System, program and method

Abstract

A system is provided that can identify a first region in which a change has occurred and identify a second region within the first region. [Solution] A system including at least one computer device. The system includes a first area specifying means for specifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a part of an area in the first image, a selection receiving means for receiving a selection of a second area in the first area based on a third image capturing at least a part of the first area, the first image, or the second image, and an address specifying means for specifying an address corresponding to the second area. The first image, the second image, and / or the third image are images captured from above the ground.

Description

[Technical field]

[0001] The present invention relates to a system, a program and a method. [Background technology]

[0002] It has been disclosed that a method is used to determine whether a house in an aerial photograph or satellite image is vacant or not, based on machine learning data that estimates vacant houses in images generated based on pixel information of the vacant house's site (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2019 / 225597 Summary of the Invention [Problem to be solved by the invention]

[0004] The present invention can solve, for example, any of the following problems. A first problem of the present invention is to provide a system capable of identifying a first area in which a change has occurred and identifying a second area within the first area. A second problem of the present invention is to provide a system capable of identifying a first area in which a change has occurred and further identifying the owner of real estate corresponding to an address from the address corresponding to the first area. [Means for solving the problem]

[0005] The object of the present invention is to [1] A system including at least one computer device, the system including: a first area identification means for identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time, the second image capturing at least a portion of the first area; a selection receiving means for receiving a selection of a second area in the first area based on a third image capturing at least a portion of the first area, the first image, or the second image; and an address identification means for identifying an address corresponding to the second area, wherein the first image, the second image, and / or the third image are images captured from above the ground; [2] A system including at least one computer device, the system including: a first area specifying means for specifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time, the second image capturing at least a part of an area in the first image; and a second area specifying means for specifying a second area in the first area that satisfies a predetermined condition based on a third image capturing at least a part of the first area, the first image, the second image, and the third image being images captured from above the ground; [3] The system according to [1] or [2], wherein the first image and the second image are captured images having a lower resolution than the third image; [4] The system of [1] or [2], wherein the third image is an optical image taken during the day, and the first image and the second image are optical, infrared, or SAR images taken at night; [5] The first time belongs to a different day from the second time and is a later time than the second time, The system according to any one of the above [1 to [4], wherein the first image and the second image are images taken during a predetermined time period; [6] The system according to any one of [2] to [5], wherein the second area identification means identifies, based on the third image, a second area in the first area in which a predetermined change has occurred and / or a second area having a predetermined real estate attribute; [7] The system according to [6], wherein the second region identification means uses image data relating to an image captured from above the ground as input data, and uses information regarding a position in the captured image and a change in the region corresponding to the position as output data, to identify the second region in which a predetermined change has occurred, using a machine-learned prediction model; [8] The system according to [6], wherein the second area identification means uses image data relating to an image captured from the air above the ground as input data, and uses information regarding a position in the captured image and the attributes of real estate in the area corresponding to the position as output data, to identify the second area having a predetermined property attribute using a machine-learned prediction model; [9] The system described in [2], wherein the second region identification means identifies a second region in which a change has occurred within the first region based on the third image taken at a third time and a fourth image taken at a fourth time and capturing at least a part of the first region, and the first image and the second image are images taken at a lower resolution than the third image and the fourth image, or the third image and the fourth image are optical images taken during the day, and the first image and the second image are optical images, infrared images, or SAR images taken at night;

[10] The system according to [9], wherein the first time belongs to a different day from the second time and is later than the second time, the third time is later than the first time, and the fourth time is earlier than the second time;

[11] The system according to any one of [2] to

[10] , further comprising an address identification means for identifying an address corresponding to the second area;

[12] The system according to [1] or

[11] , wherein the address identification means identifies a latitude and longitude corresponding to at least one location within the second region, and identifies an address corresponding to the identified latitude and longitude;

[13] The system according to [1],

[11] or

[12] , further comprising an owner identification means for identifying an owner of real estate corresponding to the address identified by the address identification means, based on a correspondence relationship between the address and the owner of the real estate corresponding to the address;

[14] A system having at least one computer device, comprising: a first area identification means for identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a partial area within the first image; an address identification means for identifying an address corresponding to the first area; and an owner identification means for identifying an owner of real estate corresponding to the address identified by the address identification means based on a correspondence between the address and the owner of the real estate corresponding to the address; a system in which the first image and the second image are images taken from above the ground;

[15] The system according to

[14] , wherein the owner identification means identifies the owner of the real estate corresponding to the address identified by the address identification means when a predetermined change occurs in the first area and / or when the first area has a predetermined real estate attribute;

[16] The system according to any one of

[13] to

[15] , wherein the owner identification means identifies the owner of the real estate corresponding to the address identified by the address identification means and the owner's contact information based on a correspondence relationship between the address and the owner of the real estate corresponding to the address and the owner's contact information;

[17] The system according to any one of

[13] to

[16] , wherein the address identified by the address identification means is a parcel number, and the owner identification means identifies the owner of the real estate corresponding to the identified parcel number based on a correspondence between the parcel number and the owner of the real estate corresponding to the parcel number;

[18] A program for causing a computer device to function as a first area identification means for identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a portion of the area in the first image, a selection receiving means for receiving a selection of a second area of ​​the first area based on a third image capturing at least a portion of the first area, the first image, or the second image, and an address identification means for identifying an address corresponding to the second area, wherein the first image, the second image, and / or the third image are images captured from above the ground;

[19] A program for causing a computer device to function as a first area identification means for identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a partial area within the first image, and as a second area identification means for identifying a second area in the first area that satisfies a predetermined condition based on a third image capturing at least a part of the first area, wherein the first image, the second image, and the third image are images captured from above the ground;

[20] A program that causes a computer device to function as a first area identification means that identifies a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a partial area within the first image, an address identification means that identifies an address corresponding to the first area, and an owner identification means that identifies an owner of real estate corresponding to the address identified by the address identification means based on a correspondence between the address and the owner of the real estate corresponding to the address, wherein the first image and the second image are images taken from above the ground;

[21] A method executed in a system having at least one computer device, the method comprising: a first area identification step of identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time, the second image capturing at least a part of the first area; a selection receiving step of receiving a selection of a second area of ​​the first area based on a third image capturing at least a part of the first area, the first image, or the second image; and an address identification step of identifying an address corresponding to the second area, wherein the first image, the second image, and / or the third image are images captured from above the ground;

[22] A method executed in a system having at least one computer device, the method comprising: a first area identification step of identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time, the second image capturing at least a portion of an area in the first image; and a second area identification step of identifying a second area in the first area that satisfies a predetermined condition based on a third image capturing at least a portion of the first area, the first image, the second image, and the third image being images captured from above the ground;

[23] A method executed in a system having at least one computer device, the method comprising: a first area identification step of identifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a partial area within the first image; an address identification step of identifying an address corresponding to the first area; and an owner identification step of identifying an owner of real estate corresponding to the address identified in the address identification step based on a correspondence between the address and the owner of the real estate corresponding to the address, wherein the first image and the second image are images taken from above the ground; This can be solved by: Effect of the Invention

[0006] According to the present invention, it is possible to provide a system that can identify a first area where a change has occurred and identify a second area within the first area. Also, according to the present invention, it is possible to provide a system that can identify a first area where a change has occurred and, from an address corresponding to the first area, identify the owner of real estate corresponding to the address. [Brief description of the drawings]

[0007] [Figure 1] 1 is a block diagram showing a configuration of a system according to an embodiment of the present invention. [Diagram 2] 2 is a block diagram showing a hardware configuration of a user terminal according to an embodiment of the present invention. FIG. [Diagram 3]2 is a block diagram showing a hardware configuration of a server device according to an embodiment of the present invention. FIG. [Figure 4] FIG. 13 is a flowchart showing real estate and owner identification processing according to an embodiment of the present invention. [Diagram 5] FIG. 11 is a diagram for explaining a process for identifying an address according to an embodiment of the present invention. [Figure 6] FIG. 13 is a flowchart showing real estate and owner identification processing according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] The following describes an embodiment of the present invention, but the present invention is not limited to the following embodiment, as long as it does not go against the spirit of the present invention. The order of each process constituting the flowchart described below is random as long as there is no contradiction or inconsistency in the process content, and it is also possible to omit a part of each process constituting the flowchart or add a new process to each process constituting the flowchart, as long as there is no contradiction or inconsistency in the process content. In addition, the device that executes each process constituting the flowchart can be changed to another device, as long as it does not go against the spirit of the present invention. In that case, the process content can be changed so that there is no contradiction or inconsistency in the process content.

[0009] [System configuration] FIG. 1 is a block diagram showing a configuration of a system according to an embodiment of the present invention. The system 10 includes at least one computer device. The system 10 may include a user terminal 1, a server device 2, and an administrator terminal 3. The user terminal 1, the server device 2, and the administrator terminal 3 are communicably connected to each other via a communication network 4. In the system 10, any of the user terminal 1, the server device 2, and the administrator terminal 3 may function as an information processing device. When any of the user terminal 1, the server device 2, and the administrator terminal 3 functions as an information processing device, transmission and reception of information is performed between at least two or more terminals of the user terminal 1, the server device 2, and the administrator terminal 3 as necessary. Note that the number of the user terminal 1, the server device 2, and / or the administrator terminal 3 is not particularly limited as long as it is one or more.

