Information processing device, information processing method, and computer program

Abstract

To easily acquire the scattering loss of an object such as a wall.SOLUTION: An information processing device includes an acquisition part for acquiring an image in which the object is captured, an object photographing distance which is a distance from the position of an imaging device capturing the image to the object which is a subject, and the complex dielectric constant of the object, a surface roughness value acquisition part for obtaining a surface roughness value indicating the roughness of the surface of the object from the image, a correlation distance acquisition part for obtaining a correlation distance corresponding to the object photographing distance and the frequency component of the image, and a scattering loss calculation part for calculating the scattering loss of the object by using the surface roughness value, the complex dielectric constant, and the correlation distance.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a computer program. [Background technology]

[0002] Conventionally, methods for estimating the propagation loss of electromagnetic waves in the 300 GHz band have been studied (for example, see Non-Patent Documents 1 and 2). Non-Patent Document 1 studies the scattering of electromagnetic waves in the 300 GHz band by walls. Non-Patent Document 2 studies the scattering loss using the ER model (scattering loss model). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Masaaki Urahashi, Ryo Okumura, Koji Suizu, and Akihiko Hirata, “Complex Permittivity Evaluation of Building Materials at 200-500 GHz Using THz-TDS,” IEEE, 2020 [Non-Patent Document 2] Vittorio Degli-Esposti, “A Diffuse Scattering Model for Urban Propagation Prediction,” IEEE Transactions on Antennas and Propagation, Volume 49, Issue 7, July 2001 Summary of the Invention [Problem to be solved by the invention]

[0004] Since electromagnetic waves in the 300 GHz band have a large loss due to shielding, it is important to accurately estimate the loss of the scattered wave path due to walls around the human body in order to grasp the area in which a communication device worn on the human body can communicate. In order to estimate the loss of the scattered wave path, it is preferable to extract the surface roughness of the wall, etc. on the order of the wavelength of the electromagnetic wave, but there are the following problems. (1) Surface roughness measurements using point cloud scanners are generally limited to a few mm per point, which means that the granularity is insufficient. (2) Surface roughness measurements used in the metal and chemical materials industries require needles or lasers to be placed directly on the wall, making the process time-consuming.

[0005] The present invention has been made in consideration of the above circumstances, and has an object to easily obtain the scattering loss of an object such as a wall. [Means for solving the problem]

[0006] One aspect of the present invention is an information processing device that includes an acquisition unit that acquires an image of an object, an object shooting distance that is the distance from the position of an imaging device that captured the image to the object that is the subject, and the complex dielectric constant of the object, a surface roughness value acquisition unit that calculates a surface roughness value that indicates the roughness of the surface of the object from the image, a correlation distance acquisition unit that calculates a correlation distance according to the object shooting distance and a frequency component of the image, and a scattering loss calculation unit that calculates the scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance. One aspect of the present invention is an information processing device as described above, wherein the surface roughness value acquisition unit extracts contours of objects from the image, determines a luminance distribution from the image, and acquires a surface roughness value corresponding to the number of objects with the extracted contours and the determined luminance distribution from the relationship between the number of objects with the contours determined in advance, the luminance distribution, and the surface roughness value. One aspect of the present invention is an information processing device as described above, wherein the correlation distance acquisition unit calculates a power spectrum from the image, and acquires a correlation distance between the calculated power spectrum and the object shooting distance from a relationship between the previously calculated power spectrum of the image, the distance from a position of an imaging device that captured the image to a subject, and the correlation distance. One aspect of the present invention is an information processing device as described above, wherein the scattering loss calculation unit calculates, from the surface roughness value, the complex dielectric constant, and the correlation distance, parameters used in a scattering loss model, a first parameter that determines the beam width of the scattered wave for each surface element, and a second parameter that determines the strength of the scattered wave for each surface element.

[0007] One aspect of the present invention is an information processing method executed by an information processing device, the information processing method including: an acquisition step of acquiring an image including an object, an object shooting distance which is a distance from a position of an imaging device that captured the image to the object that is a subject, and a complex dielectric constant of the object; a surface roughness value acquisition step of calculating a surface roughness value indicating a roughness of a surface of the object from the image; a correlation distance acquisition step of calculating a correlation distance corresponding to the object shooting distance and a frequency component of the image; and a scattering loss calculation step of calculating a scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance.

