Position estimation method, position estimation system, camera, and program

Abstract

To provide a position estimation method and the like that can easily estimate a position of a viewpoint when an image for photogrammetry is captured.SOLUTION: A position estimation method includes: acquiring a first image obtained by capturing at a first viewpoint, and a first atmospheric pressure at the first viewpoint (S11); acquiring a second image obtained by capturing at a second viewpoint different from the first viewpoint, and a second atmospheric pressure at the second viewpoint (S12); calculating a distance in a vertical direction between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure (S13); estimating a positional relation between the first viewpoint and the second viewpoint by performing feature point matching on the first image and the second image (S15); and estimating a position of the first viewpoint and a position of the second viewpoint by applying the distance to the positional relation (S16).SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present disclosure relates to a position estimation method, a position estimation system, a camera in the position estimation system, and a program for estimating the position of a viewpoint when an image for photogrammetry is captured. [Background technology]

[0002] Patent Document 1 discloses a technique for estimating the positions and orientations of a plurality of imaging devices (that is, cameras) by performing feature point matching on a plurality of images obtained by a plurality of imaging devices. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2020 / 153264 Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure provides a position estimation method and the like that can easily estimate the position of the viewpoint when an image for photogrammetry was captured. [Means for solving the problem]

[0005] A position estimation method according to one embodiment of the present disclosure acquires a first image obtained by photographing from a first viewpoint and a first atmospheric pressure at the first viewpoint, acquires a second image obtained by photographing from a second viewpoint different from the first viewpoint and a second atmospheric pressure at the second viewpoint, calculates the vertical distance between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure, estimates a positional relationship between the first viewpoint and the second viewpoint by performing feature point matching on the first image and the second image, and estimates the position of the first viewpoint and the position of the second viewpoint by applying the distance to the positional relationship.

[0006] A position estimation system according to one embodiment of the present disclosure includes a first camera having a first atmospheric pressure sensor and generating a first image by capturing an image from a first viewpoint; a second camera having a second atmospheric pressure sensor and generating a second image by capturing an image from a second viewpoint different from the first viewpoint; and a control device that estimates the position of the first viewpoint and the position of the second viewpoint. The control device acquires the first image and a first atmospheric pressure at the first viewpoint from the first camera, acquires the second image and a second atmospheric pressure at the second viewpoint from the second camera, calculates the vertical distance between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure, estimates the positional relationship between the first viewpoint and the second viewpoint by performing feature point matching on the first image and the second image, and estimates the position of the first viewpoint and the second viewpoint by applying the distance to the positional relationship.

[0007] These general or specific aspects may be realized as a system, an integrated circuit, a computer program, or a non-transitory recording medium such as a computer-readable CD-ROM, or as any combination of a method, a system, an apparatus, an integrated circuit, a computer program, and a non-transitory recording medium. [Effects of the Invention]

[0008] The position estimation method and the like disclosed herein can easily estimate the position of a camera whose shooting direction can be changed by rotation. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a position estimation system according to an embodiment. [Figure 2] FIG. 2 is a diagram showing the relationship between three-dimensional objects and each viewpoint in a virtual space. [Figure 3] FIG. 3 is a diagram for explaining the height between the two cameras. [Figure 4]FIG. 4 is a diagram for explaining the estimated heights of the positions of the two viewpoints. [Figure 5] FIG. 5 is a block diagram illustrating an example of the configuration of the control device according to the embodiment. [Figure 6] FIG. 6 is a flowchart illustrating an example of a process for estimating the positions of the first camera and the second camera according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] (Findings that formed the basis of this disclosure) The present inventors have found that the conventional systems described in the "Background Art" section have the following problems.

[0011] In conventional techniques such as those described in Patent Document 1, the positions of multiple cameras are estimated using SfM (Structure from Motion). SfM is a technology that selects any two cameras (hereinafter referred to as a camera pair) from multiple cameras, calculates the relative positions (x, y, z) and rotation angles (ψ, θ, φ) of the camera pair based on the principle of triangulation by matching feature points contained in the two images (image pair), and simultaneously estimates the alignment that satisfies the relative positions of all cameras in the camera pair. This type of photogrammetry obtains the relative positions of the camera pair and generates a three-dimensional object of the subject. The generated three-dimensional object is composed of multiple three-dimensional points, each of which indicates a position in virtual space. Unless the distances in real space are given, the multiple three-dimensional points and the positions of each camera only indicate the relative positional relationships between the three-dimensional points. Therefore, representative dimensions of the three-dimensional object in real space are measured, and the measured dimensions are set as the distances between the corresponding three-dimensional points of the three-dimensional object. Since the relative positional relationship has been obtained, the distances between other multiple three-dimensional points and the viewpoints when each image was taken are calculated by a ratio based on the relative positional relationship, with the measured dimensions being set as the distance between two points in virtual space corresponding to the measured dimensions.