[0010] The system 10 may be composed of, for example, one computer device (standalone type), one or more server devices and one or more terminal devices (client-server type), or a host device and one or more guest devices (peer-to-peer type). The server device 2 may function in a distributed manner across multiple computer devices. For example, instead of the server device 2, a distributed ledger technology such as a blockchain may be used.

[0011] [User terminal] The user terminal 1 is a terminal operated by a user of the system 10. Fig. 2 is a block diagram showing the hardware configuration of the user terminal according to the embodiment of the present invention. The user terminal 1 includes a control unit 11, a RAM 12, a storage unit 13, an input unit 14, a display unit 15, and a communication interface 16, each of which is connected by a bus.

[0012] The control unit 11 is composed of a CPU and a ROM. The control unit 11 executes programs stored in the storage unit 13 and controls the user terminal 1. The RAM 12 is a work area for the control unit 11. The storage unit 13 is a storage medium for saving programs and data. The control unit 11 performs arithmetic processing based on the programs and data read from the RAM 12 and data inputted via the input unit 14.

[0013] The display unit 15 has a display screen. The control unit 11 outputs a video signal for displaying an image on the display screen according to the result of the arithmetic processing. Here, the display screen of the display unit 15 may be a touch panel equipped with a touch sensor. In this case, the touch panel functions as the input unit 14.

[0014] The communication interface 16 can be connected to the communication network 4 wirelessly or via a wire, and can transmit and receive data to and from other computer devices via the communication network 4. Data received via the communication interface 16 is loaded into the RAM 12, and the control unit 11 performs arithmetic processing.

[0015] [Server device] 3 is a block diagram showing a hardware configuration of a server device according to an embodiment of the present invention. The server device 2 includes at least a control unit 21, a RAM 22, a storage unit 23, and a communication interface 24, which are connected to each other via an internal bus.

[0016] The control unit 21 is composed of a CPU and a ROM, and executes programs stored in the storage unit 23 to control the server device 2. The control unit 21 also has an internal timer that measures time. The RAM 22 is the work area of ​​the control unit 21. The storage unit 23 is a storage area for saving programs and data. In other words, the storage unit 23 functions as a recording medium that stores programs. The control unit 21 reads out the programs and data from the RAM 22, and performs program execution processing based on information received from the user terminal 1 or the administrator terminal 3, respectively.

[0017] [Administrator terminal] The administrator terminal 3 is a terminal operated by an administrator, operator, or provider of the system 10. The administrator terminal 3 may have the same configuration as the user terminal 1. The administrator terminal 3 may include, for example, a control unit, a RAM, a storage unit, an input unit, a display unit, and a communication interface, each of which may be connected by an internal bus.

[0018] The program may be stored in a recording medium such as a CD-ROM. In this case, the program stored in the recording medium may be installed in the user terminal 1, the server device 2, or the administrator terminal 3 to execute the specified function. Alternatively, the program may be distributed from a computer device outside the system. In this case, the program distributed from a computer device outside the system may be installed in the user terminal 1, the server device 2, or the administrator terminal 3 to execute the specified function.

[0019] [Real estate and owner identification processing] Next, a first embodiment of real estate and owner identification processing in a system according to an embodiment of the present invention will be described. FIG. 5 is a diagram showing a flowchart of real estate and owner identification processing according to an embodiment of the present invention. Note that real estate is a concept that includes both land and buildings. In the following, for example, a case where a system 10 is composed of a user terminal 1 and a server device 2 will be described.

[0020] The user operates the input unit 14 of the user terminal 1 to identify the area where a change has occurred from the captured image, and initiates a real estate and owner identification process (hereinafter, the real estate and owner identification process will be referred to as the "identification process") to identify the owner of the real estate corresponding to the identified area. First, the user operates the input unit 14 of the user terminal 1 to start dedicated application software for executing the identification process. The user inputs a user ID and password to identify the user into the user terminal 1. The server device 2 receives the user ID and password input into the user terminal 1, authenticates the user, and permits the user to log in to the system 10. Alternatively, the user may log in to the system 10 by accessing the server device 2 from the user terminal 1 via a web browser.

[0021] Next, the user operates the input unit 14 of the user terminal 1 to input a request to start the identification process. The start request is transmitted from the user terminal 1 to the server device 2 and received by the server device 2. The start request may include information regarding the specified change to be identified and / or information regarding the attributes of the specified real estate to be identified. Details of the specified change and the attributes of the specified real estate will be described later. The start request may also include information regarding the range in which to search for the specified change that has occurred and / or the range in which to search for real estate having the specified attributes in the identification process, as well as information regarding the period of the search.

[0022] When the server device 2 receives the start request, it acquires the first image and the second image (step S1). The first image and the second image are images captured from above the ground. The captured images may be stored in advance in the storage unit 23 of the server device 2, or may be read by the server device 2 from an external storage device in which the captured images are stored. The server device 2 may also acquire the captured images in cooperation with an external system that holds the captured images. The external system is, for example, a system configured from another computer device. When collaborating with the external system, the server device 2 transmits an acquisition request for the first image and the second image to the other computer device. The acquisition request includes information on the date and time of capture of the captured image to be acquired and information on the area where the image was captured. The captured image is stored in association with information on the date and time of capture and the area where the image was captured.

[0023] The captured image is not particularly limited as long as it is an image of the ground taken from the sky, and examples of the captured image include an aerial photograph and a satellite image. An aerial photograph is a photograph of the ground taken by a camera mounted on an aircraft. A satellite image is image data acquired by a sensor mounted on an artificial satellite. A satellite image is, for example, an optical image (also called a visible image), an infrared image (also called a thermal infrared image), or a SAR (synthetic aperture radar) image (also called a synthetic aperture radar image). A captured image may be an image obtained by combining a plurality of images. In addition, the captured image includes not only images acquired as image data itself, but also image data obtained by processing data acquired by a sensor.

[0024] The first image is an image taken at a first time. The second image is an image taken at a second time. The first time belongs to a different day from the second time. The first time is later than the second time. The second time may be a time going back a predetermined period or more from the first time. The predetermined period is not particularly limited and can be set appropriately by the administrator or the user. The predetermined period is preferably a period during which a change in the real estate can be detected, and may be, for example, a period of days, weeks, months, or years. The first time may be the time of taking the most recently acquired image based on the time when the start request is input to the user terminal 1 or the time when the server device 2 receives the start request. For example, if the predetermined period is one week, the second time is one week before the first time. In step S1, if there is no second image taken at a time that matches the predetermined period, a second image taken before the predetermined period may be acquired. If the initiation request includes information regarding the period to search, the first and second times are specified to coincide with the period.

[0025] The first and second images may be images taken in a predetermined time period. Examples of the predetermined time period include morning (between 9:00 and 12:00), afternoon (between 12:00 and 15:00), evening (between 16:00 and 18:00), and night (between 22:00 and 2:00). By using the first and second images taken in the same time period, it becomes easier to identify the first region in step S2 described below.

[0026] The second image is a photographed image of at least a part of the area in the first image. The photographed image of at least a part of the area in the first image is a photographed image of a part or all of the area photographed in the first image. For example, when the first image is a photographed image of A city and B city, the photographed image of A city is a photographed image of at least a part of the area in the first image. Note that multiple second images may be acquired for one first image, one second image may be acquired for multiple first images, or multiple second images may be acquired for multiple first images. A second image that is a photographed image of at least a part of the area in one first image is also referred to as a second image corresponding to the one first image.

[0027] A first image and a second image corresponding to the first image (also referred to as a set of a first image and a second image) are images of a specific area photographed at different times or days. The set of a first image and a second image acquired in step S1 may be one, or may be two or more. When two or more sets of a first image and a second image are acquired, a part or all of the area photographed in each first image is different.

[0028] The shooting range of the first image and the second image acquired by step S1 is not particularly limited and can be appropriately set by the administrator or the user. The shooting range may be a range corresponding to the information on the range to be searched included in the start request, or may be a preset range. For example, when an area to be a target of the specific process is input as information on the range to be searched in the start request, the first image and the second image corresponding to that area are acquired. For example, when it is set in advance to search the 23 wards of Tokyo, the first image and the second image capturing the 23 wards of Tokyo are acquired by step S1. In addition, the shooting range of the first image and the second image may be wider than the third image described later and the fourth image described later.

[0029] The first and second images may be images with the same resolution as the third and fourth images described below, or may be images with a lower resolution. The resolution of a captured image represents the distance on the ground that one side of a pixel, which is the smallest unit that constitutes an image, corresponds to. For example, the resolution of the first and second images may be 5 km, and the resolution of the third and fourth images may be 1 m. It is also preferable that the first and second images, or the third and fourth images, have the same resolution.

