Three-dimensional shape measuring device and three-dimensional shape measuring method

Abstract

To provide a three-dimensional shape measuring device and a three-dimensional shape measuring method using an imaging device.SOLUTION: A three-dimensional shape measuring device 11 measures the three-dimensional shape of an object to be measured, and is mounted on a vehicle capable of traveling on a track. The device includes at least two line sensor cameras 31a, 31b that image the object to be measured, an optical flow calculation unit 41 that identifies corresponding points in each image captured by the at least two line sensor cameras 31a, 31b and calculates the optical flow of the corresponding points, and a distance calculation unit 42 that calculates the height of the object to be measured based on the optical flow calculated by the optical flow calculation unit 41. The line sensor cameras 31a, 31b are mounted so that the angles of optical axes 51a, 51b of the line sensor cameras 31a and 31b with respect to the traveling direction of the vehicle are different and intersect with each other.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a three-dimensional shape measuring device and a three-dimensional shape measuring method. [Background technology]

[0002] For example, when the temperature rises significantly on sunny summer days, the rails may move in a direction that would cause them to buckle. To prevent this, sleepers are buried in the track bed to restrict their lateral movement. The track bed is provided with a raised ballast "excess bank."

[0003] As a method for checking whether the trackbed "excess reinforcement" is properly raised, a technology is known in which a laser is projected from a running track inspection vehicle onto the track surface formed by piling up ballast, to measure the shape of the ballast, particularly the height of the trackbed excess reinforcement and the shoulder width of the trackbed (Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-015423 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the invention described in Patent Document 1, a laser sensor must be provided separately in addition to the imaging device that captures the two-dimensional image, which can make the system large-scale.

[0006] The present invention has been made in view of the above problems, and has as its object to provide a three-dimensional shape measuring device and a three-dimensional shape measuring method using an imaging device. [Means for solving the problem]

[0007] A three-dimensional shape measuring device according to one aspect of the present invention is a three-dimensional shape measuring device for measuring the three-dimensional shape of an object to be measured, and is mounted on a vehicle capable of traveling on a track, and comprises at least two image capturing units for capturing images of the object to be measured, an optical flow calculation unit for identifying corresponding points in each image captured by the at least two image capturing units and calculating the optical flow of the corresponding points, and a distance calculation unit for calculating the height of the object to be measured based on the optical flow calculated by the optical flow calculation unit, and is characterized in that the angles of the optical axes of the image capturing units relative to the direction of travel of the vehicle are different and intersect.

[0008] A three-dimensional shape measurement method according to one aspect of the present invention is a three-dimensional shape measurement method for measuring the three-dimensional shape of a part to be measured, and includes an imaging step in which at least two imaging units are installed on a vehicle capable of running on a track and photograph the object to be measured; an optical flow calculation step in which corresponding points in each image photographed by the at least two imaging units are identified and the optical flow of the corresponding points is calculated; and a distance calculation step in which the height of the object to be measured is calculated based on the optical flow calculated by the optical flow calculation step, and the imaging units are installed so that the angles of the optical axes of the imaging units relative to the direction of travel of the vehicle are different and intersect. [Effects of the Invention]