[0008] One aspect of the present invention is a computer program for causing a computer to execute the following steps: acquiring an image of an object, an object shooting distance which is the distance from the position of an imaging device that captured the image to the object that is the subject, and the complex dielectric constant of the object; a surface roughness value acquiring step of calculating a surface roughness value indicating the roughness of the surface of the object from the image; a correlation distance acquiring step of calculating a correlation distance corresponding to the object shooting distance and a frequency component of the image; and a scattering loss calculating step of calculating a scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance. Effect of the Invention

[0009] According to the present invention, it is possible to obtain an effect that the scattering loss of an object such as a wall can be easily obtained. [Brief description of the drawings]

[0010] [Figure 1] 1 is a block diagram showing an example of a configuration of an information processing device according to an embodiment; [Diagram 2] 1 is a diagram illustrating an overview of an electromagnetic wave transmission path estimation method according to an embodiment; [Diagram 3] FIG. 1 is a diagram illustrating an example of an information processing method according to an embodiment. [Figure 4] FIG. 4 is a diagram for explaining a surface roughness value according to an embodiment. [Diagram 5] 5A to 5C are diagrams for explaining an example of a method for calculating a surface roughness value and a correlation distance according to an embodiment. [Figure 6] 5A to 5C are diagrams for explaining an example of a method for calculating a surface roughness value and a correlation distance according to an embodiment. [Figure 7] 5A to 5C are diagrams for explaining an example of a method for calculating a surface roughness value and a correlation distance according to an embodiment. [Figure 8] 5A to 5C are diagrams for explaining an example of a method for calculating a surface roughness value and a correlation distance according to an embodiment. [Figure 9] FIG. 2 is a diagram for explaining an example of a method for calculating ER model parameters according to an embodiment. [Figure 10] FIG. 2 is a diagram for explaining an example of a method for calculating ER model parameters according to an embodiment. [Figure 11] FIG. 2 is a diagram for explaining an example of a method for calculating ER model parameters according to an embodiment. [Figure 12] FIG. 2 is a diagram for explaining an example of a method for calculating ER model parameters according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. 1 is a block diagram showing an example of the configuration of an information processing device according to an embodiment. In FIG. 1, the information processing device 1 includes an acquisition unit 11, a surface roughness value acquisition unit 12, a correlation distance acquisition unit 13, a scattering loss calculation unit 14, and a storage unit 20.

[0012] Each function of the information processing device 1 is realized by the information processing device 1 including computer hardware such as a CPU (Central Processing Unit) and a memory, and the CPU executing a computer program stored in the memory. The information processing device 1 may be configured using a general-purpose computer device, or may be configured as a dedicated hardware device. For example, the information processing device 1 may be configured using a server computer connected to a communication network such as the Internet. Each function of the information processing device 1 may be realized by cloud computing. The information processing device 1 may be realized by a single computer, or may be realized by distributing the functions of the information processing device 1 among multiple computers. The information processing device 1 may be configured to open a website using, for example, a WWW system or the like.

[0013] The acquisition unit 11 acquires an image (target image) showing an object such as a wall, an object shooting distance, which is the distance from the position of the imaging device that captured the target image to the object that is the subject, and the complex dielectric constant of the object. The surface roughness value acquisition unit 12 obtains a surface roughness value indicating the roughness of the surface of the object from the target image. The correlation distance acquisition unit 13 obtains a correlation distance according to the object shooting distance and the frequency component of the target image. The scattering loss calculation unit 14 calculates the scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance. The storage unit 20 stores various data. The acquisition unit 11, the surface roughness value acquisition unit 12, the correlation distance acquisition unit 13, and the scattering loss calculation unit 14 store their own processing results in a predetermined area of ​​the storage unit 20.

[0014] The information processing device 1 outputs the processing result stored in the storage unit 20. For example, the information processing device 1 may display the processing result on a predetermined display device. For example, the information processing device 1 may transmit the processing result to a predetermined destination by communication.