[0030] It is preferable that the first image and the second image, or the third image described below and the fourth image described below, have the same scale. Having the same scale means that the length in the real world corresponding to a unit distance on the image (e.g., 1 inch) is the same. The scale of the first image and the second image may be the same as that of the third image and the fourth image, or may be smaller. The scale becomes smaller as the length in the real world corresponding to the unit distance is longer. For example, when the scale of the first image and the second image is 1 / 10,000, the scale of the third image and the fourth image may be 1 / 100.

[0031] The first image, the second image, the third image described later, and the fourth image described later may be an optical image taken during the day, an optical image taken at night (also called a nighttime light image), an infrared image, or an SAR image. In this case, it is preferable that the first image and the second image are images taken with a lower resolution than the third image and the fourth image. Alternatively, when the third image described later and the fourth image described later are optical images taken during the day, the first image and the second image may be an optical image taken during the day, a nighttime light image, an infrared image, or an SAR image.

[0032] When the first image and the second image are acquired in step S1, the server device 2 identifies the first area based on the first image and the second image (step S2).

[0033] The first region is a region in which a change has occurred. The region in which a change has occurred is a region in which a predetermined change has occurred in the real world. The concept of a region includes both an area having a predetermined range and a position indicating a predetermined point. The region may be a region corresponding to one pixel, or may be a region including multiple pixels. The region may be shown as quadrangular data selected from a region divided into a mesh at equal intervals, or may be shown as polygon data of a polygonal shape surrounded by lines.

[0034] The server device 2 compares images (e.g., a first image and a second image) taken at different times of the same area with the same resolution, and when there is an area that satisfies a predetermined condition, it can identify the area where a change has occurred. The predetermined condition is not particularly limited, but may be that the change in pixel (RGB or HSV) value in the area is greater than a predetermined value, or that a difference has been extracted by difference extraction.

[0035] For example, in step S2, first, the server device 2 aligns the area shown in the first image with the area shown in the second image. A known process can be applied for the alignment process. Next, the server device 2 determines whether or not a predetermined condition is satisfied for each predetermined area in the first image and the second image. The predetermined area can be set appropriately, but may be an area corresponding to the resolution, for example, a rectangular area including nine pixels arranged in a 3×3 array. The server device 2 can specify a part or all of the area determined to satisfy the predetermined condition as the first area.

[0036] More specifically, for example, a case where the server device 2 identifies the first region using RGB values ​​will be described. The RGB values ​​indicate the color of one pixel with values ​​of R (red), G (green), and B (blue). Each of R, G, and B is represented by a value of 256 levels from 0 to 255.

[0037] First, the server device 2 identifies corresponding positions in the first image and the second image. For example, the server device 2 identifies a group of pixels having the same point (e.g., latitude and longitude) in the real world in each of the first image and the second image. The latitude and longitude of a pixel may be, for example, the latitude and longitude of a position in the real world corresponding to the center position of the pixel. Next, the server device 2 identifies the amount of change of pixels in a window. A window is a portion that indicates a predetermined range in an image. A window is a rectangular portion that includes multiple pixels. The number of pixels included in one window can be designed appropriately according to the resolution of the image.

[0038] When identifying the amount of change of pixels in the window, for example, the server device 2 calculates the amount of change of RGB values ​​of pixels in the window. Specifically, for each pixel included in the window, the following calculation is performed between corresponding pixels of the first image and the second image. First, the server device 2 compares the pixels of the first image and the second image, adds the square of the difference of the R value, the square of the difference of the G value, and the square of the difference of the B value, and multiplies the result by the weighting value in the window. Then, the server device 2 calculates the amount of change of pixels in the window by taking the square root of the multiplied value. The method of weighting in the window is not particularly limited, and a known method can be used. For example, weighting such as a Gaussian filter or an averaging filter can be used as the weighting value. The weighting value can be set so that the weight becomes larger toward the center of the window and becomes smaller as it moves away from the center.

[0039] After calculating the amount of pixel change for all pixels in the window, the server device 2 sums up all the amounts of change for the pixels in the window to identify the amount of change in the window. At this time, weighted summation is performed in the window, so that it does not depend on a single pixel but reflects changes in the entire local area. Next, the server device 2 uses a preset offset value to move the window up, down, left, and right (also called a sliding window) and similarly identifies the amount of change in the window. The movement of the window may be repeated until a predetermined range (e.g., 80%) or more of the first image and the second image have been processed.

[0040] After identifying the amount of change in each window, the server device 2 executes a threshold determination of the amount of change in the window. For example, the server device 2 determines whether the amount of change in the window exceeds a predetermined threshold. If the threshold is exceeded, the server device 2 can identify that a change has occurred in an area included in the window that has exceeded the threshold. The server device 2 can also identify the area as a first area in which a change has been detected. The first area may be the entire window area, or a part of the window area identified by an offset value. For example, if the offset value is one pixel, one pixel in the center of the identified window may be identified as the area in which a change has occurred. Also, for example, if the offset value is three pixels, nine pixels (3×3) in the center of the identified window may be identified as the area in which a change has occurred.

[0041] When the server device 2 generates polygon data, the server device 2 identifies a window in which the amount of change exceeds the threshold in the same manner as described above. The server device 2 can generate polygon data by identifying the outline of the entire window or a part of a region in the window in which a change has occurred, for the window in which the amount of change exceeds the threshold.

[0042] Next, the server device 2 identifies the latitude and longitude (hereinafter referred to as latitude and longitude) of the first area identified in step S2 (step S3). The captured image acquired in step S1 uses image data that can identify the latitude and longitude of each point or area in the captured image. Therefore, when the first area is identified in step S2, the server device 2 can identify the latitude and longitude corresponding to at least one position of the first area based on the position of the first area in the first image or the second image. The at least one position of the first area may be a predetermined point included in the first area in the first image or the second image. The predetermined point may be the center position of the identified first area. Furthermore, when the first area is a rectangular area, the predetermined point may be a point corresponding to four points: the upper left, upper right, lower right, and lower left.

[0043] When the latitude and longitude of the first area are identified in step S3, the server device 2 acquires a third image (step S4). The third image is an image captured from above the ground, and is an image of at least a part of the first area. The third image may be an image captured so as to include the entire first area. The captured image is synonymous with the captured image described above, and therefore a description thereof will be omitted.

[0044] Here, the third image is an image taken at a third time. The third time may be a time after the first time, a time before the second time, or a time between the second time and the first time. The third image may be an image taken after the second time and within a predetermined period (e.g., three days) from the first time, or may be an image taken most recently. The time at which the third image is to be acquired may be specified according to information on the change input in the start request and / or information on the attributes of the real estate.

[0045] The captured image acquired in step S4 uses image data that can identify the date and time of capture and the latitude and longitude of each point or area in the captured image. Therefore, the server device 2 can identify the third image using the first time and / or the second time and the latitude and longitude identified in step S3.

[0046] As described above, the third image may be a high-resolution captured image. For example, the high-resolution captured image may have a resolution of 1 m or less. The third image may be an optical image captured during the day.

[0047] In step S4, when the server device 2 cooperates with an external system, the server device 2 transmits a request to acquire the third image to another computer device. The request includes information on the shooting date and time of the captured image to be acquired and information on the area where the image was captured (for example, the latitude and longitude specified in step S3). The external system that cooperates with the server device 2 in step S4 and the external system that cooperates with the server device 2 in step S1 may be the same system or different systems.

[0048] The acquisition of the third image in step S4 may be performed in response to an input by the user operating the user terminal 1. For example, the process of step S4 may be performed by transmitting a request to acquire the third image in response to an input to the user terminal 1. Alternatively, the user inputs specific information capable of identifying the third image to the user terminal 1. The specific information may then be transmitted from the user terminal 1 to the server device 2, and the server device 2 may acquire the third image based on the received specific information. The specific information may include, for example, information regarding the time when the captured image to be acquired was captured, information capable of identifying the first area, and the like. The information capable of identifying the first area may be, for example, the latitude and longitude identified in step S3, an address corresponding to the first area, a place name corresponding to the first area, and the like.

[0049] When the third image is acquired in step S4, the server device 2 identifies a second area that satisfies a predetermined condition in the first area based on the third image. The predetermined condition may be, for example, that a predetermined change has occurred or that the second area has a predetermined real estate attribute.

[0050] First, the server device 2 identifies a second area in which a predetermined change has occurred in the first area based on the third image (step S5). The change in the area identifies what state the real estate has changed from, what state it has changed to, or what state it has changed from.

[0051] The specified change is not particularly limited, but may be, for example, demolition, new construction, rebuilding, or repair. Demolition means that a building is disassembled and removed from an area. New construction means that a building is constructed from a vacant lot. Reconstruction means that a building is replaced with a new building. Repair means that a building is repaired, and examples of repair include remodeling and exterior construction.

[0052] The method by which the server device 2 identifies the second area in which a predetermined change has occurred in the third image (photographed image) is not particularly limited. For example, the server device 2 can use the first prediction model to identify the second area in which a predetermined change has occurred based on the third image acquired in step S4. The first prediction model is a prediction model that is machine-learned using image data (information such as RGB of each pixel constituting an image) in which a change (e.g., demolition, new construction, reconstruction, or repair) is clear among the photographed images that are a reference (sample) as input data, and information on a position in the photographed image and a change in the area corresponding to the position as output data.