[0009] According to the present invention, the three-dimensional shape of an object to be measured can be measured using an image obtained by an imaging device. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing an example of use of a three-dimensional shape measuring device 11. [Figure 2] FIG. 2 is a diagram for explaining the track 12. As shown in FIG. [Figure 3] FIG. 3 is a block diagram showing the internal configuration of the three-dimensional shape measuring device 11. [Figure 4] FIG. 4 is a diagram showing how the line sensor cameras 31a and 31b photograph the surface of the track 12. As shown in FIG. [Figure 5] FIG. 5 is a diagram showing the line sensor cameras 31a and 31b photographing the object to be measured, viewed obliquely from above. [Figure 6] FIG. 6 is a diagram showing a side view of the line sensor cameras 31a and 31b capturing an image of the object to be measured at time t0, and also shows image frames F1-0 and F2-0 obtained at time t0. [Figure 7] FIG. 7 is a diagram showing a side view of the line sensor cameras 31a and 31b capturing an image of the object to be measured at time t1, and also shows image frames F1-1 and F2-1 obtained at time t1. [Figure 8] FIG. 8 is a diagram showing a side view of the line sensor cameras 31a and 31b capturing an image of the object to be measured at time t2, and also shows image frames F1-2 and F2-2 obtained at time t2. [Figure 9] FIG. 9 is a diagram showing a side view of the line sensor cameras 31a and 31b capturing an image of the object to be measured at time t3, and also shows image frames F1-3 and F2-3 obtained at time t3. [Figure 10] FIG. 10 is a diagram showing a side view of the line sensor cameras 31a and 31b capturing an image of the object to be measured at time t4, and also shows image frames F1-4 and F2-4 obtained at time t4. [Figure 11] FIG. 11 is a diagram showing a side view of the line sensor cameras 31a and 31b capturing an image of the object to be measured at time t5, and also shows image frames F1-5 and F2-5 obtained at time t5. [Figure 12] FIG. 12 is a diagram showing the composite images Wa and Wb. [Figure 13] FIG. 13 is a diagram showing corresponding points and optical flows in the composite images Wa and Wb. [Figure 14] FIG. 14 is a diagram for explaining the calculation of the height h of the object to be measured 62. In FIG. [Figure 15] FIG. 15 is a diagram for explaining the flow of the projection process performed by the three-dimensional shape measuring device 11. [Figure 16]FIG. 16 is a diagram showing an example of a three-dimensional image of the track bed 23. DETAILED DESCRIPTION OF THE INVENTION

[0011] [One embodiment] A three-dimensional shape measuring device according to an embodiment of the present invention will be described below. Fig. 1 is a diagram showing an example of use of a three-dimensional shape measuring device 11.

[0012] The three-dimensional shape measuring device 11 has two line sensor cameras 31a and 31b (hereinafter, when there is no need to distinguish between them individually, they will simply be referred to as line sensor cameras 31; the same applies to other cases) that are installed at the bottom of the vehicle 13 and serve as two photographing units that photograph the track 12 from above.

[0013] The three-dimensional shape measuring device 11 measures the three-dimensional shape near the track bed 23 (FIG. 2) based on image data captured by the line sensor camera 31 when the vehicle 13 travels on the track 12.

[0014] As shown in FIG. 2, the track 12 is laid by burying sleepers 22 in a ballast-filled trackbed 23, and fastening rails 21 placed on the sleepers 22 to predetermined rail support parts. For example, on sunny summer days, the temperature of the rails 21 rises significantly, and there is a risk that the rails 21 will buckle as they move forward. Therefore, by burying the sleepers 22 in the trackbed 23, resistance to lateral movement of the sleepers 22 (ballast lateral resistance) is provided, preventing the rails 21 from buckling. In particular, the lateral resistance of the sleepers 22 is increased by providing "reinforcements" made of raised ballast on the shoulders on both sides of the trackbed 23. Therefore, the three-dimensional shape of the trackbed 23 is periodically measured to check whether the "reinforcements" of the trackbed 23 are properly raised and to repair any collapsed ballast.

[0015] (Internal configuration of the three-dimensional shape measuring device 11) 3 is a block diagram showing the internal configuration of three-dimensional shape measuring device 11. Three-dimensional shape measuring device 11 is configured to include line sensor cameras 31a and 31b, a control unit 32, and a storage unit 33.

[0016] The line sensor camera 31 captures the track 12, and synthesizes the resulting image data (hereinafter referred to as an image frame) for one line by arranging them in chronological order to generate a composite image, which is then supplied to the control unit 32.

[0017] The line sensor cameras 31a and 31b are disposed on the underside of the body of the vehicle 13, inside the left and right wheels, and disposed at the front and rear in the traveling direction of the vehicle 13 (FIG. 1). The line sensor cameras 31a and 31b are also disposed so that the angles of the optical axes 51a and 51b of the line sensor cameras 31a and 31b are different and intersect, as shown in FIG.

