Measurement system, measurement device, measurement method, and program

Abstract

The objective of the present disclosure is to provide a measurement system enabling detailed analysis using three-dimensional map data. A measurement system (10) according to the present disclosure comprises: a data generation unit (11) that generates three-dimensional map data combining point cloud data indicating the shape of a predetermined area and identification information for objects present in the predetermined area; an identification unit (12) that identifies the shape of each object included in the three-dimensional map data; a measurement unit (13) that measures the dimensions of an object of measurement designated for measurement from among the objects of which the shape has been identified; and an output unit (14) that outputs a measurement result.

Description

MEASUREMENT SYSTEM, MEASUREMENT DEVICE, MEASUREMENT METHOD, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM

[0001] The present disclosure relates to a measurement system, a measurement device, a measurement method, and a non-transitory computer-readable medium.

[0002] The Mobile Mapping System (MMS) is used as a system for quickly and accurately acquiring information about three-dimensional space. The MMS is equipped with a laser measuring device, a camera device, and an IMU (Inertial Measurement Unit) on a vehicle, and while the vehicle is moving, it generates three-dimensional map data by combining point cloud data acquired by the laser measuring device with image data acquired by the camera device and data measured by the IMU.

[0003] Patent Literature 1 discloses the configuration of a road feature recognition device that uses road feature image data to recognize road features whose shapes are formed by a laser point cloud. Furthermore, Patent Literature 2 discloses the configuration of a tree number calculation system that uses a three-dimensional image including the tree apexes and crowns to identify tree species and measure the distance between each tree apex.

[0004] JP 2009-199284 A JP 2011-103098 A

[0005] When 3D map data generated using an MMS or the device disclosed in Patent Document 1 is applied to the system disclosed in Patent Document 2, it is possible to identify tree species contained in the 3D map data. On the other hand, it is desirable to perform more detailed analysis using 3D map data and smoothly carry out survey work in a specified area.

[0006] An object of the present disclosure is to provide a measurement system, a measurement device, a measurement method, and a non-transitory computer-readable medium that enable detailed analysis using three-dimensional map data.

[0007] A measurement system according to a first aspect of the present disclosure includes a data generation means for generating three-dimensional map data that combines point cloud data indicating the shape of a specified area with identification information of objects present in the specified area, an identification means for identifying the shape of each of the objects included in the three-dimensional map data, a measurement means for measuring the dimensions of a measurement object designated as a measurement object among the objects whose shape has been identified, and an output means for outputting the measurement results.

[0008] A measuring device according to a second aspect of the present disclosure includes an identification means for identifying the shape of each object included in three-dimensional map data that combines point cloud data indicating the shape of a specified area with identification information of objects present in the specified area, a measurement means for measuring the dimensions of a measurement object designated as a measurement object among the objects whose shape has been identified, and an output means for outputting the measurement results.

[0009] A measurement method according to a third aspect of the present disclosure identifies the shape of each object contained in three-dimensional map data that combines point cloud data indicating the shape of a specified area with identification information of objects existing in the specified area, measures the dimensions of measurement objects designated as measurement objects among the objects whose shapes have been identified, and outputs the measurement results.

[0010] A program according to a fourth aspect of the present disclosure causes a computer to identify the shape of each object included in three-dimensional map data that combines point cloud data indicating the shape of a specified area with identification information of objects existing in the specified area, measure the dimensions of measurement objects designated as measurement objects among the objects whose shapes have been identified, and output the measurement results.

[0011] The present disclosure can provide a measurement system, a measurement device, a measurement method, and a non-transitory computer-readable medium that enable detailed analysis using three-dimensional map data.

[0012] FIG. 1 is a configuration diagram of a measurement system according to a first embodiment. FIG. 2 is a diagram showing the flow of measurement processing executed in the measurement system according to the first embodiment. FIG. 3 is a configuration diagram of a measurement device according to a second embodiment. FIG. 4 is a diagram showing the flow of processing related to image data according to the second embodiment. FIG. 5 is a diagram showing the flow of position estimation processing according to the second embodiment. FIG. 6 is a diagram showing the flow of 3D map data generation processing according to the second embodiment. FIG. 7 is a diagram showing the flow of dimension measurement processing according to the second embodiment. FIG. 8 is a diagram showing the flow of measurement processing according to a third embodiment. FIG. 9 is a configuration diagram of a measurement device according to each embodiment.