[0053] Here, image data showing the same change as the change identified in step S5 is used as input data. In this way, the server device 2 can identify the second area where a predetermined change has occurred from the captured image. For example, if the third image is captured after the first time, a captured image of the area captured near the time when the change is completed is used as input data. If the third image is captured before the second time, a captured image near the time when the change occurs is used as input data. If the third image is captured between the second time and the first time, a captured image during the change is occurring is used as input data.

[0054] When the server device 2 identifies demolition as a specified change, that is, when identifying a position on the photographed image corresponding to the area before demolition, the area being demolition, or the area that has been demolished, the server device 2 uses a first prediction model that uses as input data multiple image data of the area before demolition, the area being demolition, or the area that has been demolished, photographed from the air.

[0055] When the server device 2 identifies a new construction as a specified change, that is, when identifying a position on a photographed image corresponding to an area before construction of a building begins, an area after construction of a building begins or is under construction, or an area after construction is completed, the server device 2 uses a first prediction model that uses as input data multiple image data of the area of ​​a building before construction begins, the area after construction begins or is under construction, or the area after construction is completed, photographed from the air.

[0056] When the server device 2 identifies reconstruction as a specified change, that is, when identifying a position on a photographed image corresponding to an area of ​​a building before it is demolished, an area of ​​a building during demolition, an area of ​​a building after construction has started or is underway, or an area of ​​a building after completion, the server device 2 uses a first prediction model whose input data are multiple image data of the area of ​​a building before it is demolished, the area during demolition, the area after construction has started or is underway, or the area after completion, photographed from the air.

[0057] When the server device 2 identifies repair as a specified change, that is, when identifying a position on a photographed image corresponding to an area of ​​a building before repair, an area of ​​a building under repair, or an area of ​​a building after repair, the server device 2 uses a first prediction model in which multiple image data of the area of ​​a building before repair, the area under repair, or the area after repair photographed from the sky are used as input data.

[0058] The machine learning algorithm is not particularly limited, and a known algorithm can be used, but it is preferable to use deep learning using a multilayer neural network. The multilayer neural network has an input layer, an output layer, and multiple intermediate layers. Weights are set on the edges connecting the nodes of each layer. Weights corresponding to each input to the node are set on the edges, and the edges are multiplied by the weights corresponding to each input to the node, and the values ​​obtained by multiplying these weights and the bias are added. The value obtained by the addition is nonlinearly transformed using an activation function to calculate an activation value. The calculated activation value becomes the input value passed to the node of the next layer. The number of intermediate layers can be designed as appropriate.

[0059] In step S5, when the server device 2 identifies the second area in which the predetermined change has occurred, the server device 2 identifies the second area having the predetermined real estate attribute in the first area based on the third image (step S6). The attribute identifies the state of the real estate, the purpose for which it is used, or what buildings and facilities are present. In step S6, the server device 2 may identify the second area having the predetermined real estate attribute from the second area in which the predetermined change has occurred identified in step S5.

[0060] The specified real estate attributes (also referred to as specified attributes) are not particularly limited, but examples thereof include vacant houses, unused land, parking lots, agricultural land, and material storage yards. A vacant house means a building where no one lives, and unused land means land that is not being used. A parking lot is land that is used as a place to park vehicles. Agricultural land is land that is used for agriculture, and examples thereof include rice fields and farms. A material storage yard is land that is used as a storage area for materials such as construction materials.

[0061] Furthermore, the predetermined attribute may be the presence of a predetermined building. The predetermined building is not particularly limited, but may be, for example, a condominium, an apartment, a house, or an office building. The predetermined building may be a building that is more than a predetermined number of years old, or a building that is less than a predetermined number of years old.

[0062] There is no particular limitation on the method by which the server device 2 specifies an area corresponding to real estate having a predetermined attribute in the third image (photographed image). For example, the server device 2 can specify an attribute of real estate corresponding to each area of ​​the photographed image based on information (RGB information) about pixels constituting the photographed image, thereby specifying an area corresponding to real estate having a predetermined attribute.

[0063] For example, the server device 2 can use the second prediction model to specify an area corresponding to real estate having a predetermined attribute based on the third image acquired in step S4. The second prediction model is a prediction model trained by machine learning using image data (information such as RGB of each pixel constituting the image) in which the attributes of real estate (for example, vacant house, unused land, parking lot, agricultural land, or material storage area) are clear from the captured image as a reference (sample), and information on the position in the captured image and the attributes of real estate in the area corresponding to the position as output data. Here, image data having the same attribute as the predetermined attribute specified in step S6 is used as input data. In this way, the server device 2 can specify an area corresponding to real estate having a predetermined attribute from the captured image.

[0064] When the server device 2 identifies land that is a vacant house as real estate having a predetermined attribute, that is, when identifying a position on the photographed image that corresponds to land that is a vacant house, the server device 2 uses a second prediction model that uses multiple image data of vacant houses photographed from the sky as input data. In areas where snow accumulates, the server device 2 can also use the state of snow accumulated on the house or site in the photographed image as material for determining whether the house is vacant or not.

[0065] In addition, when the server device 2 identifies an area on the third image corresponding to land that is vacant land, a parking lot, or agricultural land, the server device 2 uses a second prediction model in which multiple image data for each of the vacant land, parking lot, or agricultural land photographed from the air are used as input data.

[0066] The machine learning algorithm is not particularly limited, and a known algorithm can be used. The machine learning algorithm is the same as that described above, and therefore the description thereof will be omitted.

[0067] In addition, if in step S5 the server device 2 does not identify a second area in which a specified change has occurred, or if in step S6 the server device 2 does not identify a second area having specified real estate attributes, the identification process is terminated.

[0068] On the other hand, in step S6, when the server device 2 identifies the second area having the attribute of the predetermined real estate, the server device 2 identifies the latitude and longitude corresponding to at least one position of the identified second area based on the position in the third image of the second area identified as having the attribute of the predetermined real estate in which a predetermined change has occurred (step S7). Next, the server device 2 identifies the address of the real estate corresponding to the identified second area based on the position in the third image of the second area identified as having the attribute of the predetermined real estate in which a predetermined change has occurred (step S8). In step S8, the server device 2 may identify the address of the real estate corresponding to the latitude and longitude identified in step S7. Here, the "address" is a concept including both the address and the lot number. The address is the address determined by the city, town, or village based on the "Law Concerning Addresses (Law No. 119 of 1962)", and the lot number is the number assigned to each real estate by the Legal Affairs Bureau.

[0069] The processing of steps S7 and S8 will be described. Map data of the same area as the area where the third image (photographed image) was photographed is preregistered in the storage unit 23 of the server device 2. Furthermore, for the photographed image acquired in step S4, image data capable of identifying the latitude and longitude of each point or area in the photographed image is used. The image data used is stored in such a way that the position in each image data is associated with the latitude and longitude. The map data stores the address (land number or house number) of each area or area on the map in association with the latitude and longitude of the area or area.

[0070] Therefore, when the second area is specified in steps S7 and S8, the server device 2 can specify the latitude and longitude corresponding to at least one position of the second area based on the position of the second area in the captured image, similar to step S3. Explanations that overlap with step S3 will be omitted. The server device 2 can specify an address (land number or house number) corresponding to the latitude and longitude corresponding to at least one position of the specified second area by referring to map data in which the address of each area or each point on the map is stored in association with the latitude and longitude of each area or each point.

[0071] In step S8, the user terminal 1 can specify the address of the real estate corresponding to the specified second area by using a Cartesian coordinate system on a plane, in addition to the method of specifying the address of the real estate corresponding to the specified second area by using latitude and longitude. In this case, step S7 may be omitted. FIG. 6 is a diagram for explaining the process of specifying an address according to an embodiment of the present invention. Map data 31 of the same area as the area where the photographed image 32 (third image) was photographed is registered in advance in the storage unit 23 of the server device 2.

[0072] In the map data 31, the address of each property in this area is registered in association with the XY coordinates of a Cartesian coordinate system (XY coordinate system) on a plane. A specific point in this area is set as the origin O. With the north-south direction as the Y axis, the north side can be the first and second quadrants and the south side the third and fourth quadrants, and with the east-west direction as the X axis, the east side can be the first and fourth quadrants and the west side the second and third quadrants. The coordinates (X, Y) of the origin O can be expressed as (0, 0), and in FIG. 6, the address of the origin O is registered as address E.

[0073] In step S2, some areas of the photographed image 32 are identified as areas 33a and 33b corresponding to real estate having a predetermined attribute. The map data 31 is set to the same scale as the photographed image 32, and a point in the photographed image 32 corresponding to a specific point in the map data 31 is superimposed so that the point is the same as the origin O of the map data 31 and the direction of the photographed image 32 is the same as the direction of the map data 31, thereby making it possible to identify the address of each area of ​​the photographed image 32. That is, the map data 31 is registered with addresses associated with XY coordinates, and the address of the area can be identified based on the XY coordinates of the area in the photographed image 32 according to this correspondence. Here, the address of the area 33a is address D, and the address of the area 33b is address I.