[0015] Fig. 2 is a diagram showing an outline of an electromagnetic wave transmission path estimation method according to the present embodiment. In the example of Fig. 2, in the case where a transmitter Tx (e.g., a smartphone, etc.) carried by a person and a receiver Rx (e.g., wireless headphones, etc.) worn by the person perform wireless communication using electromagnetic waves in the 300 GHz band, the transmission path of the electromagnetic waves is estimated when scattering occurs at a wall surface.

[0016] As shown in Fig. 2, first, the wireless environment (people, transmitter Tx, receiver Rx, walls, etc.) is modeled three-dimensionally (3D model). Next, the dominant propagation path between the transmitter Tx and the receiver Rx is identified by the 3D model 3DM. Next, the losses of the identified direct wave path, diffracted wave path, and scattered wave path are estimated. Next, the estimated direct wave path, diffracted wave path, and scattered wave path are synthesized, and the propagation loss between the transmitter Tx and the receiver Rx is calculated by the synthesized transmission path. This embodiment can be applied to estimating the loss of the scattered wave path exemplified in Fig. 2.

[0017] Next, the information processing executed by the information processing device 1 according to this embodiment will be described in detail.

[0018] Fig. 3 is a diagram showing an example of an information processing method according to the present embodiment. Fig. 3 shows two examples of objects: (A) a wall with a smooth surface (referred to as wall A) and (B) a wall with a rough surface (referred to as wall B).

[0019] The acquisition unit 11 acquires an image (referred to as target image A) in which wall A appears, the distance (referred to as target shooting distance A) from the position of the imaging device that captured the target image A to the wall A, which is the subject, and the complex dielectric constant (referred to as complex dielectric constant A) of the wall A. The target image A, the target shooting distance A, and the complex dielectric constant A are prepared in advance and input to the information processing device 1.

[0020] Similarly, the acquisition unit 11 acquires an image in which a wall B appears (referred to as a target image B), a distance from the position of the imaging device that captured the target image B to the wall B, which is the subject (referred to as a target shooting distance B), and the complex dielectric constant of the wall B (referred to as a complex dielectric constant B). The target image B, the target shooting distance B, and the complex dielectric constant B are prepared and input to the information processing device 1 in advance.

[0021] The surface roughness value acquisition unit 12 extracts the contours of objects appearing in the target image A by executing a contour extraction image analysis process on the target image A. As a result, 100 contours of objects are extracted as black dots from the target image A.

[0022] Similarly, the surface roughness value acquiring unit 12 extracts contours of objects appearing in the target image B by executing a contour extraction image analysis process on the target image B. As a result, 5000 contours of objects are extracted as black dots from the target image B.

[0023] The surface roughness value acquisition unit 12 executes an RGB image analysis process on the target image A to obtain the luminance distribution of each of the RGB components from the target image A. As a result, the luminance distribution width of the R component "44", the luminance distribution width of the G component "38", and the luminance distribution width of the B component "31" are obtained from the target image A. The luminance distribution widths are widths determined according to a predetermined standard, and may correspond to the standard deviation, for example.

[0024] Similarly, the surface roughness value acquisition unit 12 executes RGB image analysis processing on the target image B to obtain the luminance distribution of each RGB component from the target image B. As a result, the width of the luminance distribution of the R component, the width of the luminance distribution of the G component, and the width of the luminance distribution of the B component are obtained from the target image B: "152", "171", and "170".

[0025] The surface roughness value acquisition unit 12 acquires, from the relationship between the number of contour objects, the luminance distribution, and the surface roughness value obtained in advance, a surface roughness value "σ_h=aaa" for wall A corresponding to the number of extracted contour objects "100" and the acquired luminance distributions "R component luminance distribution width "44", "G component luminance distribution width "38", and "B component luminance distribution width "31".