[0013] (Embodiment 1) Hereinafter, an embodiment of the present invention will be described with reference to the drawings. An example configuration of a measurement system 10 according to embodiment 1 will be described using FIG. 1 . The measurement system 10 includes a data generation unit 11, an identification unit 12, a measurement unit 13, and an output unit 14. The data generation unit 11, the identification unit 12, the measurement unit 13, and the output unit 14 may be physically located in a single computer device or may be distributed across two or more computer devices. When the data generation unit 11, the identification unit 12, the measurement unit 13, and the output unit 14 are distributed across two or more computer devices, the data generation unit 11, the identification unit 12, the measurement unit 13, and the output unit 14 may transfer data via a network. The data generation unit 11, the identification unit 12, the measurement unit 13, and the output unit 14 may be used as a means for generating data, a means for identifying data, a means for measuring data, and a means for outputting data, respectively.

[0014] The computer device may be a device that operates when a processor executes a program stored in a memory. The data generation unit 11, the identification unit 12, the measurement unit 13, and the output unit 14 may be software or modules that perform processing when a processor executes a program stored in a memory. Alternatively, the data generation unit 11, the identification unit 12, the measurement unit 13, and the output unit 14 may be hardware such as a circuit or a chip.

[0015] The data generation unit 11 generates three-dimensional map data that combines point cloud data indicating the shape of a predetermined area with identification information of objects present in the predetermined area. The predetermined area may be, for example, an area from which point cloud data can be acquired using a sensor or the like. Specifically, the predetermined area may be an area of ​​a closed space such as the interior of a building, or an area of ​​an open space such as the exterior of a building. Note that, in describing the embodiments of the present disclosure, point cloud data is used as an example of data indicating the shape of the predetermined area, but this is not intended to be limited to point cloud data, and data representing other shapes, such as mesh data generated from point cloud data, may also be used.

[0016] The shape of the predetermined area may be the shape of an object existing within the predetermined area. The object existing within the predetermined area may be, for example, an object having the shape of a building, a vehicle, a person, a traffic light, a plant, etc. Furthermore, the object may be a moving object or a stationary object.

[0017] Point cloud data is a collection of points having three-dimensional information. For example, each point may be represented using coordinates indicating a position in three-dimensional space, such as the surface or boundary (edge) of an object. The three-dimensional information may be acquired or detected using a three-dimensional sensor. Specifically, the three-dimensional sensor may be a LiDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging), a laser scanner, or the like. Coordinates indicating a position in three-dimensional space may be represented using a coordinate system based on the position of the three-dimensional sensor. Alternatively, the coordinates indicating a position in three-dimensional space may be a coordinate system for indicating the position of an object in space, such as a world coordinate system or a local coordinate system. Alternatively, the coordinates indicating a position in three-dimensional space may be coordinates converted from a coordinate system based on the position of the three-dimensional sensor to a world coordinate system or the like using a predetermined conversion formula.

[0018] The identification information of the object may be, for example, information indicating the name of the object, or color information used to distinguish between the objects. The name of the object may be determined based on the shape of the point cloud data, for example. The name of the object may be determined using a learning model that learns the shape of the point cloud data and outputs the name of the object indicated by the shape of the point cloud data, or the name recognized by an operator or the like who visually recognizes the shape of the point cloud data may be input to the data generation unit 11.

[0019] The three-dimensional map data may be represented as image data. Furthermore, the three-dimensional map data may be, for example, image data in which different colors are applied to each object, thereby making each object identifiable. Alternatively, the three-dimensional map data may be distance image data or depth image data, which indicates areas of the same distance using the same color. The same distances may be considered to be the same as long as they are substantially the same, and may be considered to be the same as long as they are within a predetermined error range. Furthermore, the image data representing the three-dimensional map data may display the names of each object.

[0020] The identification unit 12 identifies the shape of each object included in the three-dimensional map data. The identification unit 12 may, for example, divide or distinguish the objects included in the three-dimensional map data by considering a plurality of adjacent points as a point cloud indicating the same object. The plurality of adjacent points may, for example, be a set of points located at positions where the distance between the points is shorter than a predetermined distance. Alternatively, the identification unit 12 may identify an area in the three-dimensional map data where a set of points assigned with the same identification information exists as the shape of the same object.

[0021] The measuring unit 13 measures the dimensions of a measurement object designated as a measurement object among the objects whose shapes have been identified. The measurement object may be, for example, an object designated by an operator or the like, and the measuring unit 13 may receive input of information identifying the object from the operator or the like. For example, the operator or the like may input information indicating the name of the object, and may further input information indicating a measurement location within the object to be measured.