[0074] If the address identified in step S8 is a residential address, the server device 2 identifies the land number corresponding to the residential address identified in step S7 based on the correspondence between the residential address and the land number (step S9). An address master table in which land numbers are stored in association with residential addresses is registered in the storage unit 23 of the server device 2, and the land number corresponding to the residential address identified in step S8 can be identified by referring to the address master table.

[0075] When the process of step S8 is performed based on a photographed image of an area where the lot number and the address are the same, the process of step S9 can be omitted. The lot number identified in step S8 or S9 is used to identify the owner of real estate having a predetermined attribute in step S11 described later. If the address identified in step S8 is a lot number, step S9 is omitted, and the process proceeds from step S8 to step S10.

[0076] Next, the server device 2 identifies related information corresponding to the address identified in step S8 based on the correspondence between the address and related information corresponding to the address (step S10). The related information is, for example, the real estate use zoning, building coverage ratio, floor area ratio, elementary and junior high schools in the school district, climate, future estimated population, hazard information, real estate appraisal value, etc. In step S10, related information corresponding to the identified latitude and longitude may be identified based on the correspondence between the latitude and longitude and the related information corresponding to the latitude and longitude.

[0077] A real estate use zone is a classification of land use types determined by urban planning. A building coverage ratio is the ratio of a building that can be built on a site. A floor area ratio is the ratio of a building's floor area to the site area. Upper limits are set for building coverage ratios and floor area ratios depending on a real estate use zone. Elementary and junior high schools in a school district are the elementary and junior high schools that students planning to attend school in a specified area should attend. Climate is the average temperature, average precipitation, average snowfall, average amount of sunshine, etc. of a specified area. Estimated future population is an estimate of the future population of a specified area (for example, every five years). Hazard information is information about the risk of disasters for each specified area. Real estate appraisal value is information about the price of real estate. For example, real estate appraisal value includes the price of real estate calculated from the official price, road value, fixed asset tax assessment value, surrounding sales price, etc.

[0078] The method of identifying the related information corresponding to the address or the latitude and longitude is not particularly limited. The server device 2 may identify various related information corresponding to the latitude and longitude identified in step S7 or the address identified in step S8 by using data in which the address or the latitude and longitude is associated with and stored in association with the related information corresponding to the address or the latitude and longitude. In addition, the server device 2 may cooperate with a system composed of other computer devices to identify related information corresponding to the latitude and longitude identified in step S7 or the address identified in step S8. The control unit 11 may use open data to identify related information corresponding to the latitude and longitude identified in step S7 or the address identified in step S8. For example, the server device 2 may access a computer device that stores a database of information related to related information provided by the Geospatial Information Authority of Japan or a local government, and receive related information corresponding to the latitude and longitude or the address.

[0079] Next, the server device 2 identifies the owner of the real estate corresponding to the address identified in step S8 based on the correspondence between the address and the owner of the real estate corresponding to the address (step S11). Information about the identified owner of the real estate is stored in the storage unit 23 of the server device 2 in association with information about the identified second area (step S12). The information about the owner is, for example, the name and contact information of the owner of the real estate. The information about the second area is, for example, the address of the second area (address and / or lot number), latitude and longitude, identified changes, real estate attributes, etc.

[0080] In step S11, the owner of the property corresponding to the address identified in step S8 and the owner's contact information may be identified based on the correspondence between the address, the owner of the property corresponding to the address, and the owner's contact information. In step S8 or S9, if the server device 2 identifies the land number, the server device 2 identifies the owner of the property corresponding to the identified land number and the contact information based on the correspondence between the land number and the owner of the property corresponding to the land number.

[0081] Although the method of identifying the owner of the property corresponding to the address and the contact information of the owner is not particularly limited, it is preferable that the server device 2 identifies the owner of the property and the contact information of the property by using data stored in association with the address and the owner of the property corresponding to the address. For example, an owner master table is registered in the storage unit 23 of the server device 2, in which the owner of the property corresponding to the address (lot number) and the contact information of the owner are stored in association with the address (lot number), and the server device 2 can identify the owner and the contact information of the property corresponding to the address identified in step S8 or the lot number identified in step S8 or S9 by referring to the owner master table.

[0082] In addition, the server device 2 may cooperate with a system composed of other computer devices to identify the owner and his / her contact information corresponding to the land lot identified in step S8 or S9. In this case, the server device 2 can cooperate with, for example, a registration and deposit online application system provided by the Ministry of Justice to identify the owner and his / her contact information corresponding to the address identified in step S8 or the land lot identified in step S8 or S9. The server device 2 can receive registry data in which the owner and his / her contact information corresponding to the land lot number are recorded from the registration and deposit online application system.

[0083] The "owner" identified in step S11 is the name of the owner. In addition, the contact information of the owner identified in step S11 is not particularly limited, but may include a landline telephone number, a mobile telephone number, an email address, a facsimile number, an address (residential address), a postal code, and the like. The identified name and contact information of the owner are transmitted from the server device 2 to the user terminal 1, and are outputted, for example, to be displayed on the display unit 15 of the user terminal 1, so that the user can contact the owner of the real estate in which a specified change has occurred and which has specified attributes, by telephone, e-mail, facsimile, mail, and the like. Which of these contact methods is adopted can be appropriately changed depending on the purpose.

[0084] Next, the server device 2 uses the contact information of the owner identified in step S11 in response to the input to the user terminal 1 to transmit predetermined information to the identified owner, that is, the owner of the real estate having the predetermined attributes (step S13). By executing steps S1 to S13, the identification process is completed.

[0085] The predetermined information transmitted in step S13 is not particularly limited. The predetermined information can be stored in the storage unit 23 by the user operating the input unit 14 of the user terminal 1. The predetermined information stored in the storage unit 23 is read out when step S13 is executed.

[0086] The predetermined information transmitted to the owner of the real estate in step S13 can be appropriately changed according to the predetermined change, the type of the predetermined attribute, the purpose of the user, and the like. For example, if the predetermined change is demolition, the server device 2 can transmit a message or a proposal for selling the real estate, proposing land for renting, proposing rebuilding, and the like to the owner of the real estate. Also, for example, if the predetermined change is new construction or rebuilding, the server device 2 can transmit a message or a proposal for proposing rental, introducing a rental property agent, proposing new facilities, and the like to the owner of the real estate. Also, for example, if the predetermined attribute is vacant land or a vacant house, the server device 2 can transmit a message or a proposal for proposing selling the real estate or renting land to the owner of the real estate. Also, the predetermined information may include the owner's name as the addressee, and information on the address of the real estate (lot number, address display) to identify which real estate the proposal is about.

[0087] In step S13, the method of transmitting the predetermined information is not particularly limited. For example, the predetermined information is transmitted from the server device 2 to the identified owner by e-mail or facsimile. The method of transmitting the predetermined information may be selected by the user operating the input unit 14 of the user terminal 1.

[0088] Also, instead of or in addition to the process of transmitting the specified information to the owner of the real estate in step S13, a process of transmitting transmission information for transmitting the specified information or delivery information for sending a mailing to another computer device to the owner identified in step S11, a process of controlling the delivery information to be printed on a medium, and / or a process of storing the delivery information in a storage medium may be executed. It is possible to appropriately design which of these processes is executed after the server device 2 executes step S11. It is also possible to allow the user to select which of these processes is executed by operating the input unit 14 of the user terminal 1.

[0089] The server device 2 executes a process of transmitting transmission information for transmitting predetermined information to the owner identified in step S11 to the other computer device, whereby the other computer device can transmit the predetermined information to the owner from the other computer device by e-mail or facsimile. The transmission information includes the owner's name, contact information such as e-mail address or facsimile number, and the address (land number and house number) of the identified real estate. Here, the other computer device may be operated by a business operator or the like other than the user.

[0090] Furthermore, the server device 2 executes a process of transmitting delivery information for sending an item to the owner identified in step S11 to another computer device operated by another business, etc., so that the other business, etc. can send the item to the owner by parcel delivery or mail. The delivery information includes the owner's name, address (residential address), contact information such as a telephone number, and the address (lot number, residential address) of the identified real estate. The content of the item can be changed as appropriate depending on a specified change, a specified attribute of the real estate, its purpose, etc. For example, if the specified attribute is an unused land or a vacant house, a message or proposal proposing the sale, rental, or utilization of the real estate can be sent to the owner of the real estate.

[0091] The server device 2 executes a process for controlling printing on a medium the delivery information (the owner's name and address) for sending an item to the owner identified in step S11, thereby making it possible to print a medium such as paper on which the owner's name and address are displayed. By printing the owner's name and address on a medium such as paper and attaching it to the item, it becomes possible to send the item to the owner. The medium used here can be a sticker-like medium with an adhesive applied to the reverse side of the printed surface and which can be used by peeling off the release paper. The contents of the item can be changed as appropriate depending on the specified change, the specified attributes of the real estate, its purpose, etc.