[0018] It is preferable that the imaging range of each of the line sensor cameras 31a and 31b includes the entire width of the trackbed 23. This is to measure the three-dimensional shape of the entire trackbed 23. Furthermore, the position where the optical axes 51a and 51b of the line sensor cameras 31a and 31b intersect is not particularly limited, but it is preferable that it be a position equivalent to the lowest point of the trackbed 23. This is because, as will be described later, the position where the optical axes 51a and 51b of the line sensor cameras 31a and 31b intersect becomes the reference position in the height direction of the three-dimensional shape.

[0019] The control unit 32 is composed of a CPU (Central Processing Unit), a memory section (e.g., ROM (Read Only Memory), RAM (Random Access Memory), non-volatile memory), and other elements including hardware. The control unit 32 executes a control application program (not shown) stored in the memory unit 33 to control the entire three-dimensional shape measuring device 11 and also functions as an optical flow calculation unit 41, a distance calculation unit 42, and a three-dimensional image creation unit 43.

[0020] The optical flow calculation unit 41 identifies corresponding points in the two composite images supplied from the line sensor cameras 31a and 31b by a matching process, and calculates the optical flow of the corresponding points based on the amount of movement of the corresponding points in the two composite images.

[0021] The distance calculation unit 42 calculates the three-dimensional shape of the track bed 23 based on the optical flow of the corresponding points calculated by the optical flow calculation unit 41.

[0022] The three-dimensional image creation unit 43 creates a three-dimensional composite image of the track bed 23 based on the composite image and the three-dimensional shape calculated by the distance calculation unit 42.

[0023] The storage unit 33 includes, for example, a read-only memory (ROM), a random access memory (RAM), and a non-volatile memory. The storage unit 33 stores the control application program described above, various data required for its execution, and information generated by processing. The stored information is output to an external device such as a PC via a communication interface including, for example, a communication integrated circuit (IC) and a communication connector.

[0024] (Principle of 3D shape measurement processing) Next, the principle of the three-dimensional shape measurement process performed by three-dimensional shape measuring device 11 will be described with reference to FIGS.

[0025] ((Image acquisition)) 5 is a diagram seen from diagonally above showing how the line sensor cameras 31a and 31b capture images of the objects to be measured 61 to 63. In this example, the line sensor cameras 31a and 31b move in the direction of the arrow (Y-axis direction) at a predetermined speed, and capture images of the objects to be measured 61, 62, and 63 at a predetermined scan rate.

[0026] The line sensor cameras 31a and 31b are installed in front of and behind each other in the traveling direction. The optical axis 51a of the line sensor camera 31a is installed so as to be perpendicular to the object 61 to be measured, and the optical axis 51b of the line sensor camera 31b is installed so as to be inclined rearward in the traveling direction by an angle θ with respect to the optical axis 51a of the line sensor camera 31a. An intersection 51c of the optical axes 51a and 51b of the line sensor cameras 31a and 31b is located on the top surface of the object 61 to be measured (hereinafter also referred to as the reference surface 61). The imaging ranges of the line sensor cameras 31a and 31b are the same.

[0027] Sample points p1 to p5 are arbitrary points provided for the convenience of explaining the principle, and will be referred to as sample points p when there is no need to distinguish between them. Sample points p1 and p3 are points on reference surface 61. Sample points p2 and p4 are points on the top surface of object 62 to be measured. Sample point p5 is a point on the top surface of object 63 to be measured. Sample points p1 and p2, and sample points p3, p4, and p5 have different x-coordinate values ​​but the same y-coordinate value.

[0028] 6 to 11 are side views showing how line sensor cameras 31a and 31b capture images of objects to be measured 61 to 63 at times t0 to t5, and are also diagrams showing image frames F1 and F2 obtained by image capture by line sensor cameras 31a and 31b at those times.

[0029] 6 at time t0, the line sensor cameras 31a and 31b capture images of the portions of the objects to be measured 61 and 62 that are on the optical axes 51a and 51b at that time. Since the sample point p does not exist on the optical axes 51a and 51b of the line sensor cameras 31a and 31b, the image frames F1-0 and F2-0 obtained by the image capture by the line sensor cameras 31a and 31b at that timing do not include an image of the sample point p.