[0026] Similarly, the surface roughness value acquisition unit 12 acquires, for wall B, a surface roughness value "σ_h=bbb" corresponding to the number of extracted contour objects "5000" and the acquired luminance distributions "R component luminance distribution width '152'," "G component luminance distribution width '171'," and "B component luminance distribution width '170'" from the relationship between the previously determined number of contour objects, luminance distribution, and surface roughness value.

[0027] The correlation distance acquisition unit 13 obtains the correlation distance "l=eee" for the wall A according to the object shooting distance A and the frequency components of the target image A.

[0028] Similarly, the correlation distance acquisition unit 13 obtains the correlation distance "l=fff" for wall B according to the object shooting distance B and the frequency component of the target image B.

[0029] The scattering loss calculation unit 14 uses the surface roughness value "σ_h=aaa", the complex dielectric constant A "ε=ccc", and the correlation distance "l=eee" for the wall A to determine the first parameter "α=www" and the second parameter "S=xxx" used in the ER model (scattering loss model). The first parameter α is a parameter that determines the beam width of the scattered wave for each surface element (polygon) of the 3D model 3DM. The second parameter S is a parameter that determines the strength of the scattered wave for each surface element (polygon) of the 3D model 3DM.

[0030] Similarly, the scattering loss calculation unit 14 calculates the first parameter "α=yyy" and the second parameter "S=zzz" used in the ER model (scattering loss model) for wall B using the surface roughness value "σ_h=bbb", the complex dielectric constant B "ε=ddd", and the correlation distance "l=fff".

[0031] The scattering loss calculation unit 14 calculates the scattering loss for the wall A by using the first parameter "α=www" and the second parameter "S=xxx" according to the formula (1).

[0032]

number

[0033] Similarly, the scattering loss calculation unit 14 calculates the scattering loss for the wall B by using the first parameter "α=yyy" and the second parameter "S=zzz" according to formula (1).

[0034] 4 is a diagram for explaining the surface roughness value according to the present embodiment, in which the surface roughness value σ_h is the standard deviation of the height h of the irregularities on the surface of an object such as a wall.

[0035] 5 to 8 are diagrams for explaining an example of a method for calculating a surface roughness value and a correlation distance according to the present embodiment. The method for calculating a surface roughness value and a correlation distance according to the present embodiment will be explained with reference to Figs. 5 to 8.

[0036] A random rough surface as shown in FIG. 5 is generated in advance using three-dimensional computer graphics (3DCG) software. In generating this random rough surface, a surface roughness value σ_h and a correlation distance l are specified. Next, as shown in FIG. 6, the number K of contour objects and the luminance distributions "width R of the luminance distribution of the R component," "width G of the luminance distribution of the G component," and "width B of the luminance distribution of the B component" on the generated random rough surface are related to the specified surface roughness value σ_h, "σ_h=f(K,R,G,B)."

[0037] In addition, as shown in Fig. 7, the relational expression "l = g(P, d)" between the strongest frequency P of the power spectrum in the generated random rough surface, the distance d from the shooting point to the target object, and the specified correlation distance l is obtained. The distance d can be specified arbitrarily.

[0038] The relational expression "σ_h=f(K,R,G,B)" of the surface roughness value σ_h and the relational expression "l=g(P,d)" of the correlation distance l may be modeled by, for example, machine learning.

[0039] The actual surface roughness value σ_h and correlation distance l are calculated using the relational expression "σ_h=f(K,R,G,B)" of the surface roughness value σ_h and the relational expression "l=g(P,d)" of the correlation distance l calculated as above. FIG. 8 shows a case where the target object is a wall B. In FIG. 8, in step S1, a photograph is taken of the wall B as a subject, and the acquisition unit 11 acquires the target image B and the target shooting distance B. Note that the image quality of the target image may be within an acceptable range depending on the wavelength of the electromagnetic wave that is the target of the scattering loss (e.g., a wavelength in the 300 GHz band, etc.).

[0040] In step S2, the surface roughness value acquisition unit 12 executes a contour extraction image analysis process on the target image B to extract contours of objects appearing in the target image B. As a result, 5,000 contours of objects are extracted as black dots from the target image B.