[0092] The server device 2 can also execute processes such as storing in an external storage medium (e.g., an optical disk, a flash memory, a hard disk) delivery information (the owner's name and contact information, and the address (lot number) of the identified real estate) for sending an item to the owner identified in step S11. By handing over the external storage medium storing the delivery information to a business operator or the like other than the user, it becomes possible for the business operator to send the item to the owner by parcel delivery or mail. The contents of the item can be changed as appropriate depending on the specified change, the specified attributes of the real estate, its purpose, etc.

[0093] Next, a second embodiment of the identification process in the system according to the embodiment of the present invention will be described. The identification process of the second embodiment differs from the identification process of the first embodiment in that the following steps S21 to S24 are executed instead of steps S4 to S6. The processes of steps S1 to S3 and S7 to S13 are similar, so their explanations will be omitted as necessary. Furthermore, the terms explained in the first embodiment can be adopted to the extent necessary from the contents described in the first embodiment.

[0094] In the second embodiment, the processes of steps S1 to S3 are executed. When the latitude and longitude of the first area are identified in step S3, the server device 2 acquires a third image and a fourth image (step S21). The fourth image is an image captured from above the ground, and is an image captured of at least a part of the first area. The fourth image may be an image captured so as to include the entire first area. The captured image is synonymous with the captured image described above, and therefore description thereof will be omitted.

[0095] The fourth image is a photographed image taken at a fourth time. If the first time when the first image was photographed is later than the second time when the second image was photographed, the third time when the third image was photographed may be a time after the first time, and the fourth time may be a time before the second time. Alternatively, the third time may be a time within a predetermined range (e.g., three days) from the first time, and the fourth time may be a time within a predetermined range from the second time. The predetermined range is not particularly limited and can be set as appropriate by the administrator or the user.

[0096] The captured image acquired in step S21 uses image data that can identify the date and time of capture and the latitude and longitude of each point or area in the captured image. Therefore, the server device 2 can identify the third image and the fourth image using the first time, the second time, and the latitude and longitude identified in step S3.

[0097] As described above, the third image and the fourth image may be high-resolution captured images. For example, the high-resolution captured images may have a resolution of 1 m or less. The third image and the fourth image may be optical images captured during the day. The third image and the fourth image may have the same resolution.

[0098] In step S21, when the server device 2 cooperates with an external system, the server device 2 transmits an acquisition request for the third image and the fourth image to another computer device. The acquisition request includes information on the shooting date and time of the captured image to be acquired and information on the area where the captured image was captured (for example, the latitude and longitude specified in step S3). The external system that cooperates with the server device 2 in step S4 and the external system that cooperates with the server device 2 in step S1 may be the same system or different systems.

[0099] Note that the acquisition of the third and fourth images in step S21 may be executed in response to an input made by the user operating the user terminal 1, similar to step S4.

[0100] When the third image and the fourth image are acquired in step S21, the server device 2 identifies a second area in which a change has occurred in the first area based on the third image and the fourth image (step S22). The process of identifying the second area in step S22 is executed in the same manner as the process of identifying the first area in step S2, and therefore a description thereof will be omitted.

[0101] When the second area is specified in step S22, the server device 2 determines whether or not a predetermined change has occurred in the specified second area (step S23). The predetermined change determined in step S23 may be input in step S1.

[0102] In step S23, the server device 2 may input the third image or the fourth image to the first prediction model, similarly to the process in step S5, to determine whether or not a predetermined change has occurred in the second region. For example, when image data corresponding to the third image or the fourth image is input to the first prediction model, and the region in which the predetermined change has occurred coincides with the second region identified in step S22, the server device 2 can determine that the predetermined change has occurred in the second region.

[0103] Alternatively, in step S23, the server device 2 may determine whether or not a predetermined change has occurred in the identified second region based on the third image and the fourth image. The method in which the server device 2 determines the second region in which a predetermined change has occurred based on the third image and the fourth image is not particularly limited. For example, the server device 2 can use the fourth prediction model to determine whether or not the second region determined in step S22 is the second region in which a predetermined change has occurred. The fourth prediction model is a prediction model that is machine-learned using image data (information such as RGB of each pixel constituting an image) in which changes (e.g., demolition, new construction, reconstruction, or repair) are clear for two or more captured images that are reference (sample) images of the same region captured at different times, as input data, and information regarding the position in the captured image and the change in the region corresponding to the position as output data.

[0104] When the server device 2 determines whether the change in the second area is demolition or not, the server device 2 uses a fourth prediction model whose input data are multiple image data of the area before demolition and the area after demolition photographed from the air.

[0105] When the server device 2 determines whether the change in the second area is a new construction, the server device 2 uses a fourth prediction model that uses as input data multiple image data of the area before construction begins and the area after completion, photographed from the air.

[0106] When the server device 2 determines whether the change in the second area is reconstruction or not, the server device 2 uses a fourth prediction model that uses multiple image data photographed from the sky of the area before reconstruction and the area after reconstruction as input data.

[0107] When the server device 2 determines whether the change in the second area is repair or not, the server device 2 uses a fourth prediction model that uses multiple image data of the area before repair and the area after repair photographed from the sky as input data.

[0108] The machine learning algorithm is not particularly limited, and a known algorithm can be used. The machine learning algorithm is the same as that described above, and therefore the description thereof will be omitted.

[0109] If a predetermined change has occurred in the identified second area (YES in step S23), the server device 2 determines whether the identified second area has a predetermined property attribute (step S24). The property attribute determined in step S24 may have been input in step S1.

[0110] In step S24, the server device 2 may input the third image or the fourth image to the second prediction model in the same manner as in the process of step S6, thereby determining whether the second region has a predetermined real estate attribute. For example, when image data corresponding to the third image or the fourth image is input to the second prediction model, and the region having the predetermined real estate attribute coincides with the second region in which it is determined in step S23 that the predetermined change has occurred, the server device 2 can determine that the second region has the predetermined real estate attribute.

[0111] If the identified second area has the specified real estate attribute (YES in step S24), the processing of steps S7 to S13 is executed for the identified second area. This ends the identification processing according to the second embodiment. On the other hand, if it is determined in step S23 that the specified change has not occurred in the second area (NO in step S23), or if it is determined in step S24 that the second area does not have the specified real estate attribute (NO in step S23), the identification processing according to the second embodiment ends.

[0112] Next, a third embodiment of the identification process in the system according to the embodiment of the present invention will be described. FIG. 6 is a diagram showing a flowchart of the real estate and owner identification process according to the third embodiment of the present invention. The identification process of the third embodiment is executed by the following steps S31 to S43. The identification process of the third embodiment differs from the identification process of the first embodiment in that the following steps S34 to S36 are executed instead of steps S4 to S6. The processes of steps S31 to S33 and S37 to S43 are similar to the processes of steps S1 to S3 and S7 to S13, so the explanation will be omitted as necessary. Furthermore, the terms explained in the first and second embodiments can be adopted to the extent necessary from the contents described in the first and second embodiments.

[0113] In the third embodiment, in steps S31 to S33, the same processes as those in steps S1 to S3 are executed. When the latitude and longitude of the first area are specified in step S33, the server device 2 acquires a third image (step S34). The acquisition of the third image may be executed in the same manner as the process in step S4.

[0114] When the third image is acquired in step S34, the server device 2 transmits the third image to the user terminal 1, and the user terminal 1 displays the third image on the display unit 15. The user visually checks the displayed third image. Then, the user operates the user terminal 1 to select an area on the displayed third image, thereby selecting a second area within the first area. As a result, the user terminal 1 accepts the selection of the second area (step S35).

[0115] The second area selected in step S35 can be selected arbitrarily by the user, and may be an area where a predetermined change has occurred, or an area having predetermined real estate attributes, or both. When the third image is displayed on the user terminal 1, map data may be superimposed on the third image. The map data may indicate the address, the parcel number, or the zoning of the area shown in the third image.

[0116] In the third image displayed in step S35, the outline of the first area specified in step S32 may be displayed, or the latitude and longitude position of the first area specified in step S33 may be displayed in a manner that allows the user to understand (for example, a sign). For example, a sign indicating the center position of the first area may be displayed in the third image. Also, in step S35, the server device 2 may change the display manner of each first area in the third image according to the degree of change in the first area. The degree of change in the first area corresponds to, for example, the above-mentioned amount of change in the pixel or the amount of change in the window. For example, changing the display manner may mean changing the hue, density, or transparency of the color displayed superimposed on the first area according to the amount of change in the window, or may cause the display of the outline of the first area to blink.

[0117] The user terminal 1 transmits information about the second area selected in step S35 to the server device 2. The server device 2 receives the information about the second area and thereby identifies the second area (step S36).

[0118] When the second region is specified in step S36, the processes of steps S37 to S43 are executed, and the specification process of the third embodiment is terminated. In steps S37 to S43, the processes of steps S7 to S13 described above are executed.