[0022] The dimensions of the measurement object may be, for example, information indicating the size of the measurement object, such as the height, width, major axis of the cross section of the object, minor axis of the cross section of the object, or perimeter of the cross section of the object.

[0023] For example, the measurement unit 13 may measure the dimensions using the positions of points included in the measurement object. Alternatively, the measurement unit 13 may measure the dimensions using the positions of points included in the measurement object and a reference position. Specifically, the measurement unit 13 may specify multiple points to be used for measurement and measure the dimensions of the measurement object using the coordinates of each point. Alternatively, the measurement unit 13 may use the ground as a reference position and measure the height of the object from the ground.

[0024] The output unit 14 outputs the measurement results. For example, the output unit 14 may be a display unit such as a display that displays image data, or may be a speaker that outputs the measurement results by voice or the like.

[0025] Next, the flow of the measurement process executed in the measurement system 10 will be described using FIG. 2 . First, the data generation unit 11 generates 3D map data by combining point cloud data indicating the shape of a specified area with identification information of objects present in the specified area (S11). Next, the identification unit 12 identifies the shape of each object included in the 3D map data (S12). Next, the measurement unit 13 measures the dimensions of the measurement object designated as the measurement object among the objects whose shape has been identified (S13). Next, the output unit 14 outputs the measurement results (S14).

[0026] When the data generation unit 11 and the identification unit 12 are located in different computers, the data generation unit 11 transmits the three-dimensional map data to the identification unit 12 via a network. When the identification unit 12 and the measurement unit 13 are located in different computers, the identification unit 12 transmits information about the identified object to the measurement unit 13 via a network. When the measurement unit 13 and the output unit 14 are located in different computers, the measurement unit 13 transmits information indicating the measurement results to the output unit 14 via a network.

[0027] As described above, the measurement system 10 according to the first embodiment measures the dimensions of objects included in the three-dimensional map data as an analysis using three-dimensional data. Furthermore, a worker or the like surveying a predetermined area can recognize the measurement results indicating the dimensions. This allows the worker or the like to easily recognize the location or size of objects within the predetermined area.

[0028] (Embodiment 2) Next, an example of the configuration of the measurement device 20 will be described with reference to Fig. 3. The measurement device 20 may be a computer device that operates when a processor executes a program stored in a memory. The components of the measurement device 20 may be software or modules that perform processing when a processor executes a program stored in a memory. Alternatively, the components of the measurement device 20 may be hardware such as a circuit or a chip.

[0029] The measuring device 20 has a color data measuring unit 21, a shape data measuring unit 23, and a movement amount data measuring unit 25. While moving, the measuring device 20 generates various types of data using the color data measuring unit 21, the shape data measuring unit 23, and the movement amount data measuring unit 25. Alternatively, the measuring device 20 may collect or acquire the generated data from the color data measuring unit 21, the shape data measuring unit 23, and the movement amount data measuring unit 25, which generate data while moving.

[0030] The color data measurement unit 21 may be an image sensor that generates image data. Specifically, the image sensor may be a camera device that generates RGB (Red Green Blue) colors. The color data measurement unit 21 may be provided within the measurement device 20, or may be attached to the measurement device 20 as an external device. Alternatively, the color data measurement unit 21 may be installed in a location remote from the measurement device 20 and transmit image data to the measurement device 20 via a network.

[0031] The shape data measurement unit 23 may be a three-dimensional sensor that measures the shape of an object and the distance from the shape data measurement unit 23 to the object. The sensor that measures the shape and distance may be, for example, a LiDAR. The shape data measurement unit 23 generates point cloud data that indicates the shape of the object. The shape data measurement unit 23 may also associate time information with each point included in the point cloud data. Specifically, the shape data measurement unit 23 may associate the time at which each point was detected with each point. The shape data measurement unit 23 may be provided within the measuring device 20 or may be attached as an external device to the measuring device 20. Alternatively, the shape data measurement unit 23 may be installed at a location remote from the measuring device 20 and transmit the point cloud data to the measuring device 20 via a network.