[0012] However, to determine the distance in real space, it is necessary to measure the dimensions of the objects in the images used for photogrammetry, which is not very convenient. It is also possible to use the relative distance in real space between the cameras used to take the images, rather than the dimensions of the object being photographed, as the distance in real space. However, this method still requires measuring the distance between the cameras. One method for measuring the distance between cameras is to use the position of each camera in the Earth coordinate system using a GPS or similar technology. However, this method has an error of several meters and is therefore less accurate. Furthermore, this method's accuracy is further reduced inside buildings. Another method for measuring the distance between cameras is to determine the height of each camera using a laser tape measure or similar. However, this method is difficult to use when the floors on which the cameras are installed are at different ground levels.

[0013] Therefore, the present inventors have come up with a position estimation method that can easily estimate the position of the viewpoint when an image for photogrammetry was captured.

[0014] A position estimation method according to a first aspect of the present disclosure acquires a first image obtained by photographing from a first viewpoint and a first atmospheric pressure at the first viewpoint, acquires a second image obtained by photographing from a second viewpoint different from the first viewpoint and a second atmospheric pressure at the second viewpoint, calculates the vertical distance between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure, estimates the positional relationship between the first viewpoint and the second viewpoint by performing feature point matching on the first image and the second image, and estimates the position of the first viewpoint and the position of the second viewpoint by applying the distance to the positional relationship.

[0015] This allows the position of each viewpoint to be estimated by applying the vertical distance between viewpoints, obtained based on the air pressure at each viewpoint, to the positional relationship estimated by feature point matching, making it easy to estimate the position of the viewpoint when the image for photogrammetry was captured.

[0016] A position estimation method according to a second aspect of the present disclosure is the position estimation method according to the first aspect, wherein the distance is calculated based on an air pressure difference between the first air pressure and the second air pressure.

[0017] Since atmospheric pressure fluctuates over time, calculating the difference in atmospheric pressure can cancel out the fluctuation, thereby enabling the vertical distance between the first viewpoint and the second viewpoint to be calculated with high accuracy.

[0018] A position estimation method according to a third aspect of the present disclosure is a position estimation method according to the first or second aspect, wherein the first image is captured by a first camera equipped with a first atmospheric pressure sensor, the first atmospheric pressure being a detection result detected by the first atmospheric pressure sensor at a first time when the first image is captured by the first camera, and the second image is captured by a second camera equipped with a second atmospheric pressure sensor, and the second atmospheric pressure being a detection result detected by the second atmospheric pressure sensor at a second time when the second image is captured by the second camera.

[0019] Therefore, it is possible to easily detect the first atmospheric pressure at the position of the first camera at the first time when the first image was taken, and the second atmospheric pressure at the position of the second camera at the second time when the second image was taken.

[0020] A position estimation method according to a fourth aspect of the present disclosure is the position estimation method according to the third aspect, wherein the time difference between the first time and the second time is shorter than a predetermined time.

[0021] In this way, since the time difference between the detection of the first and second atmospheric pressures is shorter than the predetermined time, each atmospheric pressure can be measured under the same atmospheric pressure conditions, and the vertical distance between the viewpoints can be calculated with high accuracy.

[0022] A position estimation method according to a fifth aspect of the present disclosure is a position estimation method according to any one of the first to fourth aspects, further comprising: acquiring directional information indicating a vertical direction in at least one of the first image and the second image; identifying a vertical direction in the positional relationship based on the acquired directional information; and, in estimating the position of the first viewpoint and the position of the second viewpoint, determining the calculated distance as the difference in the identified positions in the vertical direction between the first viewpoint and the second viewpoint in the positional relationship, thereby applying the distance to the positional relationship.

[0023] Therefore, the vertical distance between the viewpoints can be calculated.

