each object generated by the decomposition unit, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object. It is equipped with. [Effects of the Invention]

[0006] In this disclosure, the original data, which is point cloud data obtained by a positioning device, is decomposed for each object present in the target area to generate decomposed data, which is point cloud data for each object. Then, partial data consisting of pixels associated with the decomposed data for a specified object is identified. This yields point cloud data for the specified object and partial data for the specified object from the image data. [Brief explanation of the drawing]

[0007] [Figure 1] Configuration diagram of the data processing system 100 according to Embodiment 1. [Figure 2] A diagram showing the configuration of the data processing device 10 according to Embodiment 1. [Figure 3] Flowchart of the data registration process according to Embodiment 1. [Figure 4] Flowchart of the data extraction process according to Embodiment 1. [Figure 5] Diagram illustrating the disassembly process according to Embodiment 1. [Figure 6] Flowchart of the data editing process according to Embodiment 1. [Figure 7] An explanatory diagram illustrating an example of the use of the data processing system 100 according to Embodiment 1. [Figure 8] Explanatory diagram of the data structure of the original data 51 and the decomposed data according to Embodiment 1. [Figure 9] Configuration diagram of the data processing system 100 according to Embodiment 2. [Figure 10] Configuration diagram of the data processing device 10 according to Embodiment 2. [Figure 11] Configuration diagram of the imaging device 20 according to Embodiment 2. [Figure 12] Configuration diagram of the operation terminal 30 according to Embodiment 2. [Figure 13] Flowchart of the data registration process according to Embodiment 2. [Figure 14] Flowchart of the data extraction process according to Embodiment 2. [Figure 15] Flowchart of the data editing process according to Embodiment 2.

Mode for Carrying Out the Invention

[0008] Embodiment 1. ***Explanation of the Configuration*** Referring to FIG. 1, the configuration of the data processing system 100 according to Embodiment 1 will be described. The data processing system 100 according to Embodiment 1 includes a data processing device 10. In Embodiment 1, the data processing device 10 is a computer such as a smartphone or a tablet terminal.

[0009] Referring to FIG. 2, the configuration of the data processing device 10 according to Embodiment 1 will be described. The data processing device 10 is a computer. The data processing device 10 includes hardware such as a processor 11, a memory 12, a storage 13, a communication interface 14, a camera 15, a positioning device 16, and a display device 17. The processor 11 is connected to other hardware via signal lines and controls these other hardware.

[0010] Processor 11 is an IC that performs processing. IC is an abbreviation for Integrated Circuit. As specific examples, processor 11 is a CPU, DSP, or GPU. CPU is an abbreviation for Central Processing Unit. DSP is an abbreviation for Digital Signal Processor. GPU is an abbreviation for Graphics Processing Unit.

[0011] Memory 12 is a storage device that temporarily stores data. As specific examples, memory 12 is SRAM or DRAM. SRAM is an abbreviation for Static Random Access Memory. DRAM is an abbreviation for Dynamic Random Access Memory.

[0012] Storage 13 is a storage device that stores data. As a specific example, storage 13 is an SSD. SSD is an abbreviation for Solid State Drive. Also, storage 13 may be a removable recording medium such as an SD (registered trademark) memory card, CompactFlash (registered trademark), NAND flash, flexible disk, optical disk, compact disk, Blu-ray (registered trademark) disk, or DVD. SD is an abbreviation for Secure Digital. DVD is an abbreviation for Digital Versatile Disk.

[0013] Communication interface 14 is an interface for communicating with an external device. As specific examples, communication interface 14 is a port for Ethernet (registered trademark), USB, or HDMI (registered trademark). USB is an abbreviation for Universal Serial Bus. HDMI is an abbreviation for High-Definition Multimedia Interface.

[0014] Camera 15 is a photographing device such as an optical camera for acquiring image data.

[0015] The positioning device 16 is a device that measures the position of a reflection point by irradiating a target area with light and receiving the reflected light that is reflected at the reflection point.

[0016] The display device 17 is a device such as an LCD for displaying information. LCD stands for Liquid Crystal Display.