[0030] 7, at time t1, line sensor cameras 31a and 31b capture images of portions of measurement objects 61 and 62 that are on optical axes 51a and 51b at that time. Sample points p1 and p2 are located on optical axis 51a of line sensor camera 31a, and therefore, image frame F1-1 obtained by image capture by line sensor camera 31a at that timing includes images of sample points p1 and p2. On the other hand, only sample point p1 is located on optical axis 51b of line sensor camera 31b, and therefore, sample point p2 is not located on optical axis 51b of line sensor camera 31b, and therefore, image frame F2-1 obtained by image capture by line sensor camera 31b at that timing includes only the image of sample point p1.

[0031] 8, at time t2, the line sensor cameras 31a and 31b capture images of the portions of the objects to be measured 61 and 62 that are on the optical axes 51a and 51b at that time. Because sample point p does not exist on the optical axis 51a of the line sensor camera 31a, an image of the sample point is not included in the image frame F1-2 obtained by image capture by the line sensor camera 31a at that timing. On the other hand, because sample point p2 exists on the optical axis 51b of the line sensor camera 31b, an image of sample point p2 is included in the image frame F2-2 obtained by image capture by the line sensor camera 31b at that timing.

[0032] 9 at time t3, line sensor cameras 31a and 31b capture images of portions of measurement objects 61, 62, and 63 that are located on optical axes 51a and 51b at that time. Sample points p3, p4, and p5 are located on optical axis 51a of line sensor camera 31a, and therefore, image frame F1-3 obtained by image capture by line sensor camera 31a at that timing includes images of sample points p3, p4, and p5. On the other hand, only sample point p3 is located on optical axis 51b of line sensor camera 31b, and therefore, points p4 and p5 are not located on optical axis 51b of line sensor camera 31b, and therefore, image frame F2-3 obtained by image capture by line sensor camera 31b at that timing includes only the image of sample point p3.

[0033] 10, at time t4, the line sensor cameras 31a and 31b capture images of the portions of the objects to be measured 61, 62, and 63 that are on the optical axes 51a and 51b at that time. Because sample point p does not exist on the optical axis 51a of the line sensor camera 31a, the image frame F1-4 obtained by the image capture by the line sensor camera 31a at that timing does not include an image of sample point p. On the other hand, because only sample point p4 exists on the optical axis 51b of the line sensor camera 31b, the image frame F2-4 obtained by the image capture by the line sensor camera 31b at that timing includes only an image of sample point p4.

[0034] 11, at time t5, the line sensor cameras 31a and 31b capture images of the portions of the objects to be measured 61, 62, and 63 that are on the optical axes 51a and 51b at that time. Because sample point p does not exist on the optical axis 51a of the line sensor camera 31a, the image frame F1-5 obtained by the image capture by the line sensor camera 31a at that timing does not include an image of sample point p. On the other hand, because sample point p5 exists on the optical axis 51b of the line sensor camera 31b, the image frame F2-5 obtained by the image capture by the line sensor camera 31b at that timing includes only an image of sample point p5.

[0035] The line sensor cameras 31a and 31b combine the image frames F1 and F2 obtained by imaging described with reference to FIGS. 6 to 11 in chronological order to generate a composite image, and supply the composite image to the storage unit 33. As shown in FIG. 12A, the line sensor camera 31a combines the image frames F1-1 to F1-5 obtained by imaging in chronological order to generate a composite image Wa, and supplies the composite image Wa to the storage unit 33. As shown in FIG. 12B, the line sensor camera 31b combines the image frames F2-0 to F2-5 obtained by imaging in chronological order to generate a composite image Wb, and supplies the composite image Wb to the storage unit 33.