[0024] A position estimation method according to a sixth aspect of the present disclosure is a position estimation method according to any one of the first to fifth aspects, wherein, in estimating the position of the first viewpoint and the position of the second viewpoint, an origin and three axes in a Cartesian coordinate system are further set to the positional relationship, thereby estimating the position of the first viewpoint and the position of the second viewpoint as absolute positions in the Cartesian coordinate system.

[0025] Therefore, the absolute position of each viewpoint in the Cartesian coordinate system can be easily estimated.

[0026] A position estimation system according to a seventh aspect of the present disclosure includes a first camera having a first atmospheric pressure sensor and generating a first image by capturing an image from a first viewpoint; a second camera having a second atmospheric pressure sensor and generating a second image by capturing an image from a second viewpoint different from the first viewpoint; and a control device that estimates the position of the first viewpoint and the position of the second viewpoint, wherein the control device acquires the first image and a first atmospheric pressure at the first viewpoint from the first camera, acquires the second image and a second atmospheric pressure at the second viewpoint from the second camera, calculates the vertical distance between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure, estimates the positional relationship between the first viewpoint and the second viewpoint by performing feature point matching on the first image and the second image, and estimates the position of the first viewpoint and the second viewpoint by applying the distance to the positional relationship.

[0027] This allows the position of each viewpoint to be estimated by applying the vertical distance between viewpoints, obtained based on the air pressure at each viewpoint, to the positional relationship estimated by feature point matching, making it easy to estimate the position of the viewpoint when the image for photogrammetry was captured.

[0028] A camera according to an eighth aspect of the present disclosure is a camera that is the first camera in the position estimation system according to the seventh aspect, that has a first atmospheric pressure sensor, and that generates a first image by capturing an image from a first viewpoint.

[0029] Therefore, it is possible to easily detect the first atmospheric pressure at the first time when the first images from the first viewpoint and the other viewpoint are generated.

[0030] A program according to a ninth aspect of the present disclosure is a program for causing a computer to execute the position estimation method according to any one of the first to sixth aspects.

[0031] These general or specific aspects may be realized as a system, an integrated circuit, a computer program, or a non-transitory recording medium such as a computer-readable CD-ROM, or as any combination of a method, a system, an apparatus, an integrated circuit, a computer program, and a non-transitory recording medium.

[0032] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, more detailed explanation than necessary may be omitted. For example, detailed explanation of well-known matters or redundant explanation of substantially the same configuration may be omitted. This is to avoid unnecessary redundancy in the following explanation and to facilitate understanding by those skilled in the art.

[0033] The accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0034] (Embodiment) Hereinafter, the embodiment will be described with reference to FIGS.

[0035] [composition] Fig. 1 is a diagram illustrating an example of the configuration of a position estimation system according to an embodiment, Fig. 2 is a diagram illustrating the relationship between a three-dimensional object and each viewpoint in a virtual space.

[0036] The position estimation system 1 includes a plurality of cameras 11 to 14 and a control device 100 communicably connected to the plurality of cameras 11 to 14. The position estimation system 1 is a system for generating a three-dimensional object 21 of a specific subject 20 in a space 30 by photogrammetry. The position estimation system 1 can estimate the positions of the plurality of cameras 11 to 14 by using photogrammetry. The space 30 is a real space.

[0037] In the position estimation system 1, a specific subject 20 located within a specific imaging range within the space 30 is captured by a plurality of cameras 11-14 arranged at different positions within the space 30. Of the plurality of cameras 11-14, a first camera 11 is arranged at a first position P1, a second camera 12 is arranged at a second position P2, a third camera 13 is arranged at a third position P3, and a fourth camera 14 is arranged at a fourth position P4. Because the plurality of cameras 11-14 capture images of the same subject 20 from different positions, images 201-204 of the specific subject 20 captured from a plurality of different imaging directions D1-D4 can be obtained. That is, the first camera 11 captures the subject 20 in the imaging direction D1, the second camera 12 captures the subject 20 in the imaging direction D2, the third camera 13 captures the subject 20 in the imaging direction D3, and the fourth camera 14 captures the subject 20 in the imaging direction D4. The first position P1 indicates the position of the first viewpoint taken by the first camera 11, the second position P2 indicates the position of the second viewpoint taken by the second camera 12, the third position P3 indicates the position of the third viewpoint taken by the third camera 13, and the fourth position P4 indicates the position of the fourth viewpoint taken by the fourth camera 14. The images obtained by the multiple cameras 11 to 13 may be still images or may be videos.