[0032] The movement amount data measurement unit 25 may be a movement amount sensor that records how the movement amount data measurement unit 25 has moved. The movement amount sensor may be, for example, an inertial measurement unit (IMU). The inertial measurement unit may include, for example, an angular velocity sensor, an acceleration sensor, a magnetic sensor, etc., and may measure the movement amount of the measuring device 20 equipped with the movement amount data measurement unit 25 using values ​​detected using the angular velocity sensor and the acceleration sensor. The movement amount may be a distance from a specific reference position or a distance traveled within a predetermined period. The shape data measurement unit 23 may associate time information with data indicating the movement amount. Specifically, the shape data measurement unit 23 may associate the time at which the movement amount was measured with the data indicating the movement amount.

[0033] The measuring device 20 has an object identification unit 22, a shape data synthesis unit 24, a position and direction measurement unit 26, a shape data identification unit 27, and a division unit 28 in order to process the various data generated in the color data measurement unit 21, the object identification unit 22, and the shape data measurement unit 23. Processing the data may include processes such as converting the data and correcting the data.

[0034] The object identification unit 22 uses the image data generated by the color data measurement unit 21 to identify objects included in the image data. For example, the object identification unit 22 may perform semantic segmentation to identify objects included in the image data. In the semantic segmentation, for example, image recognition using deep learning may be performed. As the deep learning, a convolutional neural network may be used. Specifically, the object identification unit 22 may assign an identifier that identifies the object, or a category of the object, to all pixels included in the image data. The identifier may be referred to as a label. The object identification unit 22 may assign the same color to pixels that indicate the same object or the same category.

[0035] The position and direction measurement unit 26 estimates the movement direction of the measurement device 20, the attitude of the measurement device 20, the position when the movement amount was measured, etc., using data indicating the movement amount of the measurement device 20. The position and direction measurement unit 26 estimates the movement direction, attitude, position, etc., using multiple sensor data that the movement amount data measurement unit 25 has.

[0036] The shape data synthesis unit 24 synthesizes the point cloud data generated by the shape data measurement unit 23 using time information associated with the movement direction, posture, position, etc. estimated by the position and direction measurement unit 26. Specifically, the shape data synthesis unit 24 identifies points associated with time information that is substantially the same as the time information associated with the movement direction, posture, position, etc. estimated by the position and direction measurement unit 26. The points associated with time information are points included in the point cloud data. The points identified using the time information are rotated and translated using the movement direction, posture, position, etc. estimated by the position and direction measurement unit 26 to generate three-dimensional data indicating a three-dimensional shape.

[0037] The shape data identification unit 27 associates the coordinate values ​​in three-dimensional space between the pixels to which identifiers have been assigned, generated by the object identification unit 22, and the three-dimensional data generated by the shape data synthesis unit 24. For example, the physical installation positions of the shape data measurement unit 23 and the movement amount data measurement unit 25 are assumed to be predetermined. As a result, the shape data identification unit 27 may recognize or store in advance a correspondence relationship indicating which measurement points measured by the shape data measurement unit 23 correspond to which pixels included in the image data generated by the color data measurement unit 21. The measurement points measured by the shape data measurement unit 23 may be each point included in the point cloud data.

[0038] Alternatively, the shape data identification unit 27 may match feature points extracted from the point cloud data generated by the shape data measurement unit 23 and the image data generated by the color data measurement unit 21, and associate pixels and measurement locations that have matching feature points.

[0039] The shape data identification unit 27 generates three-dimensional map data to which color data has been assigned by associating the coordinate values ​​in three-dimensional space of the pixels to which identifiers have been assigned with the three-dimensional data generated by the shape data synthesis unit 24.

[0040] The dividing unit 28 divides each object included in the 3D map data by grouping together pixels having the same identifier within a predetermined area in the 3D map data. In other words, the dividing unit 28 groups together pixels having the same identifier that exist in close proximity and recognizes them as a single object. This enables the dividing unit 28 to distinguish and recognize, for example, people, plants, buildings, etc., and further enables the dividing unit 28 to identify each individual person, plant, building, etc., even if they are of the same type.

[0041] The dimension measurement target designation unit 29 designates an object whose dimensions are to be measured. The dimension measurement target designation unit 29 may, for example, receive input of information designating the object from an administrator of the measuring device 20 or the like. For example, the dimension measurement target designation unit 29 may designate an identifier assigned by the object identification unit 22. Specifically, the dimension measurement target designation unit 29 may designate a type of wood, a building, a road, or the like that is to be measured. Alternatively, the dimension measurement target designation unit 29 may designate an individual object identified by the division unit 28 as the object whose dimensions are to be measured.