[0017] The data processing device 10 comprises, as functional components, an imaging unit 111, a measurement unit 112, a decomposition unit 113, a display unit 114, a designation reception unit 115, a corresponding data identification unit 116, a data extraction unit 117, and an editing unit 118. The functions of each functional component of the data processing device 10 are implemented by software. The storage 13 stores programs that implement the functions of each functional component of the data processing device 10. These programs are loaded into the memory 12 by the processor 11 and executed by the processor 11. This enables the implementation of the functions of each functional component of the data processing device 10.

[0018] In Figure 2, only one processor 11 was shown. However, there may be multiple processors 11, and multiple processors 11 may work together to execute programs that implement each function.

[0019] ***Explanation of operation*** Referring to Figures 3 to 8, the operation of the data processing system 100 according to Embodiment 1 will be described. The operation procedure of the data processing system 100 according to Embodiment 1 corresponds to the data processing method according to Embodiment 1. Furthermore, the program that implements the operation of the data processing system 100 according to Embodiment 1 corresponds to the data processing program according to Embodiment 1.

[0020] The operation of the data processing system 100 includes data registration processing, data extraction processing, and data editing processing. The data registration process involves acquiring image data and point cloud data for the target area and registering them as source data 51. The data extraction process involves identifying image data and point cloud data for a specified object from the source data 51 and extracting them as editing data 52. The data editing process involves performing editing using the editing data 52.

[0021] Referring to Figure 3, the data registration process according to Embodiment 1 will be explained. (Step S11: Image capture process) The shooting unit 111 uses the camera 15 to capture images of the target area and acquires image data of the target area. In this case, the user may acquire multiple image data of the target area by shooting a video of the target area while moving the data processing device 10.

[0022] (Step S12: Measurement process) Simultaneously with the image capture in step S11, the measurement unit 112 uses the positioning device 16 to illuminate the target area with illumination light and receives the reflected light from the reflection points to measure the position of the reflection points. As a result, the measurement unit 112 acquires point cloud data indicating the positions of multiple reflection points in the target area.

[0023] (Step S13: Registration process) The measurement unit 112 associates each pixel of one or more image data acquired in step S11 with each point data of the point cloud data acquired in step S12. Then, the measurement unit 112 writes the associated point cloud data and image data to the storage 13 as source data 51. Matching each pixel of image data with each point in point cloud data means that pixels and point data corresponding to the same location are associated. By simultaneously acquiring image data and point cloud data, it is possible to match pixels and point data for the same location.

[0024] Referring to Figure 4, the data extraction process according to Embodiment 1 will be described. (Step S21: Processing of processing requests) The decomposition unit 113 receives a processing request for the original data 51. If multiple original data 51 are stored in the storage 13, it receives a processing request that includes specifying the original data 51 to be processed. At this time, the system may be configured to display multiple original data 51 and accept selection from the user.

[0025] (Step S22: Disassembly process) The decomposition unit 113 sets the source data 51 specified in step S21 as the source data 51 to be processed. The decomposition unit 113 decomposes the point cloud data in the source data 51 to be processed into objects present in the target region and generates decomposed data, which is point cloud data for each object. The decomposition unit 113 registers the decomposed data in the storage 13, associating it with the source data 51. For example, as shown in Figure 5, suppose objects A, B, and C exist in the target area. In this case, the decomposition unit 113 detects each of objects A, B, and C in the target area and decomposes the point cloud data into object A, object B, object C, and other elements (floor, walls, etc.). This generates decomposed data, which is the point cloud data of object A, decomposed data, which is the point cloud data of object B, and decomposed data, which is the point cloud data of object C.