[0036] ((Optical flow calculation)) The optical flow calculation unit 41 identifies corresponding points in the composite images supplied from the line sensor cameras 31a and 31b stored in the storage unit 33 at a predetermined timing through a matching process, and calculates the optical flow of the corresponding points based on the movement amounts of the corresponding points in the two composite images. Specifically, the optical flow calculation unit 41 detects characteristic points in each composite image using a feature point detection algorithm. Next, the optical flow calculation unit 41 assigns a descriptor having a characteristic unique to each detected feature point to each pixel. The descriptor is described by combining information such as the brightness gradient within the image patch surrounding the feature point, the feature orientation, and color information. The optical flow calculation unit 41 then evaluates the similarity of the descriptors between the feature points detected in one composite image and the feature points detected in the other composite image, and identifies the feature points with the highest similarity as corresponding points.

[0037] 12 and 13, the images at sample points p1 to p5 of composite image Wa captured by line sensor camera 31a and the images at sample points p1 to p5 of composite image Wb captured by line sensor camera 31b are identified as corresponding points. Images other than the sample point p are also associated based on the feature amounts.

[0038] Once corresponding points in the composite images supplied from each of the line sensor cameras 31a and 31b have been identified in this manner, the optical flow calculation unit 41 calculates the optical flow of the identified corresponding points. Regarding the images of sample points p1 to p5, as shown in FIG. 13, the optical flow calculation unit 41 identifies the coordinates of the images of sample points p1 to p5 in the two composite images Wa and Wb, and expresses the pixel movement amount in the Y-axis direction of the coordinates of the same points in pixel units (px) to obtain the optical flow. When comparing the image of sample point p1 between the two composite images Wa and Wb, the movement amount (p1-p1) in the Y-axis direction is zero, so the optical flow is 0px. The image of sample point p2 has moved by the movement amount (p2-p2) in the Y-axis direction, so the optical flow is 1000px, which corresponds to that movement amount. The image of sample point p3 has the movement amount (p3-p3) in the Y-axis direction is zero, so the optical flow is 0px. The image at sample point p4 has moved by the amount of movement (p4-p4) in the Y-axis direction, so the optical flow is 1000px according to that amount of movement. The image at sample point p5 has moved by the amount of movement (p5-p5) in the Y-axis direction, so the optical flow is 2000px according to that amount of movement.

[0039] After calculating the optical flow of the corresponding points in this way, the optical flow calculation unit 41 supplies the calculated optical flow to the distance calculation unit 42.

[0040] ((3D shape calculation)) The distance calculation unit 42 calculates the three-dimensional shape of the object to be measured based on the optical flow supplied from the optical flow calculation unit 41.

[0041] The distance calculation unit 42 calculates the height of the object to be measured. Specifically, by using the fact that the horizontal camera movement amount (movement amount in the Y-axis direction in FIG. 1) during one scan of the line sensor camera 31 is 1 px, the physical length [mm] per 1 px is calculated using the movement speed and frame rate of the line sensor camera 31 as reference values ​​(Equation (1)). For example, if the movement speed of the line sensor camera 31 is 8 m / s and the scan rate is 40,000 Hz, the physical length [mm] per 1 px is 0.2 mm. 1[px]=1000v / f[mm] (1) (v: running speed [m / s], f: scan rate [Hz])

[0042] Next, the optical flow is converted to a physical length [mm] based on the optical flow and the physical length [mm] per 1px. For example, if the optical flow is 1000px and 1px is 0.2mm, the physical length is 200mm.

[0043] Then, using the principle of trigonometric functions, the height (Z axis) of the object to be measured from the reference surface 61 is calculated (Equation (2)). As shown in Fig. 14, the height h of the object to be measured 62, for example, is obtained using the optical flow M and the angle θ between the optical axes 51a and 51b of the line sensor cameras 31a and 31b. For example, if the optical flow of the sample point p2 is 200 mm and the angle between the optical axes 51a and 51b of the line sensor cameras 31a and 31b is 30 degrees, the height of the object to be measured 62 from the reference surface 61 is 200 / 0.577...≈346.6 mm. h [mm] = M [mm] / tanθ (2)

[0044] Next, distance calculation section 42 calculates the width (X axis) and length in the traveling direction (Y axis) of objects to be measured 61 to 63 using the pixel size in the composite image.