[0038] Each of the first camera 11, the second camera 12, the third camera 13, and the fourth camera 14 is a PTZ camera capable of panning, tilting, and zooming. That is, the first camera 11 can change the shooting direction D1 by rotating in two different rotational directions at the first position P1. Similarly, the second camera 12 can change the shooting direction D2 by rotating in two different rotational directions at the second position P2. Similarly, the third camera 13 can change the shooting direction D3 by rotating in two different rotational directions at the third position P3. Similarly, the fourth camera 14 can change the shooting direction D4 by rotating in two different rotational directions at the fourth position P4. In this way, each of the first camera 11, the second camera 12, the third camera 13, and the fourth camera 14 has a rotation mechanism that changes the shooting direction by rotating in two different rotational directions.

[0039] Each of first camera 11, second camera 12, third camera 13 and fourth camera 14 is equipped with an air pressure sensor that detects the air pressure at the position of each camera.

[0040] The number of cameras included in the position estimation system 1 is not limited to four cameras 11 to 14, but may be two cameras, three cameras, or five or more cameras. The position estimation system 1 is not limited to having multiple cameras, but may be provided with one camera with a changeable viewpoint. The position estimation system 1 may also be provided with a combination of a fixed camera and a camera with a changeable viewpoint.

[0041] The control device 100 controls the operations of the multiple cameras 11-14. The control device 100 acquires multiple images 201-204 obtained by shooting with the multiple cameras 11-14, and generates a three-dimensional object 21 of the subject 20 using the acquired multiple images 201-204, and estimates the positions P11-P14 and attitudes (i.e., shooting directions D1-D4) of the multiple cameras 11-14. The control device 100 is an example of a position estimation device. A detailed configuration of the control device 100 will be described later using FIG. 5.

[0042] The following describes processing related to the first camera 11 and the second camera 12 among the multiple cameras 11 to 14. This is because the processing for generating the three-dimensional object 21 of the subject 20 and the position estimation of each camera require images captured from at least two different viewpoints. That is, although not described below, instead of a combination of information obtained by the first camera 11 (first image 201 and first atmospheric pressure) and information obtained by the second camera 12 (second image 202 and second atmospheric pressure), the processing for generating the three-dimensional object 21 of the subject 20 and the position estimation of each camera may be performed using information obtained from a combination of two different cameras. Furthermore, the processing for generating the three-dimensional object 21 of the subject 20 and the position estimation of each camera may be performed using information obtained from a combination of two cameras in addition to the combination of the first camera 11 and the second camera 12. The combination of two additional cameras may be one or two or more.

[0043] Fig. 3 is a diagram for explaining the height between two cameras, and Fig. 4 is a diagram for explaining the estimated heights of the positions of two viewpoints.

[0044] 3, first camera 11 is disposed at position P1 at height z1, which is a distance C1 higher than reference height z0. Second camera 12 is disposed at position P2 at height z2, which is a distance C2 higher than reference height z0. In this embodiment, height refers to a position in the vertical direction (Z-axis direction).

[0045] Here, since the atmospheric pressure decreases as the altitude increases, the vertical distance ΔC between heights z1 and z2 can be calculated if the difference in atmospheric pressure between a first atmospheric pressure at height z1 and a second atmospheric pressure at height z2 is known. The first atmospheric pressure is the atmospheric pressure detected by a first atmospheric pressure sensor provided in first camera 11, and the second atmospheric pressure is the atmospheric pressure detected by a second atmospheric pressure sensor provided in second camera 12.

[0046] On the other hand, because the positions P11-P14 of the multiple cameras 11-14 estimated by the control device 100 using the multiple images 201-204 are relative positional relationships, the vertical distance Δc between the position P11 corresponding to the position P1 of the first camera 11 and the position P12 corresponding to the position P2 of the second camera 12 is unknown. Therefore, the control device 100 determines the distance Δc in the relative positional relationship to be the calculated distance ΔC, thereby being able to calculate the distance between other positions in the relative positional relationship (i.e., between other three-dimensional points). Note that the distance Δc is the difference between the height z11 of the position P11 and the height z12 of the position P12.

[0047] FIG. 5 is a block diagram illustrating an example of the configuration of the control device according to the embodiment.

[0048] The control device 100 includes an acquisition unit 101 and an estimation unit 102. The control device 100 may further include a control unit 103 and an input reception unit 104.