[0026] Specifically, the decomposition unit 113 removes floor and wall point data from the point cloud data. Using existing techniques for estimating surfaces, the decomposition unit 113 can identify floor and wall areas. The decomposition unit 113 clusters the remaining point data using a rule-based method based on the distance between objects. The decomposition unit 113 can cluster the remaining point data using methods such as X-means. The decomposition unit 113 obtains each point cloud data separated by clustering as logically decomposed data. Alternatively, the decomposition unit 113 recognizes an object using a learning model generated by deep learning, and converts each point cloud into decomposed data that is logically separated. Furthermore, the disassembly unit 113 also includes disassembly data in which the removed floor and wall sections have been logically broken down. Here, logical decomposition refers to a state where each point data is assigned a label that allows it to be identified as the decomposed data, which is the point cloud data for each object. Subsequently, the disassembly unit 113 generates a physically disassembled OBJ file from the logically disassembled disassembly data. The OBJ file will be described later.

[0027] (Step S23: Display process) The display unit 114 displays the original data 51 specified in step S21 on the display device 17. Specifically, the display unit 114 pastes the image data contained in the source data 51, aligning it with the position of each point in the point cloud data contained in the source data 51. This combines the image data with the point cloud data, generating a 3D model of the target region. The display unit 114 then displays this 3D model of the target region.

[0028] (Step S24: Designated reception processing) The designation reception unit 115 accepts the designation of one or more objects to be processed from among the objects included in the 3D model displayed in step S23. For example, the object to be processed is designated by touching the object to be processed. In this case, the designated request unit 115 also accepts a specification of whether the request is a cut request, which cuts and extracts data from a designated object, or a delete request, which deletes data from a designated object and extracts the remaining data.

[0029] (Step S25: Corresponding data identification process) The corresponding data identification unit 116 identifies the decomposed data for the specified object specified in step S24 from the decomposed data generated in step S22. The corresponding data identification unit 116 can identify the decomposed data for the specified object by identifying the decomposed data that includes the point data of the touched position. Furthermore, the corresponding data identification unit 116 identifies partial data consisting of pixels associated with the decomposed data of a specified object among the image data included in the original data to be processed.

[0030] (Step S26: Extraction process) The data extraction unit 117 extracts editing data 52 from the decomposed data and partial data of the specified object identified in step S25. The data extraction unit 117 determines in step S24 whether a cut request or a delete request was specified. If a cut request is specified, the data extraction unit 117 extracts the decomposed data and partial data of the specified object as editing data 52. If a delete request is specified, the data extraction unit 117 extracts the data excluding the decomposed data and partial data of the specified object from the original data 51 as editing data 52. Here, if the decomposed data is excluded from the point cloud data included in the original data 51, the point data in the area where the decomposed data was located will be missing. The data extraction unit 117 may fill in the missing point data using the point data of the walls and floor. Specifically, the data extraction unit 117 may extend the walls and floor assuming that they are planes to fill in the missing point data. Similarly, the data extraction unit 117 may also fill in the missing parts of the image data using the image data of the walls and floor.

[0031] Referring to Figure 6, the data editing process according to Embodiment 1 will be described. (Step S31: Data reading process) The editing unit 118 reads the editing data 52 extracted in step S26. The display unit 114 then displays the read editing data 52. At this time, the display unit 114 displays a composite 3D model by pasting the image data contained in the editing data 52 according to the position of each point data of the point cloud data contained in the editing data 52.

[0032] In some cases, the data extraction process may be executed multiple times, resulting in the extraction of multiple editing data sets 52. In this case, the editing unit 118 reads the multiple editing data sets 52. The display unit 114 then displays the read editing data sets 52 on a single screen. In other words, for each editing data set 52, the 3D model obtained by combining the point cloud data with image data is displayed on a single screen. In this case, the display unit 114 displays the multiple editing data 52 with their scales aligned. In other words, the display unit 114 displays each editing data 52 after matching its scale to a reference scale. In the data registration process shown in Figure 3, the point cloud data acquired by the same data processing device 10 has the same scale, so there is no need to match the scale. However, point cloud data acquired by different data processing devices 10 may have different scales, and therefore it becomes necessary to match them.