[0045] Specifically, distance calculation unit 42 acquires pixel sizes corresponding to the width direction (X axis) and length direction (Y axis) of measurement objects 61-63 extracted from the composite image obtained by imaging with vertically installed line sensor camera 31, and obtains the width direction (X axis) and length direction (Y axis) of the measurement objects in real scale based on the physical length per 1 px obtained from equation (1). For example, if the pixel sizes corresponding to the width direction and length direction of the composite image obtained by imaging with line sensor camera 31 are 10,000 px and 20,000 px, respectively, and 1 px is 0.2 mm, the real scales of the width direction (X axis) and length direction (Y axis) of the measurement objects are 2,000 mm and 4,000 mm, respectively.

[0046] After calculating the three-dimensional lengths (distances) of the objects to be measured 61 to 63 in this manner, distance calculation unit 42 supplies the calculation results to three-dimensional image creation unit 43. Three-dimensional image creation unit 43 creates a three-dimensional image based on the composite image and the distance information supplied from distance calculation unit 42.

[0047] According to the above-mentioned principle, the two line sensor cameras 31a and 31b can measure the three-dimensional shape of the object to be measured. Using this principle, the three-dimensional shape measuring device 11 measures the three-dimensional shape near the track bed 23 (Fig. 2) using the two line sensor cameras 31a and 31b mounted on a vehicle 13 traveling on a track 12 as shown in Fig. 1. In this case, by setting the position where the optical axes 51a and 51b of the line sensor cameras 31a and 31b intersect at the lowest point of the track bed 23, the height of the "excess fill" from that position can be calculated.

[0048] (3D shape measurement processing) Next, the three-dimensional shape measurement process performed by the three-dimensional shape measuring device 11 will be described with reference to the flowchart of FIG.

[0049] At a predetermined timing while the vehicle 13 is traveling, in step S1, the line sensor camera 31 of the three-dimensional shape measuring device 11 starts capturing images. The line sensor camera 31 acquires image frames including images of the track 12 obtained as a result of the capturing, and appropriately combines the image frames to generate a composite image ( FIG. 12 ). The line sensor cameras 31 a and 31 b supply the generated composite image to the storage unit 33.

[0050] In step S2, the control unit 32 determines whether or not the image capturing has ended. The control unit 32 may determine that the image capturing has ended when the vehicle 13 has stopped, or may determine that the image capturing has ended when the operator operates an operation unit (not shown) to instruct the end of the image capturing.

[0051] If it is determined in step S2 that the photographing has ended, in step S3, the optical flow calculation unit 41 of the control unit 32 identifies corresponding points in the two composite images supplied from the line sensor cameras 31a and 31b stored in the memory unit 33 by a matching process (Figure 13).

[0052] In step S4, the optical flow calculation unit 41 calculates an optical flow based on the amount of movement of the identified corresponding point in the Y-axis direction (FIG. 13). The optical flow calculation unit 41 supplies the calculated optical flow to the distance calculation unit .

[0053] In step S5, the distance calculation unit 42 calculates (FIG. 14) the three-dimensional shape of the vicinity of the track bed 23 (FIG. 2) based on the optical flow of the corresponding points supplied from the optical flow calculation unit 41. The heights of the sleepers 22 and the "excess reinforcement" of the track bed 23, etc. are calculated.

[0054] In step S6, the three-dimensional image creation unit 43 creates a three-dimensional image based on the composite image and the distance information calculated by the distance calculation unit 42. Fig. 16 is an example of a three-dimensional image of the vicinity of the track bed 23 (Fig. 2).

[0055] The process then ends.

[0056] The composite image, height information, and three-dimensional image are stored in the storage unit 33, and the worker can output the information stored in the storage unit 33 to a PC or the like as needed.

[0057] [Other Examples] (Photography Department) In the above, an example has been described in which the line sensor camera 31 is used, but a handheld camera can be used instead of the line sensor camera 31. Although equation (1) cannot be directly applied to a handheld camera, for example, it is possible to photograph an object to be measured with known dimensions and determine the physical length per 1 px using the known dimensions as a reference value.