[0042] The measurement point designation unit 30 designates a measurement point on the object designated in the dimension measurement target designation unit 29. The measurement point designation unit 30 may receive input of information designating the measurement point from, for example, an administrator of the measuring device 20. The measurement point may be, for example, the diameter, major axis, or minor axis of a cross section at a specific point on the object. Alternatively, the measurement point may be the perimeter of a cross section at a specific point on the object. Alternatively, the measurement point may be the height, length, or width of the object.

[0043] The dimension measurement unit 31 measures the measurement location specified in the measurement location designation unit 30 of the object specified in the dimension measurement target designation unit 29. The dimension measurement unit 31 may measure the dimension, for example, using coordinates indicated by point cloud data at the location specified as the measurement location. Alternatively, when it is specified to measure the height of an object, the dimension measurement unit 31 may measure the dimension from a surface with which the bottom end of the object is in contact to the top end of the object. In other words, the dimension measurement unit 31 may measure the dimension using coordinates indicating the surface and coordinates of the point cloud data at the top end of the object. The surface with which the bottom end of the object is in contact may be, for example, the ground, the surface of another object, etc.

[0044] Alternatively, when dimensions relating to a cross section at a predetermined position on the object are specified as the measurement location, the dimension measuring unit 31 may use point cloud data on the cross section to fit a circular shape to the cross section and measure the diameter, circumference, area, etc. of the fitted circular shape.

[0045] The output unit 32 outputs the measurement results measured by the dimension measuring unit 31. Specifically, the output unit 32 may display the measurement results. Alternatively, the output unit 32 may transmit the measurement results to a terminal or the like held by a user who wishes to check the measurement results.

[0046] Next, the flow of processing for image data according to the second embodiment will be described with reference to FIG. 4 . First, the color data measurement unit 21 acquires image data (S21). For example, the color data measurement unit 21 acquires image data using a camera capable of acquiring RGB data. Next, the object identification unit 22 identifies objects contained in the image data (S22). For example, the object identification unit 22 may perform semantic segmentation and assign an identifier for identifying the object to every pixel contained in the image data. The color data measurement unit 21 may be mounted on a mobile measurement device 20 and may periodically acquire image data. Therefore, steps S21 and S22 may be repeated for a predetermined period of time. Furthermore, information regarding the time at which the image data was acquired may be associated with the image data acquired by the color data measurement unit 21.

[0047] Next, a flow of the position estimation process of the measuring device 20 according to the second embodiment will be described with reference to Fig. 5. First, the movement amount data measurement unit 25 acquires movement amount data (S31). For example, the movement amount data measurement unit 25 may use an inertial measurement unit to acquire data indicating the amount of movement of the measuring device 20 equipped with the movement amount data measurement unit 25.

[0048] Next, the position and direction measurement unit 26 uses the data indicating the movement amount of the measurement device 20 to estimate the movement direction of the measurement device 20, the attitude of the measurement device 20, the position when the movement amount was measured, etc. (S32). The movement amount data measurement unit 25 may be mounted on the moving measurement device 20 and may periodically acquire movement amount data. Therefore, steps S31 and S32 may be repeated over a predetermined period. Furthermore, the data indicating the movement amount acquired by the movement amount data measurement unit 25 may be associated with information regarding the time when the data indicating the movement amount was acquired.

[0049] Next, a flow of a process for generating 3D map data according to the second embodiment will be described with reference to FIG. 6 . First, the shape data measurement unit 23 acquires point cloud data indicating the shape of an object (S41). The shape data measurement unit 23 may acquire the point cloud data using a LiDAR, which is a three-dimensional sensor. The shape data measurement unit 23 may periodically acquire the point cloud data during a predetermined period. The shape data measurement unit 23 may associate each piece of point cloud data with time information at which it was measured. The shape data measurement unit 23 may periodically acquire the point cloud data. More specifically, the shape data measurement unit 23 may periodically acquire the point cloud data while the measuring device 20 is moving.

[0050] Next, the shape data synthesis unit 24 generates three-dimensional data that shows the object in three dimensions within a specified area using the movement direction of the measuring device 20, the attitude of the measuring device 20, and the position when the movement amount was measured, estimated by the movement amount data measurement unit 25 (S42).

[0051] Next, the shape data identification unit 27 generates three-dimensional map data using the three-dimensional data generated by the shape data synthesis unit 24 and the image data including the pixels to which the identifiers have been assigned (S43). The shape data identification unit 27 may combine the three-dimensional data with color data included in the image data to generate colored three-dimensional map data.