[0033] Furthermore, the editorial unit 118 may also load a 3D model created with CAD or similar software in addition to the editing data 52. CAD stands for Computer-Aided Design. In this case, the display unit 114 displays the loaded editing data 52 along with the 3D model created with CAD or similar software on a single screen. In other words, it displays both the 3D model obtained by combining point cloud data and image data for the editing data 52, and the 3D model created with CAD or similar software, on a single screen. In this case, the display unit 114 displays the scale of the editing data 52 and the scale of the 3D model created with CAD or the like, in combination.

[0034] (Step S32: Editing process) The editorial department 118 accepts edits to the editing data 52 displayed in step S31. If multiple 3D models of the editing data 52 are displayed, or if a 3D model of the editing data 52 and a 3D model created with CAD or the like are displayed, the editorial department 118 accepts edits to the combined data which is a combination of multiple 3D models.

[0035] Referring to Figure 7, an example of using the data processing system 100 according to Embodiment 1 will be described. First, in the data registration process, data for room A and room B is obtained and registered as source data 51. In the data extraction process, object X is designated as the specified object in the original data 51 for room A, and a cut-out request is issued. As a result, the point cloud data and image data for object X are extracted as editing data 52. Similarly, all objects are designated as specified objects in the original data 51 for room B, and a delete request is issued. As a result, the point cloud data for all objects is removed from room B, and the remaining point cloud data and the image data corresponding to the remaining point cloud data are extracted as editing data 52. In other words, the point cloud data and image data of room B, which has been removed and is now empty, are extracted as editing data 52. During the data editing process, the editing data 52 for object X and the editing data 52 for room B are displayed on a single screen. In other words, the 3D model of object X and the 3D model of empty room B are displayed on the same screen. Then, the 3D model of object X is moved and superimposed on the 3D model of room B. This makes it possible to see what the state will be like when object X is placed in room B. It is also possible to duplicate the 3D model of object X and see what the state will be like when multiple objects X are placed in room B.

[0036] Here, both the 3D model of object X and the 3D model of empty room B were generated from the original data 51 registered during the data registration process. However, either the 3D model of object X or the 3D model of empty room B may be a 3D model created using CAD or similar software. In other words, it is possible to combine and edit a 3D model obtained by extracting point cloud data and image data from some objects, or a 3D model obtained by removing point cloud data from some objects, with a 3D model created using CAD or similar software.

[0037] Referring to Figure 8, the data structure of the original data 51 and the decomposed data according to Embodiment 1 will be described. The source data 51 includes an OBJ file, an MTL file, a texture file, an image file, and a thumbnail file. The OBJ file is a 3D data file that shows coordinate data of a 3D point cloud, and contains information on where in the 3D data the image data should be applied as a texture based on the texture coordinates. The MTL file is a file that describes the information necessary when performing texture mapping. The texture file is the image data of the texture that will be applied to the 3D point cloud shown in the OBJ file, according to the MTL file. The image file is the image data acquired in step S11, and is composed of files in format such as JPG. The thumbnail file is a reduced version of the image data shown in the image file. In the decomposed data, an OBJ file is set for each object from the original data 51. Because an OBJ file is set for each object in the decomposed data, when a specified object is identified, the OBJ file for that specified object is identified, and the partial data, which is the image data of the specified object corresponding to the 3D data of the OBJ file, is identified based on the information held in the OBJ file.

[0038] ***Effects of Embodiment 1*** As described above, the data processing system 100 according to Embodiment 1 decomposes the original data 51, which is point cloud data obtained by the positioning device 16, into separate data for each object present in the target area, and generates decomposed data, which is point cloud data for each object. The data processing system 100 then identifies the decomposed data for a specified object and the partial data consisting of pixels associated with the decomposed data. This provides point cloud data for the specified object and a partial image of the specified object from the image data. In particular, simply by specifying an object, it is possible to obtain point cloud data of the specified object and a partial image of the specified object from the image data, without having to enclose the specified object or perform other such actions.

[0039] Since point cloud data and partial images of the specified object are obtained, it becomes easy to combine and edit the 3D model of the specified object with other 3D models.

