JP6802944B1 - Inspection support equipment, inspection support methods and programs - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an inspection support device for accurately detecting a bar arrangement area to be inspected. SOLUTION: In an inspection support device that supports inspection of a skeleton of a building and civil engineering structure, a three-dimensional information acquisition unit 32 that acquires three-dimensional data of the structure including a plurality of planes formed by the skeleton, and A plurality of plane detection units 34 that detect a plurality of first planes containing at least three points of the three-dimensional data from the acquired three-dimensional data and calculate the number of three-dimensional points for each detected first plane. A front surface specifying portion 36 for specifying a second plane to be measured in the skeleton of the structure from among the plurality of detected first planes based on the calculated number of the three-dimensional points is provided. [Selection diagram] Fig. 4

Description

The present invention relates to an inspection support device that supports inspection of the skeleton of a building and civil engineering structure.

In the construction of reinforced concrete buildings, bar arrangement inspections are carried out to check whether the reinforcing bars are correctly arranged based on the bar arrangement diagram and the like. In such a bar arrangement inspection, a system that supports the bar arrangement inspection (hereinafter referred to as "bar arrangement inspection system") has been developed from the viewpoint of improving the efficiency of the inspection and reducing the burden on the inspector. As this bar arrangement inspection system, a technique for performing bar arrangement inspection by analyzing image data of reinforcing bars taken by a digital camera has been actively developed.

For example, Patent Document 1 proposes a reinforcing bar inspection device that derives the distance between adjacent nodes and derives the diameter of the corresponding reinforcing bar of the distance between adjacent nodes based on images of a plurality of nodes of the reinforcing bar. Has been done.

JP-A-2015-001146

Usually, the bar arrangement has a structure divided into a plurality of layers (faces) such as a front surface, a rear surface, and a side surface. Reinforcing bar inspection is often performed on the front layer, but it is difficult to photograph only the reinforcing bar on the front layer in the field, and the reinforcing bars of each layer are often mixed in the photographed image. Therefore, when performing a bar arrangement inspection based on a captured image, it is necessary to correctly extract the reinforcing bars belonging to the layer to be inspected. For example, in Patent Document 1, in order to detect the bar arrangement front region, a three-dimensional point belonging to the front region is first manually specified. However, the method of manually designating the bar arrangement area to be inspected hinders the automation of the inspection and is prone to errors.
In view of the above problems, an object of the present invention is to provide an inspection support device that accurately detects a bar arrangement area to be inspected.

In order to achieve the above object, in an inspection support device that supports inspection of the skeleton of a building and civil engineering structure, three-dimensional data of the structure including a plurality of planes formed by the skeleton is acquired and acquired. A plurality of first planes including at least three three-dimensional points extracted from the three-dimensional data are detected, and the number of three-dimensional points belonging to the first plane is calculated for each of the detected first planes. Each is calculated, and based on the calculated number of the three-dimensional points, the second plane to be measured in the skeleton of the structure is specified from among the plurality of detected first planes.

According to the present invention, it is possible to provide an inspection support device that accurately detects a bar arrangement region to be inspected.

It is a figure which shows the configuration example of the bar arrangement inspection system. It is a flow explaining the main processing of the whole bar arrangement inspection system. It is a block diagram which shows the hardware configuration example of an information processing apparatus. It is a functional block diagram about a bar arrangement inspection process. It is a flowchart explaining the procedure of the front parameter detection process. It is a figure which shows the relationship between the plane L_tmp and the corresponding proximity point. It is a figure which shows the relationship between the plane L_tmp and the corresponding proximity point. This is an example of a plane area image created by the plane area image creation unit. It is a figure which compares the plane area image by the front surface reinforcement and the rear surface reinforcement. It is a functional block diagram about the inspection support process in 2nd Embodiment. It is a flowchart explaining the procedure of the front parameter detection processing in 2nd Embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing a configuration example of a bar arrangement inspection system 1 according to an embodiment of the present invention. The bar arrangement inspection system 1 inspects the skeleton of buildings and civil engineering structures. In the following, as a specific example of the bar arrangement inspection system 1, an example in which the reinforcing bars arranged are photographed and the reinforcing bars are measured based on the photographed image will be described. Reinforcing bar arrangement measurement processing includes measuring the diameter of reinforcing bars, measuring the number of reinforcing bars, measuring the spacing between reinforcing bars, and the like.