[0052] Next, the segmentation unit 28 identifies the shape of each object included in the 3D map data (S44). The segmentation unit 28 groups nearby pixels having the same identifier and recognizes them as a single object. This enables the segmentation unit 28 to distinguish between, for example, people, plants, buildings, etc., and further enables the segmentation unit 28 to identify individual plants of the same type.

[0053] Next, the flow of the dimension measurement process according to the second embodiment will be described with reference to Fig. 7. First, the dimension measurement target designation unit 29 receives information designating an object to be measured (S51). For example, the dimension measurement target designation unit 29 receives input of information designating the object from an administrator of the measuring device 20 or the like. The administrator may input the information designating the object using an input device such as a touch panel or a keyboard.

[0054] Next, the measurement location designation unit 30 receives information designating the measurement location of the object to be measured (S52). For example, the measurement location designation unit 30 receives information designating the measurement location of the object from an administrator of the measuring device 20 or the like.

[0055] Next, the dimension measuring unit 31 measures the dimension of the measurement location specified as the measurement target of the object specified as the measurement target (S53). Next, the output unit 32 outputs the measurement result of the dimension measuring unit 31 (S54).

[0056] As described above, the measuring device 20 according to the second embodiment measures the dimensions of any location of an object included in three-dimensional map data, as specified by an administrator, etc. This enables detailed analysis using the dimensions of each object in a specified area.

[0057] For example, by using the measuring device 20 when conducting a tree survey in a forest, it becomes possible to easily measure the diameter at breast height of each tree without the need for an operator to measure the diameter at breast height of each tree on-site. The tree survey may also be referred to as a tree-by-tree survey.

[0058] Third Embodiment Next, the flow of measurement processing according to the third embodiment will be described with reference to Fig. 8. In Fig. 8, the flow of processing for verifying the accuracy of various data acquired by the color data measurement unit 21, the shape data measurement unit 23, and the movement amount data measurement unit 25 will be described.

[0059] In this embodiment, the color data measurement unit 21 acquires the time when the color data was acquired (a time synchronized with the shape data measurement unit 23 and the movement amount data measurement unit 25) along with the color data. Using position information estimated by the position and direction measurement unit 26, which can be considered to be the same time as this time information, the shape data identification unit 27 identifies the distance from the color data measurement unit 21 to the object included in the 3D map data when the color data of the object was acquired (S61). The 3D map data includes point cloud data, which has distance information to each object. The shape data identification unit 27 may, for example, identify the distance information of an arbitrary point among the point cloud data included in the 3D map data. The arbitrary point may, for example, be a point included in each of the areas obtained by dividing the 3D map data into multiple areas.

[0060] Next, the shape data identification unit 27 identifies a measurement error using the distance to the object and the number of pixels in the image data (S62). For example, the shape data identification unit 27 calculates the width and height of the image data to the actual length of a specified area using the sensor size and focal length of the camera that generates the image data and the distance to an arbitrary point included in the point cloud data. Furthermore, the shape data identification unit 27 calculates the actual length of a specified area to which one pixel constituting the image data corresponds using the number of pixels in the image data. In other words, the shape data identification unit 27 calculates how many meters one pixel corresponds to in reality. In this case, the longer the distance to the object, the longer the actual length represented by one pixel.

[0061] The shape data identification unit 27 determines the actual length represented by one pixel as the measurement error and compares the measurement error with a threshold (S63). For example, if the actual length represented by one pixel is longer than the threshold, the shape data identification unit 27 determines the area near the object as an incomplete measurement area (S64). Furthermore, if the actual length represented by one pixel is shorter than the threshold, the shape data identification unit 27 determines the area near the object as a fully measured area (S65). If the actual length represented by one pixel is longer than the threshold, the object is photographed from a greater distance. In this case, when a measurement point is specified to measure the dimensions, the measurement error increases. Therefore, if the actual length represented by one pixel is longer than the threshold, the area near the object may be determined as an incomplete measurement area and the user may be prompted to remeasure the area near the object. For example, the shape data identification unit 27 may output map data indicating the fully measured area and the incomplete measurement area from the output unit 32.

[0062] Alternatively, the shape data identification unit 27 may determine the incompletely measured area and the completely measured area using measurement errors given as specifications of the image sensor used as the color data measurement unit 21 and the three-dimensional sensor used as the shape data measurement unit 23. In this case, the measurement error may indicate, for example, an error in the size of an object at a predetermined distance from the sensor. If the measurement errors of the image sensor and the three-dimensional sensor at a predetermined distance are different, the completely measured area and the incompletely measured area may be determined based on the distance at which the measurement error of the less accurate sensor is smaller than a predetermined value. Alternatively, if the measurement errors of the image sensor and the three-dimensional sensor at a predetermined distance are different, data may be acquired using each sensor, and measurement may be determined to be complete when both sensors indicate that all areas are completely measured.