[0040] Furthermore, the data processing system 100 according to Embodiment 1 displays multiple 3D models on a single screen after adjusting the scale of each 3D model. This makes it easy to adjust the layout and perform other operations. For example, if the designated object is a large object such as furniture, the data processing system 100 can be used to photograph an area including the room entrance and the planned installation location of the furniture, thereby confirming whether the furniture can be brought in via the delivery route from the room entrance to the planned installation location, which is difficult to confirm visually. It can also be used to confirm whether the furniture can be installed in the planned installation location.

[0041] Embodiment 2. Embodiment 2 differs from Embodiment 1 in that the data processing system 100 is composed of multiple devices. Embodiment 2 will explain these differences, while the same points will not be explained.

[0042] ***Explanation of the structure*** Referring to Figure 9, the configuration of the data processing system 100 according to Embodiment 2 will be described. The data processing system 100 comprises a data processing device 10, a camera 20, and an operation terminal 30. In Embodiment 2, the data processing device 10 is a computer such as a server. The camera 20 is a computer such as a smartphone or tablet terminal. The operation terminal 30 is a computer such as a smartphone, tablet terminal, or PC. PC stands for Personal Computer. The data processing device 10, the imaging device 20, and the operation terminal 30 are connected via a network 40. The camera 20 and the operating terminal 30 may be implemented using a single computer. For example, a single smartphone may function as both the camera 20 and the operating terminal 30.

[0043] Referring to Figure 10, the configuration of the data processing device 10 according to Embodiment 2 will be described. The data processing device 10 differs from the data processing device 10 shown in Figure 2 in that it does not include a camera 15, a positioning device 16, and a display device 17 as hardware components. Furthermore, the data processing device 10 differs from the data processing device 10 shown in Figure 2 in that it does not include an imaging unit 111 and a measurement unit 112 as functional components.

[0044] Referring to Figure 11, the configuration of the imaging device 20 according to Embodiment 2 will be described. The imaging device 20 comprises hardware including a processor 21, memory 22, storage 23, a communication interface 24, a camera 25, and a positioning device 26. The processor 21 is connected to the other hardware via signal lines and controls this other hardware. The processor 21, memory 22, storage 23, communication interface 24, camera 25, and positioning device 26 are the same as the processor 11, memory 12, storage 13, communication interface 14, camera 15, and positioning device 16, respectively.

[0045] The imaging device 20 comprises an imaging unit 211, a measurement unit 212, and a communication unit 213 as functional components. The functions of each functional component of the imaging device 20 are implemented by software. Storage 23 stores programs that implement the functions of each functional component of the imaging device 20. These programs are loaded into memory 22 by the processor 21 and executed by the processor 21. This enables the functions of each functional component of the imaging device 20 to be implemented.

[0046] Referring to Figure 12, the configuration of the operating terminal 30 according to Embodiment 2 will be described. The operating terminal 30 comprises hardware including a processor 31, memory 32, storage 33, a communication interface 34, and a display device 35. The processor 31 is connected to the other hardware via signal lines and controls this other hardware. The processor 31, memory 32, storage 33, communication interface 34, and display device 35 are the same as the processor 11, memory 12, storage 13, communication interface 14, and display device 17, respectively.

[0047] The operating terminal 30 includes an instruction unit 311 and a communication unit 312 as functional components. The functions of each functional component of the operating terminal 30 are implemented by software. The storage 33 stores programs that implement the functions of each functional component of the operating terminal 30. These programs are loaded into memory 32 by the processor 31 and executed by the processor 31. This enables the implementation of the functions of each functional component of the operating terminal 30.

[0048] ***Explanation of operation*** Referring to Figures 13 to 15, the operation of the data processing system 100 according to Embodiment 2 will be described.

[0049] Referring to Figure 13, the data registration process according to Embodiment 2 will be explained. (Step S11A: Image capture process) The imaging unit 211 of the imaging device 20 uses the camera 25 to image the target area and acquires image data of the target area, similar to step S11 in Figure 3.

[0050] (Step S12A: Measurement process) The measurement unit 212 of the imaging device 20 acquires point cloud data indicating the positions of multiple reflection points in the target area using the positioning device 26, similar to step S12 in Figure 3.