[0049] The acquisition unit 101 acquires a first image 201 and a first atmospheric pressure from the first camera 11. The first image 201 is an image obtained by photographing from a first viewpoint. The first image 201 is an image photographed by the first camera 11. The first atmospheric pressure is the atmospheric pressure at the first viewpoint. The first atmospheric pressure is a detection result detected by the first atmospheric pressure sensor at a first time when the first image 201 is photographed by the first camera 11.

[0050] Similarly, the acquisition unit 101 acquires a second image 202 and a second atmospheric pressure from the second camera 12. The second image 202 is an image obtained by capturing an image from a second viewpoint different from the first viewpoint. The second image 202 is an image captured by the second camera 12. The second atmospheric pressure is the atmospheric pressure at the second viewpoint. The second atmospheric pressure is the detection result detected by the second atmospheric pressure sensor at the second time when the second image 202 is captured by the second camera 12. Note that the time difference between the first time and the second time may be shorter than the predetermined time. The predetermined time may be set to a time when the change in atmospheric pressure over time is small. For example, the predetermined time may be set to a time when the change in atmospheric pressure is converted into height of 10 cm or less.

[0051] The estimation unit 102 calculates the vertical distance between the first viewpoint and the second viewpoint based on the pressure difference between the first pressure and the second pressure. Specifically, the estimation unit 102 may determine the vertical distance corresponding to the pressure difference between the first pressure and the second pressure by referring to information indicating the correspondence between different pressure differences and the vertical distance corresponding to each pressure difference, or may calculate the vertical distance corresponding to the pressure difference by multiplying the pressure difference by a predetermined coefficient for calculating the vertical distance from the pressure difference.

[0052] Furthermore, the estimation unit 102 performs feature point matching between the first image 201 acquired from the first camera 11 and the second image 202 acquired from the second camera 12, thereby estimating the positional relationship between the first viewpoint position P11 and the second viewpoint position P12 corresponding to the first image 201 and the second image 202, respectively. For example, the estimation unit 102 detects a plurality of feature points in each of the first image 201 and the second image 202, and matches feature points having corresponding feature amounts (i.e., similar feature points) among the detected plurality of feature points. In this way, the estimation unit 102 identifies pairs of feature points in the first image 201 and the second image 202, and estimates the positional relationship between the position and orientation of the first camera 11 when the first image 201 was captured and the position and orientation of the second camera 12 when the second image 202 was captured, based on the pairs of feature points. Then, the estimation unit 102 estimates the position P1 of the first viewpoint and the position P2 of the second viewpoint by applying the vertical distance between the first viewpoint and the second viewpoint to the positional relationship.

[0053] Here, the vertical direction in the virtual space may be set to match either the vertical direction of the first image 201 or the vertical direction of the second image 202. In this case, the vertical directions of the first camera 11 and the second camera 12 match the vertical direction in the real space (the direction of gravity). Note that it is sufficient that the vertical direction of at least one camera matches the vertical direction in the real space, and the vertical directions of all cameras do not have to match the vertical direction in the real space. In this case, the vertical direction in the virtual space is set to match the vertical direction of the image captured by a camera that is placed so as to match the vertical direction in the real space. Here, the vertical direction of the camera is the direction in which the tilt angle of the PTZ camera is set to 0 degrees.

[0054] The positional relationship indicates the ratio of the distances between a position P11 corresponding to a first viewpoint, a position P12 corresponding to a second viewpoint, and a plurality of three-dimensional points on the surface of the three-dimensional object 21 of the subject 20 in the virtual space. Specifically, the estimation unit 102 determines the vertical distance between the first viewpoint and the second viewpoint, thereby identifying the distances between the first viewpoint position P1, the second viewpoint position P2, and a plurality of three-dimensional points on the surface of the three-dimensional object 21 of the subject 20. The estimation unit 102 then generates a positional relationship in which the distances between the plurality of positions are identified. The plurality of three-dimensional points on the surface of the three-dimensional object 21 correspond to a plurality of pairs identified as a result of feature point matching. The three-dimensional point CP1 on the surface of the subject 20 in FIG. 1 is calculated by triangulation based on the pair of the feature point corresponding to the three-dimensional point CP1 on the first image 201 and the feature point corresponding to the three-dimensional point CP1 on the second image 202.