[0063] The dimension measuring unit 31 measures the dimensions of the designated measurement location of the designated object using three-dimensional map data relating to the measurement-completed area.

[0064] As described above, by executing the measurement process according to the third embodiment, it is possible to generate data with smaller measurement errors so as to minimize errors when measuring dimensions. Here, the configuration for using 3D map data to suppress measurement errors below a threshold has been described, but this may also be performed during measurement. For example, the measurement range may be set in advance using a GIS (Geographic Information System) or the like, and the measurement device 20 may acquire location information in a coordinate system that can be linked to the GIS using GNSS or the like, thereby determining its own location. Then, each time the color data measurement unit 21 acquires color data, the shape data measurement unit 23 acquires shape data (a collection of distance information to the object) to acquire distance information to the object indicated by each pixel of the color data. The distance information, the sensor size, focal length, and number of pixels of the color data measurement unit 21 may be used to calculate how many meters each pixel corresponds to in real life, and the measurement may be determined to be complete or incomplete based on the calculation. Alternatively, the measuring device 20 may be able to determine its own position using SLAM (Simultaneous Localization And Mapping, simultaneous execution of self-position estimation and environmental map creation) technology and information on reference points that can be linked with a GIS.

[0065] FIG. 9 is a block diagram showing an example of the configuration of the measurement device 20 described in the above embodiment. Referring to FIG. 9, the measurement device 20 includes a network interface 1201, a processor 1202, and a memory 1203. The network interface 1201 may be used to communicate with a network node. The network interface 1201 may include, for example, a network interface card (NIC) conforming to the IEEE 802.3 series. IEEE stands for Institute of Electrical and Electronics Engineers.

[0066] The processor 1202 reads and executes software (computer programs) from the memory 1203 to perform the processing of the measurement device 20 described using the flowcharts in the above-described embodiment. The processor 1202 may be, for example, a microprocessor, an MPU, or a CPU. The processor 1202 may include multiple processors.

[0067] The memory 1203 is configured by a combination of volatile memory and non-volatile memory. The memory 1203 may include storage located remotely from the processor 1202. In this case, the processor 1202 may access the memory 1203 via an I / O (Input / Output) interface (not shown).

[0068] 9, the memory 1203 is used to store software modules. The processor 1202 reads and executes these software modules from the memory 1203, thereby performing the processing of the measurement device 20 described in the above embodiment.

[0069] As explained using Figure 9, each of the processors of the measuring device 20 in the above-mentioned embodiment executes one or more programs including a set of instructions for causing a computer to perform the algorithm explained using the drawing.

[0070] In the above examples, the program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored on a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable medium or tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0071] The technical ideas of the present disclosure are not limited to the above-described embodiments, and can be modified as appropriate within the scope of the invention.