The bar arrangement inspection system 1 includes an information processing device 10 and a stereo camera 100. The stereo camera 100 is an example of a three-dimensional data generator (also called a three-dimensional sensor). The three-dimensional data generator may be a 3D laser scanner.

The bar arrangement H is photographed by the stereo camera 100, and three-dimensional data of the bar arrangement H is generated. The stereo camera 100 has a right imaging unit 110R, a left imaging unit 110L, and a three-dimensional data generation unit 120. The right imaging unit 110R captures a right eye viewpoint image viewed from the right eye viewpoint. The left image pickup unit 110L captures a left eye viewpoint image viewed from the left eye viewpoint. The images captured by the right imaging unit 110R and the left imaging unit 110L may be color images or multi-gradation single-color images such as grayscale images, but in the present embodiment, they are grayscale images. ..

The three-dimensional data generation unit 120 generates three-dimensional data by performing a known stereo matching process on the image data of the right-eye viewpoint image and the image data of the left-eye viewpoint image. The three-dimensional data is acquired as an image that holds three-dimensional point information in pixel units, and is also called a three-dimensional image or a distance image.

The information processing device 10 is, for example, a PC (Personal Computer), a tablet terminal, dedicated hardware, or the like. The information processing device 10 acquires the generated three-dimensional data, specifies the measurement target by the front parameter calculation process or the like based on the three-dimensional data, and performs various measurement processes of the reinforcing bar. Further, the information processing apparatus 10 may perform a process of displaying or storing the process result. In the following, the front bar arrangement HA located in the foreground of the bar arrangement H will be measured.

As a means for the information processing device 10 to acquire three-dimensional data from the stereo camera 100, it is wired (for example, a USB cable or the Internet), wireless (for example, a wireless LAN (Local Area Network) or the Internet), or externally attached. Any recording medium may be used.

Next, the entire processing in the bar arrangement inspection system 1 will be briefly described. FIG. 2 is a flow for explaining the main processing of the entire bar arrangement inspection system 1.

Using the stereo camera 100 described above, the photographer performs stereo shooting of the bar arrangement H (step S1). The stereo camera 100 captures a right-eye viewpoint image and a left-eye viewpoint image, and three-dimensional data is generated. The information processing device 10 acquires three-dimensional data from the stereo camera 100 (step S2). The information processing device 10 identifies the frontmost plane from the three-dimensional data (step S3). The foreground plane is the plane located in the foreground among the planes formed by the skeletons of architectural and civil engineering structures. Specifically, the frontmost plane is a plane including the front reinforcement HA in FIG.

The information processing apparatus 10 creates a plane region image based on the identified frontmost plane (step S4), and specifies the arrangement of the reinforcing bars to be measured (step S5). The plane region image will be described with reference to FIGS. 8 and 9. The information processing apparatus 10 performs various measurement processes such as diameter measurement, number measurement, and interval measurement of the target reinforcing bars based on the specified reinforcing bar arrangement (step S6).

FIG. 3 is a block diagram showing a hardware configuration example of the information processing device 10. The information processing device 10 includes a CPU (Central Processing Unit) 510, a RAM (Random Access Memory) 520, a ROM (Read Only memory) 530, an input / output IF (Interface) 540, a communication unit 550, an operation unit 560, a display unit 570, and the like. It has a bus 580.

The CPU 510 is a control unit that comprehensively controls the entire information processing apparatus 10. The CPU 510 reads a control program from the ROM 530 and executes various control processes according to the read control program.