[0055] Furthermore, the estimation unit 102 may estimate the first viewpoint position P1 and the second viewpoint position P2 as absolute positions in a Cartesian coordinate system by further setting an origin and three axes in the Cartesian coordinate system in the positional relationship in which the distances between the multiple positions are specified. The three axes are, for example, the X-axis, Y-axis, and Z-axis in the Cartesian coordinate system, which are mutually orthogonal. As a result, the first viewpoint position P1 and the second viewpoint position P2 are each expressed in three-dimensional coordinates including the X-coordinate, the Y-coordinate, and the Z-coordinate relative to the set origin. The origin may be set at a position indicated by any one of the multiple viewpoints and multiple three-dimensional points, or may be set at any point in the virtual space.

[0056] The control unit 103 instructs the first camera 11 and the second camera 12 to capture images. The control unit 103 may also request the first camera 11 and the second camera 12 to transmit the first image 201 and the second image 202 obtained by capturing the images to the control device 100. At this time, the control unit 103 may also request the first camera 11 and the second camera 12 to transmit to the control device 100 the first atmospheric pressure when the first image 201 was captured and the second atmospheric pressure when the second image 202 was captured.

[0057] Control unit 103 may instruct first camera 11 and second camera 12 to capture an image in response to an input received by input receiving unit 104, which will be described later. For example, control unit 103 may instruct a camera designated by a user to capture an image in a direction designated by the user.

[0058] Input receiving unit 104 receives input from the user. The input from the user may be an input for instructing first camera 11 and second camera 12 to take a photograph, or an input for instructing a specific camera to take a photograph. The input for instructing a photograph may specify the photographing direction, the photographing timing, the image quality of the image to be taken, etc. The image quality includes, for example, the resolution and, in the case of a video, the frame rate.

[0059] [Operation] The operation of estimating the positions of first camera 11 and second camera 12 by control device 100 of position estimation system 1 configured as above will be described.

[0060] FIG. 6 is a flowchart illustrating an example of a process for estimating the positions of the first camera and the second camera according to the embodiment.

[0061] The control device 100 acquires a first image 201 and a first atmospheric pressure from the first camera 11 (S11).

[0062] The control device 100 acquires a second image 202 and a second atmospheric pressure from the second camera 12 (S12).

[0063] The control device 100 calculates the vertical distance between the first viewpoint and the second viewpoint based on the air pressure difference between the first air pressure and the second air pressure (S13).

[0064] The control device 100 performs feature point matching between the first image 201 obtained from the first camera 11 and the second image 202 obtained from the second camera 12 (S14).

[0065] Based on the result of feature point matching, the control device 100 estimates the positional relationship between the first viewpoint position P11 and the second viewpoint position P12 corresponding to the first image 201 and the second image 202, respectively (S15).

[0066] The control device 100 estimates the position P1 of the first viewpoint and the position P2 of the second viewpoint by applying the calculated distance to the positional relationship (S16).

[0067] [effect] In the position estimation method according to this embodiment, the control device 100 (position estimation device) acquires a first image 201 obtained by capturing an image from a first viewpoint and a first atmospheric pressure at the first viewpoint (S11). The control device 100 acquires a second image 202 obtained by capturing an image from a second viewpoint different from the first viewpoint and a second atmospheric pressure at the second viewpoint (S12). The control device 100 calculates a vertical distance ΔC between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure (S13). The control device 100 estimates the positional relationship between the first viewpoint and the second viewpoint by performing feature point matching on the first image 201 and the second image 202 (S15). The control device 100 estimates the position P1 of the first viewpoint and the position P2 of the second viewpoint by applying the calculated distance to the estimated positional relationship (S16).

[0068] This allows the position of each viewpoint to be estimated by applying the vertical distance between viewpoints, obtained based on the air pressure at each viewpoint, to the positional relationship estimated by feature point matching, making it easy to estimate the position of the viewpoint when the image for photogrammetry was captured.

[0069] Furthermore, in the position estimation method according to this embodiment, when calculating the distance, the control device 100 calculates the vertical distance between the first viewpoint and the second viewpoint based on the air pressure difference between the first air pressure and the second air pressure.

[0070] Since atmospheric pressure fluctuates over time, calculating the difference in atmospheric pressure can cancel out the fluctuation, thereby enabling the vertical distance between the first viewpoint and the second viewpoint to be calculated with high accuracy.

