Image analysis device, image analysis method, and program

Abstract

To provide an image analysis device, an image analysis method, and a program for swiftly providing information about a damage situation when a disaster occurs.SOLUTION: In an image analysis device 20, an acquisition unit 21 divides an image analysis target area into multiple areas to perform image analysis and acquires information about a damage situation in each of the divided areas, an evaluation unit 22 evaluates a damage in each of the multiple areas on the basis of the acquired information related to the damage situation in each of the multiple areas, and an output unit 23 outputs information based on the evaluated damage in each of the multiple areas.SELECTED DRAWING: Figure 7

Description

Technical Field

[0001] The present disclosure relates to an image analysis apparatus, an image analysis method, and a program, and particularly relates to an image analysis apparatus, an image analysis method, and a program for analyzing damage situations from images obtained by photographing the ground.

Background Art

[0002] In related technologies, an aircraft such as a drone is used to photograph the ground from above, and three-dimensional map data is generated from the obtained image data. The generated three-dimensional map data can be used for various applications such as disaster prevention, firefighting, and autonomous driving.

[0003] For example, Patent Document 1 describes a related technology in which image data obtained by imaging the ground from above is received, and the original three-dimensional map data is updated using the received image data.

[0004] Also, in the related technology described in Patent Document 1, when changes occur simultaneously in a plurality of areas on the ground, the imaging device is caused to photograph in order from the area with the highest priority, taking into account the magnitude of the influence of the structures existing on the ground on autonomous driving.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] The related technology described in Patent Document 1 assumes that the three-dimensional map data is updated during normal times. Therefore, the related technology described in Patent Document 1 cannot appropriately determine the priorities among multiple areas during a disaster. As a result, in the related technology, it may not be possible to quickly provide emergency information (e.g., the latest damage situation in the most important area) to the relevant parties (e.g., the fire department).

[0007] The present disclosure has been made in view of the above problems, and its object is to quickly provide information regarding the damage situation during a disaster.

Means for Solving the Problems

[0008] An image analysis apparatus according to an aspect of the present disclosure includes: specifying means for dividing a region to be subjected to image analysis into a plurality of areas and performing image analysis to specify a disaster-affected area among the plurality of areas; receiving means for receiving image data obtained by photographing the disaster-affected area after the disaster; creating means for creating map data corresponding to the disaster-affected area using the received image data; and updating means for updating a portion corresponding to the created map data in the original map data created before the disaster.

[0009] In an image analysis method according to an aspect of the present disclosure, a computer divides a region to be subjected to image analysis into a plurality of areas and performs image analysis to specify a disaster-affected area among the plurality of areas, receives image data obtained by photographing the disaster-affected area after the disaster, creates map data corresponding to the disaster-affected area using the received image data, and updates a portion corresponding to the created map data in the original map data created before the disaster.

[0010] A program according to one aspect of the present disclosure causes a computer to perform processing of dividing an area to be subjected to image analysis into a plurality of areas, performing image analysis, identifying a disaster-affected area among the plurality of areas, receiving image data obtained by photographing the disaster-affected area after a disaster, creating map data corresponding to the disaster-affected area using the received image data, and updating a portion corresponding to the created map data in original map data created before the disaster.

[0011] An image analysis apparatus according to one aspect of the present disclosure includes: acquisition means for dividing an area to be subjected to image analysis into a plurality of areas, performing image analysis, and acquiring information regarding the damage situation of each of the divided plurality of areas; evaluation means for evaluating the damage of each of the plurality of areas based on the information regarding the damage situation of each of the acquired plurality of areas; and output means for outputting information based on the damage of each of the evaluated plurality of areas.

[0012] In an image analysis method according to one aspect of the present disclosure, a computer divides an area to be subjected to image analysis into a plurality of areas, performs image analysis, acquires information regarding the damage situation of each of the divided plurality of areas, evaluates the damage of each of the plurality of areas based on the information regarding the damage situation of each of the acquired plurality of areas, and outputs information based on the damage of each of the evaluated plurality of areas.

[0013] A program according to one aspect of the present disclosure causes a computer to perform processing of dividing an area to be subjected to image analysis into a plurality of areas, performing image analysis, acquiring information regarding the damage situation of each of the divided plurality of areas, evaluating the damage of each of the plurality of areas based on the information regarding the damage situation of each of the acquired plurality of areas, and outputting information based on the damage of each of the evaluated plurality of areas.

Advantages of the Invention

[0014] According to one aspect of the present disclosure, information regarding the damage situation can be quickly provided during a disaster.

Brief Description of the Drawings

[0015]

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Embodiments for Carrying Out the Invention

[0016] With reference to the drawings, some embodiments of the present disclosure will be described below.

[0017] [Embodiment 1] Embodiment 1 will be described with reference to FIGS. 1 to 3.

[0018] (Drone control system 1) FIG. 1 is a diagram schematically showing an example of the drone control system 1 according to the first embodiment. As shown in FIG. 1, the drone control system 1 includes an image analysis device 10 (20, 30), a drone base 100, a drone A 200-1, and a drone B 200-2. In FIG. 1, "image analysis device 10 (20, 30)" represents "any one of the image analysis devices 10, 20, and 30 in Embodiments 2 to 4 described below".