[0119] The process of step S34 may be omitted. In this case, the captured image displayed on the user terminal 1 when the selection of the second area is accepted in step S35 may be the first image and / or the second image used in step S31. The first image and / or the second image displayed in step S35 is a captured image of the first area identified in step S32. Alternatively, the user may actually go to a real-world area corresponding to the first area and confirm the second area. The user may operate the user terminal 1 and input information (e.g., an address) capable of identifying the second area in step S35.

[0120] The processes of steps S34 to S36 may be executed in response to an operation on the user terminal 1. The process of step S35 may be executed by the administrator terminal 3. For example, when the first area is specified by the processes of steps S1 to S3, one or more first areas are displayed on the user terminal 1. The user terminal 1 accepts the selection of the first area for specifying the second area and transmits an execution request of step S35. When the execution request is received by the server device 2, step S34 may be executed and a third image may be specified. Information on the specified third image, information on the first image, or information on the second image, and information on the specification of the second area are received by the administrator terminal 3. The administrator terminal 3 displays the first image, the second image, or the third image, and information on the specification of the second area. The information on the specification of the second area is, for example, information on a predetermined change for specifying the second area and / or information on a predetermined property attribute input by the user in step S1. Then, the administrator selects a second area within the first area by selecting an area on the displayed image by operating the administrator terminal 3. In this way, the administrator terminal 3 accepts the selection of the second area.

[0121] In the above, the manner in which the selection of the second area is accepted by operating the user terminal 1 or the administrator terminal 3 has been described, but the acceptance of the selection of the second area is not limited to this. For example, in step S35, the acceptance of the selection of the second area may be executed by the server device 2. In this case, the server device 2 can accept the selection of the second area by the process of step S5, S6, or S22.

[0122] [Other embodiments] The system 10 according to the present invention is not limited to the first, second, and third embodiments described above, and may be modified within the scope of the gist of the invention. In addition, the configuration of the system 10 described above and the following configurations may be combined in any manner.

[0123] The order of the first time and the second time may be reversed. For example, the first time may be a time before the second time. In this case, in the first embodiment, the third time may be a time after the second time, a time before the first time, or a time between the first time and the second time. In the second embodiment, the third time may be a time after the second time, and the fourth time may be a time before the first time.

[0124] The number of first areas identified in step S2 or S32 may be one or more. When multiple first areas are identified, multiple third images, or multiple third images and multiple fourth images, taken of the respective first areas are identified in step S4, S21, or S34. The number of second areas identified in step S5, S6, or S22, or the second area selected in step S35 and identified in step S36 may be one or more. When multiple second areas are identified, the processing in step S7 or S37 and thereafter is executed for each second area. Therefore, the number of owners of real estate and their contact information identified in the identification processing may be multiple.

[0125] The determination in step S23 of whether the second area is one in which a predetermined change has occurred and / or the determination in step S24 of whether the second area has a predetermined real estate attribute may be executed in response to an input by a user operating the user terminal 1. For example, the second area specified in step S22 is displayed on the user terminal 1. The user visually determines whether a predetermined change has occurred in the second area or whether the second area has a predetermined real estate attribute. Then, the determination result may be input in response to an input to the user terminal 1, thereby executing the processing of step S23 or S24. This processing may be executed by the administrator terminal 3.

[0126] It should be noted that step S5 is for identifying the second area in which a predetermined change has occurred from the third image, and step S23 is for judging whether or not a predetermined change has occurred in the second area, but in step S1, the user may operate the input unit 14 of the user terminal 1 to select the above-mentioned predetermined change from options such as demolition, new construction, reconstruction, repair, etc. The user selects one of these options depending on what kind of change the user wants to identify the owner of the real estate and his / her contact information.

[0127] In step S6, an area corresponding to real estate having a predetermined attribute is identified from the third image, and in step S24, whether the second area has the predetermined real estate attribute is determined. In step S1, the user may operate the input unit 14 of the user terminal 1 to select the predetermined attribute from options such as vacant house, unused land, parking lot, agricultural land, etc. The user may select one attribute from these options depending on what kind of property owner and contact information the user wants to identify. In addition to selecting the predetermined attribute, in step S1, the user may operate the input unit 14 of the user terminal 1 to select the time when the area to be searched has the predetermined real estate attribute from options such as before or after the change occurs. The server device 2 can identify the time when the third image acquired in step S4 was taken depending on the time of selection. In addition, the server device 2 can select the image to execute step S24 from the third image or the fourth image depending on the time of selection.

[0128] If a time having the predetermined real estate attribute is not selected, it is preferable that the third image is used in S24. In this case, it is preferable that the third image used in step S6 or S24 is an image taken after the first time or within a predetermined range from the first time. The third image used in step S6 or S24 may be the image taken most recently.

[0129] The process of step S3 or S33 may be omitted. In this case, instead of latitude and longitude, an address, a place name, a region, or the like may be specified as information capable of identifying the first region. In step S4, S21, or S34, the third image, or the third image and the fourth image are specified based on the information capable of identifying the first region.

[0130] The process of step S4 may be omitted. In this case, in steps S5 and S6, the first image and / or the second image used in step S1 may be used instead of the third image. The first image and / or the second image used in steps S5 and S6 are images of the first area identified in step S2. In other words, the system 10 can identify a second area in the first area that satisfies a predetermined condition based on the third image, the first image, or the second image that captures at least a part of the first area.

[0131] The process of step S21 may be omitted. In this case, in steps S22, S34, and S24, the first and second images used in step S1 can be used instead of the third and fourth images. The first and second images used in steps S22, S34, and S24 are images captured of the first area identified in step S2.

[0132] Note that the processing of steps S4 to S7, steps S21 to S24 and S7, or steps S34 to S37 may be omitted. In this case, in step S8 or S38, the latitude and longitude identified in step S3 or S33 are used to identify the address of the real estate corresponding to the first area. The address corresponding to the first area may be an address corresponding to at least a part of the area within the first area. Also, the address corresponding to the first area may be one or a plurality of addresses. Then, the server device 2 can identify the owner of the real estate corresponding to the address based on the correspondence between the address corresponding to the first area and the owner of the real estate corresponding to the address by executing the processing of steps S9 to 11 or S39 to S41 in the same manner as described above.

[0133] Furthermore, when a predetermined change occurs in the first area and / or when the first area has a predetermined property attribute, the server device 2 may specify the address of the real estate corresponding to the first area, and may specify the owner of the real estate corresponding to the specified address. In this embodiment, the system 10 omits steps S21 and S22 for the first area specified in steps S1 to S3, and executes steps S23 and / or S24. Then, the processes from step S7 onwards are executed.

[0134] In the above, the system 10 has been described as specifying the second area in the first area where a predetermined change has occurred and the second area in the first area that has a predetermined real estate attribute based on the third image or the third image and the fourth image, but the present invention is not limited to this. For example, the process of step S5 or step S23 may be omitted. Also, for example, the process of step S6 or step S24 may be omitted. In other words, the system 10 may specify the second area in the first area where a predetermined change has occurred or the second area in the first area that has a predetermined real estate attribute based on the third image or the third image and the fourth image.

[0135] In the second embodiment, the processes of steps S23 and S24 may be omitted. Also, the processes of step S35 and the following steps in the third embodiment may be performed using the first, second, third, or fourth image in which the second region is captured in step S22.

[0136] The process of step S10 or S40 may be executed after step S7 or S37. Furthermore, after executing the process up to step S7 or S37 and the process of step S10 or S40, the process of steps S8, S9, S11, and S13, or the process of steps S38, S39, S41, and S43 may be executed in response to an operation input to the user terminal 1, or for the second area selected by the user terminal 1. Alternatively, after executing the process up to step S8 or S38 and the process of step S10 or S40, the process of steps S9, S11, and S13, or the process of steps S39, S41, and S43 may be executed in response to an operation input to the user terminal 1, or for the second area selected by the user terminal 1.

[0137] The server device 2 can execute a process of extracting contours by a known method based on the third image acquired in step S4, and divide the third image into a plurality of regions separated by contours. Then, the server device 2 can use the first prediction model and / or the second prediction model to determine whether or not each of the plurality of regions corresponds to a real estate in which a predetermined change has occurred and / or a real estate having a predetermined attribute.

[0138] The process of step S4, S21, or S34 may be a process of acquiring a captured image having a different property from the captured images (first and second images) for identifying the first region. The captured image having a different property from the first and second images is, for example, an image having a different resolution from the first and second images, an image captured using a different wavelength, an image captured at a different time of day, etc. When the first and second images are visible light images, for example, an image captured using a different wavelength is a thermal infrared image or an SAR image. The system 10 can identify the first region where a change has occurred by the process of steps S1 to S4, steps S1 to S3 and S21, or steps S1 to S3 and S34, and further identify a captured image of the first region having a different property.

[0139] In the above-described embodiment, the user terminal 1 and / or the administrator terminal 3 are communicatively connected to the server device 2 and the specific process is executed. However, for example, the specific process may be executed in the user terminal 1. In this case, the process executed in the server device 2 in the above-described embodiment is executed in the control unit 11 of the user terminal 1. Information required for the process in the user terminal 1 may be pre-stored in the storage unit 13, or may be read out from an external storage device.