The RAM 520 is a work area for temporarily storing various data such as a control program and three-dimensional data from the stereo camera 100. The RAM 520 is, for example, a DRAM (Dynamic Random Access Memory). The ROM 530 is a non-volatile storage unit that stores control programs, data, and the like. The ROM 530 is, for example, a flash memory.

The input / output IF 540 transmits / receives data to / from an external device. The external device is, for example, a stereo camera 100 connected by a USB cable or the like, or an interchangeable storage unit 600. The information processing device 10 acquires three-dimensional data from the stereo camera 100 by the input / output IF 540. The input / output IF540 is also called a three-dimensional data acquisition unit. The storage unit 600 is a recording medium called a so-called memory card. The storage unit 600 may be an HDD (Hard Disk Drive). The storage unit 600 may store the three-dimensional data generated by the stereo camera 100 and the plane region image generated by the information processing apparatus 10 based on the three-dimensional data.

The communication unit 550 wirelessly communicates various data with an external device. The operation unit 560 is a keyboard or touch panel for inputting operation instructions. The display unit 570 displays, for example, an input data, a captured image, an image based on three-dimensional data, or the like on an LCD (liquid crystal display). The CPU 510 is connected to the RAM 520, the ROM 530, etc. by the bus 580.

FIG. 4 is a functional block diagram related to the bar arrangement inspection process by the information processing device 10 in the bar arrangement inspection system 1. The bar arrangement inspection process is performed by software processing by reading the control program by the CPU 510 and executing the control program read by the CPU 510.

As shown in FIG. 4, the bar arrangement inspection process is performed by software such as a three-dimensional information acquisition unit 32, a plurality of plane detection units 34, a front surface identification unit 36, a plane area image creation unit 38, a reinforcing bar arrangement identification unit 40, and a measurement unit 42. It is realized by the functional part by. Further, since the three-dimensional information acquisition unit 32, the plurality of plane detection units 34, and the front surface specifying unit 36 identify the frontmost plane and support the bar arrangement inspection as described later, the inspection support device 30 is collectively used. Also called.

The three-dimensional information acquisition unit 32 acquires three-dimensional data from the stereo camera 100. The three-dimensional information acquisition unit 32 is, for example, an input / output IF540 as described above.

The multi-plane detection unit 34 detects a plurality of planes including at least three points of the three-dimensional data from the acquired three-dimensional data. Specifically, for example, the plurality of plane detection unit 34 selects three points from the acquired three-dimensional data and sets a temporary plane (also referred to as a first plane) composed of the three points. Detect multiple temporary planes.

Then, the plurality of plane detection units 34 extract, as three-dimensional points belonging to the temporary plane, three-dimensional points whose distance from the temporary plane is equal to or less than a predetermined value from the three-dimensional data for each detected temporary plane. The three-dimensional point is each point of the three-dimensional data. The multiple plane detection unit 34 calculates the number of three-dimensional points belonging to each temporary plane. The plurality of plane detection units 34 output the parameters of the detected temporary plane (referred to as plane parameters) and the number of three-dimensional points belonging to each temporary plane.

The front surface specifying unit 36 identifies the frontmost plane from the plurality of temporary planes output from the plurality of plane detection units 34. Specifically, the front surface specifying portion 36 is a plane located at the foremost surface in the skeleton of the structure from among the plurality of detected temporary planes based on the number of three-dimensional points belonging to each temporary plane. Identify the foreground plane). The frontmost plane is also called the second plane. More specifically, the front surface specifying unit 36 identifies the temporary plane having the largest number of calculated three-dimensional points among the detected plurality of temporary planes as the frontmost plane. The front surface specifying unit 36 outputs the plane parameters of the specified frontmost plane as reinforcement front surface information to the plane area image creation unit 38.