[0072] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0073] (Supplementary Note 1) A measurement system comprising: a data generation means for generating three-dimensional map data that combines point cloud data indicating the shape of a predetermined area with identification information of objects present in the predetermined area; a specification means for specifying the shape of each of the objects included in the three-dimensional map data; a measurement means for measuring dimensions of a measurement object designated as a measurement object among the objects whose shape has been specified; and an output means for outputting the measurement results. (Supplementary Note 2) The measurement system according to Supplementary Note 1, wherein the measurement means measures dimensions of a measurement target location of the measurement object designated together with the measurement object. (Supplementary Note 3) The measurement system according to Supplementary Note 1, wherein the measurement means measures a height of the measurement object or a width of the measurement object at a predetermined height. (Supplementary Note 4) The measurement system according to any one of Supplements 1 to 3, wherein the specification means associates the object with label information indicating the object. (Supplementary Note 5) The measurement system according to Supplementary Note 4, wherein the measurement means measures the dimensions of an object associated with the designated label information. (Supplementary Note 6) The measurement system according to any one of Supplements 1 to 5, further comprising an image sensor that generates image data of the object, wherein the data generation means generates the 3D map data using the image data in which a measurement error of the size of the object falls within a predetermined range. (Supplementary Note 7) The measurement system according to Supplementary Note 6, further comprising a three-dimensional sensor that generates the point cloud data including distance information from the image sensor to the object, wherein the data generation means selects the point cloud data and the image data to be used for generating the 3D map data using the distance to the object. (Supplementary Note 8) The measurement system according to Supplementary Note 7, wherein the data generation means calculates a length equivalent to one pixel using the distance information and the number of pixels in image data generated by the image sensor, and generates the 3D map data using the image data and the point cloud data generated at a distance where the length equivalent to one pixel is shorter than a predetermined length.(Supplementary Note 9) A measurement device comprising: an identifying means for identifying the shape of each object included in three-dimensional map data that combines point cloud data that indicates the shape of a predetermined area with identification information of objects present in the predetermined area; a measuring means for measuring dimensions of a measurement object designated as a measurement object from among the objects whose shapes have been identified; and an output means for outputting a measurement result. (Supplementary Note 10) The measurement device according to Supplementary Note 9, wherein the measuring means measures dimensions of a measurement target location of the measurement object that has been designated together with the measurement object. (Supplementary Note 11) A measurement method that identifies the shape of each object included in three-dimensional map data that combines point cloud data that indicates the shape of a predetermined area with identification information of objects present in the predetermined area, measures the dimensions of a measurement object designated as a measurement object from among the objects whose shapes have been identified, and outputs a measurement result. (Supplementary Note 12) A non-transitory computer-readable medium storing a program that causes a computer to execute the following steps: identify the shape of each object included in three-dimensional map data that combines point cloud data indicating the shape of a specified area with identification information of objects existing in the specified area; measure the dimensions of measurement objects designated as measurement objects among the objects whose shapes have been identified; and output the measurement results.

[0074] REFERENCE SIGNS LIST 10 Measurement system 11 Data generation unit 12 Identification unit 13 Measurement unit 14 Output unit 20 Measurement device 21 Color data measurement unit 22 Object identification unit 23 Shape data measurement unit 24 Shape data synthesis unit 25 Movement amount data measurement unit 26 Position and direction measurement unit 27 Shape data identification unit 28 Division unit 29 Dimension measurement target designation unit 30 Measurement location designation unit 31 Dimension measurement unit 32 Output unit

Claims

1. a data generating means for generating three-dimensional map data by combining point cloud data indicating the shape of a predetermined area with identification information of objects existing in the predetermined area; an identification means for identifying the shape of each of the objects included in the three-dimensional map data; a measuring means for measuring the dimensions of a measurement object designated as a measurement object among the objects whose shapes have been specified; and an output means for outputting the measurement result.

2. The identification means The measurement system according to claim 1 , wherein the object is associated with label information that indicates the object.

3. The measuring means The measurement system of claim 2 , which measures dimensions of an object associated with the specified label information.

4. further comprising an image sensor for generating image data of the object; The data generating means The measurement system according to claim 1 , wherein the three-dimensional map data is generated using the image data in which a measurement error in the size of the object falls within a predetermined range.

5. a three-dimensional sensor that generates the point cloud data including distance information from the image sensor to the object; The data generating means The measurement system according to claim 4 , wherein the distance to the object is used to select the point cloud data and the image data to be used for generating the three-dimensional map data.

6. The data generating means 6. The measurement system according to claim 5, wherein a length corresponding to one pixel is calculated using the distance information and the number of pixels of image data generated by the image sensor, and the three-dimensional map data is generated using the image data and the point cloud data generated at a distance where the length corresponding to one pixel is shorter than a predetermined length.

7. an identification means for identifying the shape of each object included in three-dimensional map data that combines point cloud data indicating the shape of a predetermined area with identification information of objects existing in the predetermined area; a measuring means for measuring the dimensions of a measurement object designated as a measurement object among the objects whose shapes have been specified; and an output means for outputting the measurement result.

8. The measuring means The measuring device according to claim 7 , wherein the measuring device measures dimensions of a measurement target portion of the measurement target that is specified together with the measurement target.

9. Identifying the shape of each object included in three-dimensional map data that combines point cloud data indicating the shape of a predetermined area with identification information of objects present in the predetermined area; measuring the dimensions of a measurement object designated as a measurement object among the objects whose shapes have been specified; A measurement method that outputs measurement results.

10. Identifying the shape of each object included in three-dimensional map data that combines point cloud data indicating the shape of a predetermined area with identification information of objects present in the predetermined area; measuring the dimensions of a measurement object designated as a measurement object among the objects whose shapes have been specified; A program that causes a computer to output measurement results.