[0140] The user can operate the user terminal 1 to make a request to execute the process of step S8, S11, S13, S38, S41, or S43. The system 10 can also charge the user when executing the process of step S8, S11, S13, S38, S41, or S43. For example, after executing step S8 or S38, the system 10 may control the user terminal 1 to display the address of the real estate corresponding to the identified second area, the identified change, the attributes of the identified real estate, and / or map information showing the second area. When the user selects a request button for executing the process of step S11 or S41 displayed on the display screen of the user terminal 1, the process of steps S9 to S11 or S39 to S41 is executed, and the user may be charged.

[0141] In this way, a system including at least one computer device includes a first area specifying means for specifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a part of the area in the first image, a selection receiving means for receiving a selection of a second area in the first area based on a third image capturing at least a part of the first area, the first image, or the second image, and an address specifying means for specifying an address corresponding to the second area, and the first image, the second image, and / or the third image are images captured from above the ground, so that an address corresponding to the second area in the first area in which a change has occurred can be specified. Also, an address corresponding to an area in which a change has occurred can be found quickly.

[0142] In this way, a system including at least one computer device includes a first area specifying means for specifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a part of the area in the first image, and a second area specifying means for specifying a second area in the first area that satisfies a predetermined condition based on a third image capturing at least a part of the first area, and the first image, the second image, and the third image are images captured from above the ground, so that the second area in the first area that satisfies the predetermined condition can be specified. Also, the area in which a change has occurred can be found quickly.

[0143] In addition, since the first image and the second image are images with a lower resolution than the third image, the burden of identifying a second region that satisfies a predetermined condition in the first region is reduced. For example, the processing speed can be improved and the processing cost can be reduced. Furthermore, since the third image is an optical image taken during the day and the first image and the second image are optical images, infrared images, or SAR images taken at night, when identifying a second region that satisfies a predetermined condition from the first region, images with different properties are used, so that the second region can be identified from different perspectives. For example, after identifying an area where the population has increased, an area that is growing or developing, etc., based on changes in a nighttime light image or an infrared image, specific changes can be identified by an optical image taken during the day. Furthermore, after identifying an area where a change has occurred in the topography based on changes in an SAR image, specific changes can be identified by an optical image taken during the day. Furthermore, by using images with different properties, the second region where a change has occurred can be detected without omission.

[0144] Furthermore, since the first time belongs to a different day than the second time and is a later time than the second time, and the first image and the second image are images taken at a specified time period, the first area can be identified based on the first image and the second image, excluding changes that depend on the time period.

[0145] Furthermore, in this way, the second area identification means identifies the second area in the first area where a predetermined change has occurred and / or the second area having a predetermined real estate attribute based on the third image, thereby making it possible to identify the second area in the first area where a predetermined change has occurred and / or the second area having a predetermined real estate attribute. Furthermore, in this way, the second area identification means uses image data relating to a photographed image taken from above the ground as input data, and uses a machine-learned prediction model with information on a position in the photographed image and a change in the area corresponding to the position or information on a real estate attribute to identify the second area in the first area where a predetermined change has occurred. Furthermore, in this manner, the second area identification means uses image data relating to an image taken from above the ground as input data, and information relating to a position within the captured image and changes in the area corresponding to the position or real estate attributes as output data, to identify a second area having specified real estate attributes using a machine-learned predictive model, thereby making it possible to identify a second area having specified real estate attributes within the first area using the machine-learned predictive model.

[0146] In this way, the second region identification means identifies the second region in which a change has occurred in the first region based on the third image taken at the third time and the fourth image taken at the fourth time and capturing at least a part of the first region, thereby enabling the second region in which a change has occurred in the first region to be identified with high accuracy. In addition, for the purpose of identifying the second region with high accuracy, it is preferable that the first image and the second image are images with lower resolution than the third image and the fourth image, or that the third image and the fourth image are optical images taken during the day, and the first image and the second image are optical images, infrared images, or SAR images taken at night. Similarly, for the purpose of identifying the second region with high accuracy, it is preferable that the first time belongs to a day different from the second time and is later than the second time, the third time is a time after the first time, and the fourth time is a time before the second time.

[0147] Furthermore, in this way, the system is provided with an address identification means for identifying an address corresponding to the second area, so that the address corresponding to the second area can be identified. Furthermore, in this way, the address identification means identifies the latitude and longitude corresponding to at least one position in the second area, and identifies an address corresponding to the identified latitude and longitude, so that the address of a property corresponding to the latitude and longitude corresponding to at least one position in the second area can be identified. Furthermore, in this way, the system is provided with an owner identification means for identifying the owner of a property corresponding to an address identified by the address identification means based on a correspondence relationship between an address and an owner of a property corresponding to the address, so that the owner of a property corresponding to an address in the second area that satisfies a predetermined condition can be identified.

[0148] In this way, a system including at least one computer device includes a first area specifying means for specifying a first area in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a part of the area in the first image, an address specifying means for specifying an address corresponding to the first area, and an owner specifying means for specifying an owner of real estate corresponding to the address specified by the address specifying means based on a correspondence relationship between an address and an owner of real estate corresponding to the address, and the first image and the second image are images taken from above the ground, so that the owner of real estate at the address corresponding to the first area in which a change has occurred can be specified. Also, in this way, the owner specifying means specifies the owner of real estate corresponding to the address specified by the address specifying means when a predetermined change has occurred in the first area and / or when the first area has a predetermined real estate attribute, so that the owner of real estate at the address corresponding to the first area in which a predetermined change has occurred and / or the first area having a predetermined real estate attribute can be specified.

[0149] In this way, the owner identification means identifies the owner of the real estate corresponding to the address identified by the address identification means and the owner's contact information based on the correspondence between the address, the owner of the real estate corresponding to the address, and the owner's contact information, thereby making it possible to identify the owner of the real estate corresponding to the address and the owner's contact information. In this way, the address identified by the address identification means is a parcel number, and the owner identification means identifies the owner of the real estate corresponding to the identified parcel number based on the correspondence between the parcel number and the owner of the real estate corresponding to the parcel number, thereby making it possible to identify the owner of the real estate corresponding to the parcel number. [Explanation of symbols]

[0150] 1 User terminal 2 Server device 3 Administrator terminal 4 Communication Network 10 System 11 control section 12 RAM 13 storage section 14 Input section 15 Display section 16 Communication interface 21 control section 22 RAM 23 storage section 24 Communication Interface 31 Map data 32 Photographed image 33 Area

Claims

1. A system comprising at least one computing device, a first region specifying means for specifying a first region in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a partial region in the first image; a selection receiving means for receiving a selection of a second area within the first area by an operation of a user terminal operated by a user based on a third image obtained by capturing at least a part of the first area; an address specifying means for specifying an address corresponding to the second area; Equipped with the first image, the second image, and the third image are images captured from above the ground, A system, wherein the first image and the second image are captured images having a lower resolution than the third image.

2. The first time belongs to a different day than the second time and is a time later than the second time, The system of claim 1 , wherein the first image and the second image are images taken during a predetermined time period.

3. 3. The system according to claim 1, wherein the address identification means identifies a latitude and longitude corresponding to at least one location within the second region, and identifies an address corresponding to the identified latitude and longitude.

4. an owner identification means for identifying an owner of real estate corresponding to the address identified by the address identification means based on a correspondence relationship between the address and the owner of the real estate corresponding to the address; The system according to claim 1 or 2, comprising:

5. The system according to claim 4, wherein the owner identification means identifies the owner of the real estate corresponding to the address identified by the address identification means and the owner's contact information based on a correspondence between the address and the owner of the real estate corresponding to the address and the owner's contact information.

6. The address identified by the address identification means is a lot number, 5. The system according to claim 4, wherein the owner identification means identifies the owner of the real estate corresponding to the identified lot number based on a correspondence relationship between the lot number and the owner of the real estate corresponding to the lot number.

7. A computer device, a first region specifying means for specifying a first region in which a change has occurred based on a first image taken at a first time and a second image taken at a second time and capturing at least a partial region in the first image; a selection receiving means for receiving a selection of a second area of ​​the first area by an operation of a user terminal operated by a user based on a third image obtained by capturing at least a part of the first area; An address specifying means for specifying an address corresponding to the second area Function as a the first image, the second image, and the third image are images captured from above the ground, The program, wherein the first image and the second image are photographed images having a lower resolution than the third image.

8. 1. A method implemented in a system comprising at least one computing device, comprising: a first region specifying step of specifying a first region in which a change has occurred based on a first image captured at a first time and a second image captured at a second time and capturing at least a part of the region in the first image; a selection receiving step of receiving a selection of a second area of ​​the first area by an operation of a user terminal operated by a user based on a third image capturing at least a part of the first area; an address specifying step of specifying an address corresponding to the second area; having the first image, the second image, and the third image are images captured from above the ground, The method, wherein the first image and the second image are captured at a lower resolution than the third image.

Images