[0051] (Step S13A: Registration process) The communication unit 213 of the imaging device 20 associates each pixel of one or more image data acquired in step S11A with each point data of the point cloud data acquired in step S12A, and transmits this as original data 51 to the data processing device 10. As a result, the original data 51 is written to the storage 13 of the data processing device 10.

[0052] Referring to Figure 14, the data extraction process according to Embodiment 2 will be described. (Step S21A: Processing of processing requests) The instruction unit 311 of the operation terminal 30 receives a processing request for the original data 51, similar to step S21 in Figure 4. The communication unit 312 of the operation terminal 30 then transmits the processing request to the data processing device 10.

[0053] (Step S22A: Disassembly process) The decomposition unit 113 of the data processing device 10 generates decomposition data, which is point cloud data for each object, using the original data 51 specified in step S21A as the original data 51 to be processed, similar to step S22 in Figure 4, and registers it in the storage 13.

[0054] (Step S23A: Display process) The display unit 114 of the data processing device 10 transmits the source data 51 specified in step S21A to the operation terminal 30 and displays it on the display device 35, similar to step S23 in Figure 4.

[0055] (Step S24A: Designated reception processing) The instruction unit 311 of the operation terminal 30 accepts the designation of one or more objects to be processed from among the objects included in the 3D model displayed in step S23A, similar to step S24 in Figure 4. At this time, the instruction unit 311 also accepts the designation of whether it is a cut request or a delete request. The communication unit 312 of the operation terminal 30 then transmits information indicating the object to be processed and information indicating whether it is a cut request or a delete request to the data processing device 10.

[0056] (Step S25A: Corresponding data identification process) The corresponding data identification unit 116 of the data processing device 10 identifies the decomposed data for the specified object specified in step S24A from the decomposed data generated in step S22A, similar to step S25 in Figure 4. Furthermore, the corresponding data identification unit 116 identifies the partial data consisting of pixels associated with the decomposed data for the specified object.

[0057] (Step S26A: Extraction process) The data extraction unit 117 of the data processing device 10 extracts editing data 52 from the decomposed data and partial data of the specified object identified in step S25A, similar to step S26 in Figure 4. The data extraction unit 117 may send editing data 52 to the operation terminal 30 in response to a request from the operation terminal 30.

[0058] Referring to Figure 15, the data editing process according to Embodiment 2 will be described. (Step S31: Data reading process) The editing unit 118 of the data processing device 10 reads the editing data 52 extracted in step S26, similar to step S31 in Figure 6. Then, the display unit 114 transmits the read editing data 52 to the operation terminal 30 and displays it on the display device 35.

[0059] (Step S32: Editing process) The editing unit 118 of the data processing device 10 accepts edits to the editing data 52 etc. displayed in step S31, similar to step S32 in Figure 6. Here, the editing unit 118 accepts edits from the operation terminal 30.

[0060] ***Effects of Embodiment 2*** As described above, the data processing system 100 according to Embodiment 2 is implemented by a data processing device 10, an imaging device 20, and an operation terminal 30. Even in this case, it is possible to achieve the same effects as the data processing system 100 according to Embodiment 1.

[0061] Furthermore, by sending the editing data 52 to the operation terminal 30 in step S26A of Figure 14, it is also possible to perform editing using the editing data 52 on the operation terminal 30. For example, it is possible to load the editing data 52 into CAD software and perform editing.

[0062] ***Other configurations*** <Example 1> In Embodiment 1, each functional component was implemented in software. However, in Modification 1, each functional component may be implemented in hardware. The differences between this Modification 1 and Embodiment 1 will be explained below.

[0063] When each functional component is implemented in hardware, the data processing device 10 includes electronic circuits instead of the processor 11, memory 12, and storage 13. The electronic circuits are dedicated circuits that implement the functions of each functional component, as well as the functions of the memory 12 and storage 13.