[0071] Furthermore, in the position estimation method according to this embodiment, a first image 201 is captured by a first camera 11 equipped with a first atmospheric pressure sensor. The first atmospheric pressure is a detection result detected by the first atmospheric pressure sensor at a first time when the first image 201 is captured by the first camera 11. A second image 202 is captured by a second camera 12 equipped with a second atmospheric pressure sensor. The second atmospheric pressure is a detection result detected by the second atmospheric pressure sensor at a second time when the second image 202 is captured by the second camera 12.

[0072] Therefore, it is possible to easily detect the first atmospheric pressure at position P1 of the first camera 11 at the first time when the first image 201 was taken, and the second atmospheric pressure at position P2 of the second camera 12 at the second time when the second image 202 was taken.

[0073] In addition, in the position estimation method according to the present embodiment, the time difference between the first time when the first atmospheric pressure is detected and the second time when the second atmospheric pressure is detected is shorter than a predetermined time.

[0074] In this way, since the time difference between the detection of the first and second atmospheric pressures is shorter than the predetermined time, each atmospheric pressure can be measured under the same atmospheric pressure conditions, and the vertical distance ΔC between the viewpoints can be calculated with high accuracy.

[0075] Furthermore, in the position estimation method according to this embodiment, when estimating the position P1 of the first viewpoint and the position P2 of the second viewpoint, the control device 100 further sets an origin and three axes in a Cartesian coordinate system to the positional relationship, thereby estimating the position P1 of the first viewpoint and the position P2 of the second viewpoint as absolute positions in the Cartesian coordinate system.

[0076] Therefore, the absolute position of each viewpoint in the Cartesian coordinate system can be easily estimated.

[0077] [Variations] Although the position estimation method and the position estimation system according to the embodiment of the present disclosure have been described above, the present disclosure is not limited to this embodiment.

[0078] In the above embodiment, the vertical distance between the first viewpoint position P1 and the second viewpoint position P2 is calculated based on the difference in atmospheric pressure between the first and second atmospheric pressures. However, this is not limited to this. The control device 100 may calculate the height of each viewpoint based on each atmospheric pressure, and calculate the difference in height to calculate the distance. Specifically, the control device 100 calculates the height z1 of the first viewpoint position P1 based on the first atmospheric pressure. The control device 100 calculates the height z2 of the second viewpoint position P2 based on the second atmospheric pressure. The control device 100 then calculates the difference between the height z1 calculated based on the first atmospheric pressure and the height z2 calculated based on the second atmospheric pressure as the vertical distance between the first viewpoint position P1 and the second viewpoint position P2.

[0079] In the above embodiment, the vertical direction of at least one camera coincides with the vertical direction in real space. However, this is not limited to this. For example, if at least one camera has a triaxial acceleration sensor, the direction of gravity can be determined using the detection results of the triaxial acceleration sensor. Therefore, it is not necessary for there to be any camera whose vertical direction coincides with the vertical direction in real space. In this case, the acquisition unit 101 acquires, from a camera equipped with a triaxial acceleration sensor, direction information indicating the vertical direction in an image captured by the camera. The estimation unit 102 determines the vertical direction in the estimated positional relationship based on the acquired direction information. Then, in estimating the first viewpoint position P1 and the second viewpoint position P2, the estimation unit 102 applies the calculated distance ΔC to the estimated positional relationship by determining the difference in the determined vertical direction between the first viewpoint and the second viewpoint in the estimated positional relationship. This allows the vertical distance between the viewpoints to be calculated.

[0080] In the above embodiment and modifications, the control device 100 has been described as a device separate from the plurality of cameras 11-14, but it may be provided in at least one of the plurality of cameras 11-14.

[0081] In the above embodiment and variant examples, the multiple cameras 11 to 14 are all cameras whose shooting direction can be changed, but this is not limited to this, and the multiple cameras may be cameras whose shooting direction cannot be changed as long as they can shoot the subject 20 from different viewpoints.

[0082] Furthermore, each processing unit included in the control device according to the above-described embodiments is typically realized as an LSI, which is an integrated circuit. These may be individually implemented as single chips, or some or all of them may be integrated into a single chip.

[0083] Furthermore, the integration is not limited to LSI, but may be realized by dedicated circuits or general-purpose processors. FPGAs (Field Programmable Gate Arrays), which can be programmed after LSI fabrication, or reconfigurable processors, which allow the connections and settings of circuit cells within LSIs to be reconfigured, may also be used.

[0084] The present disclosure may also be realized as a position estimation method or the like executed by a control device or the like.