The frontmost plane parameter is also referred to as a front surface parameter, and the plurality of plane detection units 34 and the front surface identification unit 36 are collectively referred to as a front surface parameter detection device 50. The process performed by the front parameter detection device 50 is also called front parameter detection.

The plane area image creation unit 38 creates an image of the front bar arrangement HA from the acquired three-dimensional data based on the frontmost plane parameter. The reinforcing bar arrangement specifying unit 40 specifies the reinforcing bar arrangement from the image of the front reinforcing bar arrangement HA. The measuring unit 42 performs various measurement processes such as diameter measurement, number measurement, and interval measurement of the reinforcing bars based on the specified reinforcing bar arrangement.

FIG. 5 is a flowchart illustrating the procedure of the front parameter detection process. The front parameter detection process is performed by the front parameter detection device 50 (plural plane detection unit 34 and front identification unit 36).

First, the plurality of plane detection units 34 and the front surface identification unit 36 initialize the loop processing variables (t, N). The multi-plane detection unit 34 selects at least three points from the set φ of the three-dimensional points (step S100). The multi-plane detection unit 34 calculates the parameters of the plurality of planes L_tmp based on the selected points (step S102). The plane L_tmp is the above-mentioned temporary plane.

The parameters of the plane L_tmp are the coefficients a, b, c, and d of the equation of a plane represented by the following equation (1).
ax + by + cz + d = 0 ... Equation (1)
Here, (x, y, z) indicates the coordinates of a point in the three-dimensional space. The parameters of the plane L_tpp can be calculated using a known technique such as the least squares method. When the selected points are three points, it can be uniquely calculated.

The multi-plane detection unit 34 calculates the distance between the plane L_tmp and each point of the set φ of the three-dimensional points (step S104). The plurality of plane detection units 34 calculates the number N_tmp of points whose distance from the plane L_tmp is equal to or less than the threshold value D in the set φ of the three-dimensional points (step S106). The threshold value D is a preset value and may be stored in the ROM 530. The threshold value D may be, for example, the radius or diameter of the target reinforcing bar. A three-dimensional point whose distance from the plane L_tmp is equal to or less than the threshold value D is called a proximity point. As the relationship between the distance to the plane L_tmp and the threshold value D, the number of proximity points N_tpp satisfying the following equation (2) is calculated from the set φ of the three-dimensional points.
| Ax + by + cz + d | <D ... Equation (2)

Steps S100 to S106 will be described with reference to FIGS. 6, 7 and 8 as specific examples. 6 and 7 are diagrams showing the relationship between the plane L_tmp and the number of proximity points corresponding to the plane L_tmp.

A large number of planes L_tmp are detected from the set φ of three-dimensional points. The image D4 of FIG. 6 and the image D6 of FIG. 7 are examples thereof. In this example, the bar arrangement H, the wall surface e1 and the floor surface e2 are included in the scene. The plane L_tmp of the image D4 of FIG. 6 is a slope that diagonally crosses the bar arrangement H from the lower front surface of the bar arrangement H toward the upper rear surface of the bar arrangement H. The plane L_tpm of the image D6 of FIG. 7 is a plane parallel to the floor surface e2 and close to the floor surface e2.

Image D5 of FIG. 6 shows the region of the proximity point calculated on the plane L_tmp (slope) of image D4 in white. The region where the plane L_tpm of the image D4 intersects the bar arrangement H and the region where the plane L_tpm intersects the wall surface e1 correspond to the region of the proximity point of the plane L_tpm (slope). In the actual calculation example, the number of proximity points N_tmp was calculated to be 84,032 points.

Image D7 of FIG. 7 shows the region of the proximity point calculated on the plane L_tmp of image D6 in white. Since the plane L_tmp is close to the floor surface e2, the region of the floor surface e2 approximates the region of the proximity point. In the actual calculation example, the number of proximity points N_tmp was calculated to be 310,075 points.