[0064] Similarly, when each functional component is implemented in hardware, the imaging device 20 includes electronic circuits instead of the processor 21, memory 22, and storage 23. The electronic circuits are dedicated circuits that implement the functions of each functional component, as well as the functions of the memory 22 and storage 23.

[0065] Similarly, when each functional component is implemented in hardware, the operating terminal 30 includes electronic circuits instead of the processor 31, memory 32, and storage 33. The electronic circuits are dedicated circuits that implement the functions of each functional component, as well as the functions of the memory 32 and storage 33.

[0066] Electronic circuits can include single circuits, complex circuits, programmed processors, parallel programmed processors, logic ICs, GAs, ASICs, and FPGAs. GA stands for Gate Array. ASIC stands for Application Specific Integrated Circuit. FPGA stands for Field-Programmable Gate Array. Each functional component may be implemented in a single electronic circuit, or it may be implemented by distributing each functional component across multiple electronic circuits.

[0067] <Modification 2> As a second variation, some of the functional components may be implemented in hardware, while others may be implemented in software.

[0068] The processors 11, 21, and 31, the memories 12, 22, and 32, the storage 13, 23, and 33, and the electronic circuits are collectively called the processing circuit. In other words, the function of each functional component is realized by the processing circuit.

[0069] Furthermore, the term "part" in the above explanation may be replaced with "circuit," "process," "procedure," "processing," or "processing circuit."

[0070] The various aspects of this disclosure are summarized below as an appendix. (Note 1) A positioning device that measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and a decomposition unit that decomposes the point cloud data in the original data, which includes point cloud data obtained by a positioning device that measures the position of the reflection point by irradiating the target area with light and receiving the reflected light reflected at the reflection point, into object-specific point cloud data for each object present in the target area, and generates decomposed data which is decomposed data for each object. A correspondence data identification unit identifies the decomposition data for a specified object from the decomposition data for each object generated by the decomposition unit, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object. A data processing system equipped with the following features. (Note 2) The aforementioned data processing system further, A data extraction unit extracts the decomposition data and partial data of the designated object identified by the corresponding data identification unit as editing data. A data processing system as described in Appendix 1, comprising the following features. (Note 3) The aforementioned data processing system further, A data extraction unit extracts the data for editing, which is the disassembled data and partial data for the designated object identified by the corresponding data identification unit, from the original data. A data processing system as described in Appendix 1, comprising the following features. (Note 4) The aforementioned data processing system further, A display unit that displays a 3D model obtained by combining the image data with the point cloud data included in the original data, A designation receiving unit that receives the designation of the designated object from the three-dimensional model displayed by the display unit, and A data processing system as described in Appendix 2 or 3, comprising: (Note 5) The aforementioned data processing system further, A display unit that simultaneously displays the editing data extracted by the data extraction unit and other point cloud data different from the point cloud data, An editing unit that accepts editing of combined data, which is a combination of the editing data displayed by the display unit and the other point cloud data. A data processing system as described in Appendix 2 or 3, comprising: (Note 6) The display unit displays the editing data and the other point cloud data with the same scale as the editing data. The data processing system described in Appendix 5. (Note 7) The decomposition unit generates decomposed data for each object by removing floor point data from the point cloud data and clustering the remaining point data. A data processing system as described in any one of the items 1 through 6 of the appendix. (Note 8) The disassembly unit generates the disassembly data for each object as a separate file. A data processing system as described in any one of the items 1 through 7 of the appendix. (Note 9) A computer takes point cloud data obtained by a positioning device that measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and image data of the target area, in which each point data constituting the point cloud data is associated with a pixel, and decomposes the point cloud data in the original data for each object present in the target area to generate decomposed data, which is point cloud data for each object. A data processing method in which a computer identifies decomposition data for a specified object from the decomposition data for each object, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object. (Note 10) A positioning device measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and the original data includes point cloud data obtained by the positioning device, and image data of the target area, in which each point data constituting the point cloud data is associated with a pixel. The original data is then decomposed for each object present in the target area, and a decomposition process is performed to generate decomposed data, which is point cloud data for each object. Correspondence data identification process that identifies the decomposition data for a specified object from the decomposition data for each object generated by the decomposition process, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object. A data processing program that causes a computer to execute a command.