[0085] The division of functional blocks in the block diagram is an example, and multiple functional blocks may be realized as a single functional block, one functional block may be divided into multiple blocks, or some functions may be moved to another functional block.Furthermore, the functions of multiple functional blocks having similar functions may be processed in parallel or in time-sharing by a single piece of hardware or software.

[0086] The order in which the steps in the flowchart are executed is merely an example for specifically explaining the present disclosure, and other orders may be used. Some of the steps may be executed simultaneously (in parallel) with other steps.

[0087] While the position estimation system, control device, and the like according to one or more aspects have been described based on the embodiments, the present disclosure is not limited to these embodiments. As long as they do not deviate from the spirit of the present disclosure, various modifications conceivable by those skilled in the art to the present embodiments and configurations constructed by combining components of different embodiments may also be included within the scope of one or more aspects. [Industrial Applicability]

[0088] The present disclosure is useful as a position estimation method that can easily estimate the position of the viewpoint when an image for photogrammetry was captured. [Explanation of symbols]

[0089] 1. Location estimation system 11 Camera 1 12 Second Camera 13 Third Camera 14 Fourth Camera 20 Subject 21 Three-dimensional objects 30 space 100 control device 101 Acquisition Department 102 Estimation part 103 Control Unit 104 Input reception unit 201 Image 1 202 2nd image 203 3rd image 204 4th image D1, D2, D3, D4 Shooting direction P1~P4, P11~P14 position z0 reference height z1, z2, z11, z12 height

Claims

1. acquiring a first image obtained by photographing from a first viewpoint and a first atmospheric pressure at the first viewpoint; acquiring a second image obtained by photographing from a second viewpoint different from the first viewpoint and a second atmospheric pressure at the second viewpoint; calculating a vertical distance between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure; performing feature point matching on the first image and the second image to estimate a positional relationship between the first viewpoint and the second viewpoint; The position of the first viewpoint and the position of the second viewpoint are estimated by applying the distance to the positional relationship. Location estimation method.

2. The distance is calculated based on the pressure difference between the first pressure and the second pressure. The location estimation method according to claim 1 .

3. the first image is captured by a first camera equipped with a first atmospheric pressure sensor; the first atmospheric pressure is a detection result detected by the first atmospheric pressure sensor at a first time when the first image is captured by the first camera, the second image is taken by a second camera equipped with a second air pressure sensor; The second atmospheric pressure is a detection result detected by the second atmospheric pressure sensor at a second time when the second image is captured by the second camera. The location estimation method according to claim 1 .

4. The time difference between the first time and the second time is shorter than a predetermined time. The location estimation method according to claim 3 .

5. moreover, acquiring direction information indicating a vertical direction in at least one of the first image and the second image; Identifying a vertical direction in the positional relationship based on the acquired direction information; In estimating the position of the first viewpoint and the position of the second viewpoint, the distance is applied to the positional relationship by determining a difference in the specified position in the vertical direction between the first viewpoint and the second viewpoint in the positional relationship as the calculated distance. The method of claim 1 .

6. In estimating the position of the first viewpoint and the position of the second viewpoint, an origin and three axes in a Cartesian coordinate system are further set in the positional relationship, and the position of the first viewpoint and the position of the second viewpoint are estimated as absolute positions in the Cartesian coordinate system. The method of claim 1 .

7. a first camera having a first atmospheric pressure sensor and configured to generate a first image by capturing an image from a first viewpoint; a second camera having a second atmospheric pressure sensor and configured to generate a second image by capturing an image from a second viewpoint different from the first viewpoint; a control device that estimates the position of the first viewpoint and the position of the second viewpoint, The control device acquiring the first image and the first atmospheric pressure at the first viewpoint from the first camera; acquiring the second image and the second atmospheric pressure at the second viewpoint from the second camera; calculating a vertical distance between the first viewpoint and the second viewpoint based on the first atmospheric pressure and the second atmospheric pressure; performing feature point matching on the first image and the second image to estimate a positional relationship between the first viewpoint and the second viewpoint; The position of the first viewpoint and the position of the second viewpoint are estimated by applying the distance to the positional relationship. Location estimation system.

8. A camera that is a first camera in the position estimation system of claim 7, A first atmospheric pressure sensor is provided, and a first image is generated by capturing an image from a first viewpoint. camera.

9. A program for causing a computer to execute the position estimation method according to any one of claims 1 to 4.

Images