From this, it can be seen that it is desirable to exclude floors and walls. The multi-plane detection unit 34 excludes the floor surface and the wall surface, for example, based on the coordinate values of the three-dimensional data. Alternatively, the plurality of plane detection units 34 may exclude a plane L_tmp in which the number of proximity points N_tmp is a predetermined value or more as a floor surface or a wall surface.

Then, in step S110 and subsequent steps of FIG. 5, the temporary plane having the largest number of proximity points N_tmp is selected from the temporary planes excluding the floor surface and the wall surface, and the selected temporary plane is specified as the frontmost plane of the bar arrangement. To do. The reason will be explained.

As shown in FIG. 6, when the temporary plane crosses the reinforcing bar, the number of proximity points is small. On the other hand, when the temporary plane is in the direction parallel to the axial direction of the reinforcing bar, the number of proximity points increases. That is, the number of proximity points increases as the temporary plane parallel to the surface of the bar arrangement increases. Further, the front reinforcing bar, which is closer to the stereo camera 100, is displayed in a larger size than the rear reinforcing bar (see FIG. 9). That is, the number of proximity points is larger in the front reinforcing bar than in the rear reinforcing bar. From the above, it can be estimated that the temporary plane with the largest number of proximity points is the plane in front of the bar arrangement.

Return to FIG. In the following steps S110 to S114, the front surface specifying unit 36 sequentially compares N_tpmp, which is the calculated number of proximity points of the plane L_tpm, and uses the plane L_tpm having the largest number of proximity points N_tmp as the frontmost plane. Identify.

The front surface specifying portion 36 determines whether N <N_tmp (step S108). N is the provisional maximum value of the number of proximity points. When the front surface specifying unit 36 determines that N <N_tmp (YES in step S108), the front surface specifying unit 36 updates N with N_tpm and updates the plane L with the plane L_tpm (step S110). The plane L is a provisional foreground plane parameter.

The front surface specifying portion 36 is set to t = t + 1 (step S112). t is a loop counter for sequentially comparing N_tmp of the plane L_tmp.

The front surface specifying portion 36 determines whether t <T (step S114). T is the total number of temporary planes calculated in step S104. When t = T, the process is terminated. When the front surface specifying portion 36 determines that t <T (YES in step S114), the front surface specifying portion 36 returns to step S100 and performs processing for the next plane N_tmp.

When the front surface specifying portion 36 determines that N <N_tmp is not satisfied (NO in step S108), the process proceeds to step S112. After step S112, when the front surface specifying unit 36 determines that t <T (NO in step S114), it identifies the plane L as a plane parameter corresponding to the front surface of the bar arrangement and outputs it to the plane area image creating unit 38. .. This completes the front parameter detection process.

The above processing of steps S100 to S114 is common to the processing process of the parameter estimation method by the RANSAC (Random Sample Consensus) processing. The RANSAC process was developed and used with the intention of estimating a numerical model from measured values including outliers (outliers), but for problems that are different from the original intention and are the subject of the present invention. Is also effective.

FIG. 8 is an example of a plane region image created by the plane region image creation unit 38. Image D8 is a diagram showing a three-dimensional image of the bar arrangement H and a plane L set to include the front bar arrangement of the bar arrangement H. The image D9 is a plane region image corresponding to the plane L of the image D8.

FIG. 9 is a diagram comparing a plane region image (image D11) by the front reinforcement HA of the reinforcement H and a plane region image (image D12) by the rear reinforcement HB. The image D10 is a three-dimensional image that is the basis of the image D11 and the image D12. Since the distance to the stereo camera 100 of the front reinforcing bar HA is shorter than that of the rear reinforcing bar HB, the size of the reinforcing bar is displayed larger than that of the rear reinforcing bar HB. That is, the image D11 has a larger display area than the image D12. That is, the plane having the largest number N_tmp is the frontmost plane.