[0041] In step S3, the surface roughness value acquisition unit 12 executes RGB image analysis processing on the target image B to obtain the luminance distribution of each RGB component from the target image B. As a result, the width of the luminance distribution of the R component "152", the width of the luminance distribution of the G component "171", and the width of the luminance distribution of the B component "170" are obtained from the target image B.

[0042] In step S4, the correlation distance acquisition unit 13 executes a spectrum analysis process on the target image B to obtain a power spectrum from the target image B, and obtains the strongest frequency "P=300" in the power spectrum.

[0043] In step S5, the surface roughness value acquisition unit 12 acquires, from the relational expression for the surface roughness value σ_h, “σ_h=f(K,R,G,B)”, a surface roughness value “σ_h=bbb” for wall B, which corresponds to the number of extracted contour objects “K=5000” and the calculated luminance distributions “R component luminance distribution width “R=152”, G component luminance distribution width “G=171”, and B component luminance distribution width “B=170”.

[0044] The correlation distance acquisition unit 13 acquires, for wall B, the correlation distance "l=fff" corresponding to the strongest frequency "P=300" in the power spectrum and the object shooting distance B from the relational expression "l=g(P, d)" for the correlation distance l.

[0045] 9 to 12 are diagrams for explaining an example of a method for calculating ER model parameters according to this embodiment. The method for calculating ER model parameters according to this embodiment will be explained with reference to Figs. 9 to 12.

[0046] In this embodiment, the first parameter α and the second parameter S used in the ER model are obtained using the surface roughness value σ_h, the correlation distance l, and the complex dielectric constant ε.

[0047] A random rough surface is generated in advance using 3DCG software. In generating this random rough surface, a surface roughness value σ_h and a correlation distance l are specified. Next, an electromagnetic field simulation is performed on the generated random rough surface using a Finite Difference Time Domain (FDTD) method or the like, as illustrated in FIG. 9. In this electromagnetic field simulation, a complex dielectric constant ε of the random rough surface is specified. As a result of the electromagnetic field simulation, scattering loss is obtained.

[0048] Next, as illustrated in FIG. 10, fitting of the first parameter α and the second parameter S is performed based on the scattering loss resulting from the electromagnetic field simulation.

[0049] Next, from the fitting results of the first parameter α and the second parameter S, the relational equation “α=h(σ_h, l, ε)” between the surface roughness value σ_h, the correlation distance l, and the complex dielectric constant ε and the first parameter α is obtained, as illustrated in FIG. 11.

[0050] In addition, from the fitting results of the first parameter α and the second parameter S, a relational equation “S=i(σ_h, l, ε)” between the surface roughness value σ_h, the correlation distance l, and the complex dielectric constant ε and the second parameter S is obtained, as illustrated in FIG. 12.

[0051] The actual first parameter α and second parameter S are calculated using the relational expression "α=h(σ_h,l,ε)" of the first parameter α and the relational expression "S=i(σ_h,l,ε)" of the second parameter S calculated as above.

[0052] The scattering loss calculation unit 14 acquires the first parameter α corresponding to the surface roughness value σ_h of the object acquired by the surface roughness value acquisition unit 12, the correlation distance l of the object acquired by the correlation distance acquisition unit 13, and the complex dielectric constant ε of the object from the relational expression "α=h(σ_h,l,ε)" of the first parameter α. The scattering loss calculation unit 14 acquires the second parameter S corresponding to the surface roughness value σ_h of the object acquired by the surface roughness value acquisition unit 12, the correlation distance l of the object acquired by the correlation distance acquisition unit 13, and the complex dielectric constant ε of the object from the relational expression "S=i(σ_h,l,ε)" of the second parameter S. The scattering loss calculation unit 14 calculates the scattering loss of the object by the above formula (1) using the acquired first parameter α and second parameter S.

[0053] Although the scattering loss calculation method described above uses the ER model, the present invention is not limited to this. For example, a scattering loss calculation method that does not use the ER model may be used.

[0054] As described above, according to this embodiment, the scattering loss of an object, such as a wall, can be obtained from an image in which the object is captured, thereby obtaining the effect of easily obtaining the scattering loss of the object.