[0058] (Another example of vehicle 13) In the above description, the three-dimensional shape measuring device 11 is installed on the vehicle 13 to measure the three-dimensional shape of the track bed 23, but various other applications are conceivable. For example, the device may be installed on an automobile to measure the three-dimensional shape of the road.

[0059] [Supplementary explanation of the embodiment] The above-described embodiments each show a preferred specific example of the present invention. The numerical values, components, arrangement positions and connection order of components, processing order in flowcharts, etc. shown in the following embodiments are merely examples and are not intended to limit the present invention. Furthermore, each figure is not necessarily a strict illustration.

[0060] The above-described series of processes can be executed by hardware or software. When the series of processes is executed by software, the program constituting the software is installed from a program recording medium into a computer incorporated in dedicated hardware, or into, for example, a general-purpose personal computer that can execute various functions by installing various programs.

[0061] The program executed by the computer may be a program that processes in chronological order according to the order described in this specification, or may be a program that processes in parallel or at the required timing, such as when called.

[0062] [Contents described in the embodiment] The contents of the above-described embodiments can be understood, for example, as follows.

[0063] The above-mentioned three-dimensional shape measuring device 11 is A three-dimensional shape measuring device 11 for measuring a three-dimensional shape of an object to be measured, At least two line sensor cameras 31a and 31b are provided on a vehicle that can travel on a track and capture images of the object to be measured; an optical flow calculation unit 41 that identifies corresponding points in each image captured by at least two line sensor cameras 31 a and 31 b and calculates the optical flow of the corresponding points; a distance calculation unit 42 that calculates the height of the object to be measured based on the optical flow calculated by the optical flow calculation unit 41; Equipped with The line sensor cameras 31a and 31b are provided such that the angles of the optical axes 51a and 51b of the line sensor cameras 31a and 31b with respect to the traveling direction of the vehicle are different and intersect with each other.

[0064] In this way, the two line sensor cameras 31a and 31b are arranged so that the angles of the optical axes 51a and 51b of the line sensor cameras 31a and 31b with respect to the movement direction are different and intersect, so that the optical flow can be calculated using the image frames obtained by the line sensor cameras 31a and 31b. As a result, the three-dimensional shape of the object can be measured based on the calculated optical flow.

[0065] Furthermore, since the line sensor cameras 31a and 31b can be used, a long object to be measured can be photographed with uniform brightness compared to, for example, a stereo camera, and the track bed 23 can be photographed more appropriately. [Explanation of symbols]

[0066] 11 3D shape measuring device 12 orbits 13 vehicles 21 Rail 22 sleepers 23 Road bed 31a Line sensor camera 31b Line sensor camera 32 Control section 33 Storage section 41 Optical flow calculation unit 42 Distance calculation unit 43 3D Image Creation Department

Claims

1. A three-dimensional shape measuring apparatus for measuring a three-dimensional shape of an object to be measured, At least two imaging units are provided on a vehicle that can travel on a track and that capture images of the object to be measured; an optical flow calculation unit that identifies corresponding points in each image captured by the at least two image capture units and calculates an optical flow of the corresponding points; a distance calculation unit that calculates the height of the object based on the optical flow calculated by the optical flow calculation unit; Equipped with The photographing units are provided so that the angles of the optical axes of the photographing units with respect to the traveling direction of the vehicle are different and intersect with each other. A three-dimensional shape measuring device characterized by:

2. 2. The three-dimensional shape measuring apparatus according to claim 1, The photographing unit is a line sensor camera. A three-dimensional shape measuring device characterized by:

3. A three-dimensional shape measuring method for measuring a three-dimensional shape of an object to be measured, comprising: an imaging step of imaging the object to be measured by at least two imaging units provided on a vehicle capable of traveling on a track; an optical flow calculation step of identifying corresponding points in each image captured by the at least two image capturing units and calculating an optical flow of the corresponding points; a distance calculation step of calculating a height of the object based on the optical flow calculated in the optical flow calculation step; Including, The photographing units are provided so that the angles of the optical axes of the photographing units with respect to the traveling direction of the vehicle are different and intersect with each other. A three-dimensional shape measuring method characterized by:

Images