[0071] The embodiments and variations of this disclosure have been described above. Some of these embodiments and variations may be implemented in combination. Alternatively, some or all of them may be implemented in part. However, this disclosure is not limited to the embodiments and variations described above, and various modifications are possible as needed. [Explanation of symbols]

[0072] 100 Data processing system, 10 Data processing device, 11 Processor, 12 Memory, 13 Storage, 14 Communication interface, 15 Camera, 16 Positioning device, 17 Display device, 111 Imaging unit, 112 Measurement unit, 113 Decomposition unit, 114 Display unit, 115 Designation reception unit, 116 Corresponding data identification unit, 117 Data extraction unit, 118 Editing unit, 20 Imaging device, 21 Processor, 22 Memory, 23 Storage, 24 Communication interface, 25 Camera, 26 Positioning device, 211 Imaging unit, 212 Measurement unit, 213 Communication unit, 30 Operation terminal, 31 Processor, 32 Memory, 33 Storage, 34 Communication interface, 35 Display device, 311 Instruction unit, 312 Communication unit, 51 Original data, 52 Editing data.

Claims

1. A positioning device that measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and a decomposition unit that decomposes the point cloud data in the original data, which includes point cloud data obtained by a positioning device that measures the position of the reflection point by irradiating the target area with light and receiving the reflected light reflected at the reflection point, into object-specific point cloud data for each object present in the target area, and generates decomposed data which is decomposed data for each object. A correspondence data identification unit identifies the decomposition data for a specified object from the decomposition data for each object generated by the decomposition unit, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object. A data processing system equipped with the following features.

2. The aforementioned data processing system further, A data extraction unit extracts the decomposition data and partial data of the designated object identified by the corresponding data identification unit as editing data. The data processing system according to claim 1, comprising:

3. The aforementioned data processing system further, A data extraction unit extracts the data for editing, which is the disassembled data and partial data for the designated object identified by the corresponding data identification unit, from the original data. The data processing system according to claim 1, comprising:

4. The aforementioned data processing system further, A display unit that displays a three-dimensional model obtained by combining the image data with the point cloud data included in the original data, A designation reception unit that receives the designation of the designated object from the three-dimensional model displayed by the display unit, and The data processing system according to claim 2 or 3, comprising:

5. The aforementioned data processing system further, A display unit that simultaneously displays the editing data extracted by the data extraction unit and other point cloud data different from the point cloud data, An editing unit that accepts editing of combined data, which is a combination of the editing data displayed by the display unit and the other point cloud data. The data processing system according to claim 2 or 3, comprising:

6. The display unit displays the editing data and the other point cloud data with the same scale as the editing data. The data processing system according to claim 5.

7. The decomposition unit generates decomposed data for each object by removing floor point data from the point cloud data and clustering the remaining point data. The data processing system according to claim 1.

8. The disassembly unit generates the disassembly data for each object as a separate file. The data processing system according to claim 1.

9. A computer takes point cloud data obtained by a positioning device that measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and image data of the target area, in which each point data constituting the point cloud data is associated with a pixel, and decomposes the point cloud data in the original data for each object present in the target area to generate decomposed data, which is point cloud data for each object. A data processing method in which a computer identifies decomposition data for a specified object from the decomposition data for each object, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object.

10. A positioning device measures the position of a reflection point by irradiating a target area with light and receiving the reflected light reflected at the reflection point, and the original data includes point cloud data obtained by the positioning device, and image data of the target area, in which each point data constituting the point cloud data is associated with a pixel. The original data is then decomposed for each object present in the target area, and a decomposition process is performed to generate decomposed data, which is point cloud data for each object. Correspondence data identification process that identifies the decomposition data for a specified object from the decomposition data for each object generated by the decomposition process, and partial data consisting of pixels from the image data included in the original data that are associated with the decomposition data for the specified object. A data processing program that causes a computer to execute a command.

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