The front parameter detection process described above can be summarized as follows.
-Select any three or more points from the input three-dimensional data, and calculate the plane parameters based on those points.
-For the input three-dimensional data, the distance to the calculated plane is calculated, and the number of points whose distance is equal to or less than the threshold value is counted.
-A pair of plane parameters and numbers by repeating the above plane parameter calculation and counting the number of points whose distance to the plane is less than the threshold value a predetermined number of times while reselecting any three or more points. To calculate multiple sets.
-From the above plane parameter and number pairs, the plane parameter of the pair with the largest number is acquired as the plane corresponding to the front surface of the bar arrangement.

Then, according to the above-mentioned front parameter detection process, automatic detection is performed by utilizing the fact that the three-dimensional point data corresponding to the front surface is the largest in the acquired three-dimensional data, so that the front surface arrangement is surely performed. Muscles can be detected.

<Second Embodiment>
Next, the second embodiment will be described. In the above-mentioned front parameter detection process, the plurality of plane detection units 34 are designed to remove the floor surface and the wall surface from the temporary plane in advance. Further, in the second embodiment, the three-dimensional data separated from the three-dimensional data generation device (stereo camera 100) by a predetermined distance or more is excluded from the set φ of the three-dimensional points used by the plurality of plane detection units 34. This is because the measurement target is the frontmost bar arrangement, so that the three-dimensional point located behind the stereo camera 100 by a predetermined value or more is unnecessary.

The second embodiment has many parts in common with the first embodiment described up to FIG. 9. Hereinafter, the parts peculiar to the second embodiment will be mainly described. FIG. 10 is a functional block diagram relating to the bar arrangement inspection process in the second embodiment.

The inspection support device 30b of the second embodiment is an addition of the three-dimensional data removal unit 70 to the inspection support device 30 of the first embodiment. The three-dimensional data removing unit 70 identifies three-dimensional data separated from the three-dimensional data generator (stereo camera 100) by a predetermined distance or more, excludes the specified three-dimensional data from the set φ of three-dimensional points, and specifies the specified third order. The set φ of the three-dimensional points excluding the original data is output to the plurality of plane detection units 34. The predetermined distance is, for example, 3 m when the distance to the front bar arrangement HA is 2 m.

FIG. 11 is a flowchart illustrating the procedure of the front parameter detection process in the second embodiment. Steps S80 to S86 are processes specific to the second embodiment. Steps S100 to S114 are the same as those in the first embodiment.

The three-dimensional data removal unit 70 reads out three-dimensional points one by one from the set φ of three-dimensional points, and performs the following processes of steps S80 to S86.

The three-dimensional data removing unit 70 calculates the distance K between the three-dimensional point and the stereo camera 100 from the coordinates of the three-dimensional point (x, y, z) (step S80). The three-dimensional data removal unit 70 determines whether K <P (step S82). P is a value obtained by adding a certain margin value to the distance to the front bar arrangement HA located at the foremost surface. The distance to the front bar arrangement HA may be a distance measurement value obtained by the stereo camera 100 or an input value from the photographer.

When the three-dimensional data removing unit 70 determines that K <P is not satisfied (NO in step S82), the three-dimensional data removing unit 70 removes the three-dimensional point (step S84) and proceeds to step S86. This is because it can be determined that the three-dimensional point is not included in the front bar arrangement HA.

When the three-dimensional data removing unit 70 determines that K <P (YES in step S82), it determines whether or not the processing for all the three-dimensional points has been completed (step S86). When the three-dimensional data removing unit 70 determines that the processing for all the three-dimensional points has not been completed (NO in step S86), the process returns to step S80. When the three-dimensional data removing unit 70 determines that the processing for all the three-dimensional points is completed (YES in step S86), the process proceeds to step S100. Since steps S100 and subsequent steps have already been explained, they will be omitted.