[0055] This will make it possible to improve the overall service quality in wireless communication applications, for example, and thereby contribute to Goal 9 of the United Nations Sustainable Development Goals (SDGs), which is to "Build resilient infrastructure, promote sustainable industrialization and foster innovation."

[0056] Although an embodiment of the present invention has been described in detail above with reference to the drawings, the specific configuration is not limited to this embodiment, and design changes and the like that do not deviate from the gist of the present invention are also included.

[0057] In addition, a computer program for implementing the functions of the information processing device described above may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read into a computer system and executed. Note that the "computer system" referred to here may include hardware such as an OS and peripheral devices. In addition, the term "computer-readable recording medium" refers to writable non-volatile memory such as a flexible disk, an optical magnetic disk, a ROM, or a flash memory, a portable medium such as a DVD (Digital Versatile Disc), or a storage device such as a hard disk built into a computer system.

[0058] Furthermore, the term "computer-readable recording medium" includes devices that retain a program for a certain period of time, such as volatile memory (e.g., DRAM (Dynamic Random Access Memory)) within a computer system that serves as a server or client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. The program may be transmitted from a computer system in which the program is stored in a storage device or the like to another computer system via a transmission medium, or by a transmission wave in the transmission medium. Here, the "transmission medium" that transmits the program refers to a medium that has a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for implementing some of the functions described above, or may be a so-called differential file (differential program) that can implement the functions described above in combination with a program already recorded in the computer system. [Explanation of symbols]

[0059] 1...information processing device, 11...acquisition unit, 12...surface roughness value acquisition unit, 13...correlation distance acquisition unit, 14...scattering loss calculation unit, 20...storage unit

Claims

1. An acquisition unit that acquires an image including an object, an object shooting distance that is a distance from a position of an imaging device that captures the image to the object that is a subject, and a complex dielectric constant of the object; a surface roughness value acquiring unit that acquires a surface roughness value indicating the roughness of the surface of the object from the image; a correlation distance acquisition unit that obtains a correlation distance according to the object shooting distance and a frequency component of the image; a scattering loss calculation unit that calculates a scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance; An information processing device comprising:

2. The surface roughness value acquisition unit is Extracting a contour of an object from the image; A luminance distribution is obtained from the image. obtaining the number of objects with the extracted contour and the surface roughness value corresponding to the obtained luminance distribution from the previously obtained relationship between the number of objects with the contour, the luminance distribution, and the surface roughness value; The information processing device according to claim 1 .

3. The correlation distance acquisition unit A power spectrum is obtained from the image. obtaining a correlation distance corresponding to the obtained power spectrum and the object shooting distance from a relationship between the previously obtained power spectrum of the image, the distance from the position of the imaging device that captured the image to the object, and the correlation distance; The information processing device according to claim 1 .

4. The scattering loss calculation unit calculates, from the surface roughness value, the complex dielectric constant, and the correlation distance, a first parameter that determines a beam width of a scattered wave for each surface element and a second parameter that determines an intensity of a scattered wave for each surface element, the first parameter being used in a scattering loss model. The information processing device according to claim 1 .

5. An information processing method executed by an information processing device, An acquisition step of acquiring an image including an object, an object shooting distance which is a distance from a position of an imaging device that captured the image to the object that is a subject, and a complex dielectric constant of the object; a surface roughness value acquisition step of obtaining a surface roughness value indicating the roughness of the surface of the object from the image; a correlation distance acquisition step of obtaining a correlation distance according to the object shooting distance and a frequency component of the image; a scattering loss calculation step of calculating a scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance; An information processing method comprising:

6. On the computer, An acquisition step of acquiring an image including an object, an object shooting distance which is a distance from a position of an imaging device that captured the image to the object that is a subject, and a complex dielectric constant of the object; a surface roughness value acquisition step of obtaining a surface roughness value indicating the roughness of the surface of the object from the image; a correlation distance acquisition step of obtaining a correlation distance according to the object shooting distance and a frequency component of the image; a scattering loss calculation step of calculating a scattering loss of the object using the surface roughness value, the complex dielectric constant, and the correlation distance; A computer program for executing the above.

Images