According to the second embodiment, the three-dimensional data removing unit 70 can efficiently exclude the three-dimensional data due to the bar arrangement on the back side and the wall surface. By excluding unnecessary 3D points in advance, the number of 3D data is reduced and the time required for the front parameter detection process is shortened. The removal process described above may be performed in the plurality of plane detection units 34 (in the RANSAC process).

<Modification example>
Although the information processing device 10 and the stereo camera 100 (three-dimensional data generation device) have been described as separate bodies in FIG. 1, they may be integrated devices (tablet terminals with a built-in stereo camera). Further, although the explanation has been made that the inspection support device 30 (30b) is realized by software processing, the present invention is not limited to this. The inspection support device 30 (30b) may be partially or wholly executed by hardware processing (for example, a gate array circuit).

The present invention is not limited to the above-described embodiment as it is, and the components can be modified and embodied within a range that does not deviate from the gist at the implementation stage. In addition, various inventions can be formed by an appropriate combination of the plurality of components disclosed in the above-described embodiment. For example, all the components shown in the embodiments may be combined as appropriate. In addition, components across different embodiments may be combined as appropriate. It goes without saying that various modifications and applications are possible within the range that does not deviate from the gist of the invention.

From the above description, the following can be mentioned as typical viewpoints of the present invention other than those described in the claims.

(1) In an inspection support device that supports inspection of the skeleton of a building and civil engineering structure, three-dimensional data of the structure including a plurality of planes formed by the skeleton is acquired, and the acquired three-dimensional data is obtained. From the above, a plurality of first planes containing at least three points of the three-dimensional data are detected, and the number of three-dimensional points whose distance from the first plane is equal to or less than a predetermined value is calculated for each of the detected first planes. Then, based on the calculated number of the three-dimensional points, the second plane located in the foreground in the skeleton of the structure is specified from among the plurality of detected first planes. Inspection support device.

(2) Among the plurality of detected first planes, the first plane having the largest number of calculated three-dimensional points is specified as the second plane (1). The inspection support device according to 1).

(3) The acquired three-dimensional data includes data irrelevant to the second plane, and is characterized in that the second plane is specified by the RANSAC algorithm from the acquired three-dimensional data. The inspection support device according to (1) or (2).

(4) The three-dimensional data is generated from the data obtained by the three-dimensional sensor, and from the acquired three-dimensional data, a three-dimensional point separated from the three-dimensional sensor by a predetermined distance or more. The inspection support device according to any one of (1) to (3), characterized in that the first plane is detected by removing the above.

(5) In an inspection support device that supports inspection of the skeleton of a building or civil engineering structure, a three-dimensional information acquisition unit that acquires three-dimensional data of the structure including a plurality of planes formed by the skeleton, and acquisition A plurality of first planes containing at least three points of the three-dimensional data are detected from the three-dimensional data, and the distance from the first plane is 3 or less for each of the detected first planes. A plurality of plane detection units for calculating the number of three-dimensional points, and a position in the foreground in the skeleton of the structure from among the plurality of detected first planes based on the calculated number of three-dimensional points. An inspection support device comprising a front surface specifying portion for specifying a second plane to be used.

(6) The plurality of plane detection units are provided with a three-dimensional data removal unit that removes three-dimensional points separated from the acquired three-dimensional data by a predetermined distance or more from the sensor for generating the three-dimensional data. The inspection support device according to (5), wherein a plurality of first planes including at least three points of the three-dimensional data are detected based on the remaining three-dimensional data removed.

(7) In the inspection support method for supporting the inspection of the skeleton of the building and civil engineering structures, the three-dimensional data of the structure including a plurality of planes formed by the skeleton is acquired, and the acquired three-dimensional data is obtained. From the above, a plurality of first planes containing at least three points of the three-dimensional data are detected, and the number of three-dimensional points whose distance from the first plane is equal to or less than a predetermined value is calculated for each of the detected first planes. Then, based on the calculated number of the three-dimensional points, the second plane located in the foreground in the skeleton of the structure is specified from among the plurality of detected first planes. Inspection support method.

(8) In a program that causes a computer to execute an inspection support method that supports inspection of the skeleton of a building and civil engineering structure, three-dimensional data of the structure including a plurality of planes formed by the skeleton is acquired and acquired. A plurality of first planes containing at least three points of the three-dimensional data are detected from the three-dimensional data, and the distance to the first plane is less than or equal to a predetermined value for each of the detected first planes. The number of original points is calculated, and based on the calculated number of three-dimensional points, a second plane located in the foreground in the skeleton of the structure from among the plurality of detected first planes. A program characterized by identifying.

1 Reinforcement inspection system 10 Information processing device 30, 30b Inspection support device 32 Three-dimensional information acquisition unit 34 Multiple plane detection unit 36 Front surface identification unit 38 Plane area image creation unit 40 Reinforcing bar placement specification unit 42 Measurement unit 50 Front parameter detection device 70 3D data removal unit 100 Stereo camera 110R Right image unit 110L Left image unit 120 3D data generation unit 510 CPU
520 RAM
530 ROM
540 I / O IF
550 Communication unit 560 Operation unit 570 Display unit 580 Bus 600 Storage unit

Claims (5)

In the inspection support device that supports the inspection of the skeleton of buildings and civil engineering structures
Obtain three-dimensional data of the structure including a plurality of planes formed by the skeleton, and obtain
A plurality of first planes including at least three three-dimensional points extracted from the acquired three-dimensional data are detected, and each of the detected first planes is a three-dimensional point belonging to the first plane . Calculate each number and
An inspection characterized in that a second plane to be measured in the skeleton of the structure is specified from among the plurality of detected first planes based on the calculated number of the three-dimensional points. Support device. In the inspection support device that supports the inspection of the skeleton of buildings and civil engineering structures
Obtain three-dimensional data of the structure including a plurality of planes formed by the skeleton, and obtain
A plurality of first planes containing at least three points of the three-dimensional data are detected from the acquired three-dimensional data, and the distance to the first plane is equal to or less than a predetermined value for each of the detected first planes . Calculate the number of 3D points,
An inspection characterized in that a second plane to be measured in the skeleton of the structure is specified from among the plurality of detected first planes based on the calculated number of the three-dimensional points. Inspection support device. In the inspection support device that supports the inspection of the skeleton of buildings and civil engineering structures
A three-dimensional information acquisition unit that acquires three-dimensional data of the structure including a plurality of planes formed by the skeleton, and
A plurality of first planes including at least three three-dimensional points extracted from the acquired three-dimensional data are detected, and each of the detected first planes is a three-dimensional point belonging to the first plane . A multi-plane detector that calculates the number of each
A front surface specifying portion for specifying a second plane to be measured in the skeleton of the structure from among the plurality of detected first planes based on the calculated number of the three-dimensional points is provided.
An inspection support device characterized by this. In the inspection support method that supports the inspection of the skeleton of buildings and civil engineering structures
Obtain three-dimensional data of the structure including a plurality of planes formed by the skeleton, and obtain
A plurality of first planes including at least three three-dimensional points extracted from the acquired three-dimensional data are detected, and each of the detected first planes is a three-dimensional point belonging to the first plane . Calculate each number and
An inspection characterized in that a second plane to be measured in the skeleton of the structure is specified from among the plurality of detected first planes based on the calculated number of the three-dimensional points. Support method. In a program that causes a computer to execute an inspection support method that supports inspection of the skeleton of buildings and civil engineering structures.
Obtain three-dimensional data of the structure including a plurality of planes formed by the skeleton, and obtain
A plurality of first planes including at least three three-dimensional points extracted from the acquired three-dimensional data are detected, and each of the detected first planes is a three-dimensional point belonging to the first plane . Calculate each number and
A program characterized by identifying a second plane to be measured in the skeleton of the structure from among the plurality of detected first planes based on the calculated number of the three-dimensional points. ..