[0019] The drone base 100 controls the drone A 200-1 and the drone B 200-2 by wireless communication. Specifically, the drone base 100 moves the drone A 200-1 and the drone B 200-2 to the area to be analyzed by image analysis (for example, the affected area), and causes the drone A 200-1 and the drone B 200-2 to photograph the area to be analyzed by image analysis from above. Then, the drone base 100 receives the image data photographed by the drone A 200-1 and the drone B 200-2 by wireless communication.

[0020] Drone A200-1 is used for wide-range photography. Drone B200-2 is used for high-quality photography of a narrow range. In one example, Drone A200-1 photographs the entire area that is the subject of image analysis. Drone B200-2 photographs one of a plurality of areas into which the area that is the subject of image analysis is divided. Instead of, or in addition to, Drone B200-2 photographing one of a plurality of areas, a visible camera, a 3D visible camera, an infrared camera, LiDAR, or GNSS (global navigation satellite system), etc. may sense one of a plurality of areas.

[0021] Note that the area that is the subject of image analysis is divided into a plurality of areas by the image analysis device 10 (20, 30). The position information of each area is transmitted to each of Drone A200-1 and Drone B200-2 via the drone base 100. Alternatively, instead of the image analysis device 10 (20, 30), the drone base 100 may generate the position information of a plurality of areas.

[0022] The image analysis device 10 divides the area that is the subject of image analysis into a plurality of areas for image analysis and identifies the disaster area among the plurality of areas. The image analysis device 10 transmits information indicating the disaster area (for example, the position information of the disaster area) to Drone B200-2 via the drone base 100. Details of the method for identifying the disaster area will be described in Embodiment 2 below.

[0023] The image analysis device 10 receives, from the drone base 100, the image data obtained by Drone B200-2 photographing the disaster area after the disaster. The image analysis device 10 creates map data corresponding to the disaster area using the received image data.

[0024] Then, the image analysis device 10 updates the part corresponding to the created map data in the original map data created before the disaster. Thereby, map data reflecting the damage situation of the disaster area is created. The image analysis device 10 creates a 3D map of the area to be analyzed by image analysis. In one example, in another example, the image analysis device 10 creates a diagram (FIG. 6) showing the distribution of the disaster areas in the area to be analyzed by image analysis.

[0025] The image analysis device 20 divides the area to be analyzed by image analysis into a plurality of areas and performs image analysis. The image analysis device 20 acquires information regarding the damage situation of each of the divided plurality of areas. The information regarding the damage situation is, for example, the area of the area, the importance of the facilities and equipment existing in the area, and the cause of the disaster. The information regarding the damage situation will also be described in Embodiment 3 described later.

[0026] The image analysis device 20 evaluates the damage of each of the plurality of areas based on the information regarding the damage situation of each of the acquired plurality of areas. Then, the image analysis device 20 outputs information based on the damage of each of the evaluated plurality of areas. The information based on the damage is, for example, an index (evaluation value) indicating the severity of the damage. The image analysis device 20 may evaluate the damage of the area in consideration of the damage situation of the area adjacent to the area in addition to the damage situation of the area (Embodiment 3).

[0027] In Embodiments 2 to 4 described later, the configurations and operations of the image analysis devices 10, 20, and 30 will be described in detail.

[0028] (Operation of the drone control system 1) FIG. 2 is a sequence diagram showing the operation flow of each part of the drone control system 1 according to the first embodiment.

[0029] As shown in FIG. 2, the drone A200-1 repeatedly captures a wide range (for example, the entire area to be analyzed by image analysis) (S11, S12). Each time the drone A captures an image, it transmits the generated image data to the drone base 100.

[0030] The drone base 100 transfers the image data received from the drone A200-1 to the image analysis device 10 (20, 30).

[0031] The image analysis device 10 divides the area to be analyzed into a plurality of areas for image analysis, and identifies the disaster-affected area among the plurality of areas. For example, the image analysis device 10 compares the first image data generated by the drone A200-1 before the disaster with the second image data generated by the drone A200-1 after the disaster.

[0032] Then, the image analysis device 10 identifies the disaster-affected area based on the difference between the first image data and the second image data. For example, when the difference between the pixel value corresponding to an arbitrary area in the first image data and the pixel value corresponding to the same area in the second image data is greater than the threshold value, the image analysis device 10 can identify that area as the disaster-affected area.

[0033] The image analysis device 10 transmits the information indicating the identified disaster-affected area to the drone base 100.

[0034] The drone base 100 receives the information indicating the disaster-affected area from the image analysis device 10. Thereafter, the drone base 100 instructs the drone B200-2 to photograph the disaster-affected area identified by the image analysis device 10.

[0035] As shown in FIG. 2, the drone B200-2 photographs the disaster-affected area in accordance with the instruction from the drone base 100 (S21).

[0036] The drone B200-2 transmits the image data obtained by photographing the disaster-affected area to the drone base 100. The drone base 100 transfers the image data received from the drone B200-2 to the image analysis device 10.

[0037] The image analysis device 10 receives the image data generated by the drone B200-2. The image analysis device 10 creates map data corresponding to the disaster area using the received image data. Further, the image analysis device 10 acquires original map data (not shown) created before the disaster.

[0038] Then, the image analysis device 10 updates the corresponding part in the original map data with the created map data.

[0039] The image analysis device 20 receives the image data generated by the drone A200-1. The image analysis device 20 acquires information regarding the damage status of each of a plurality of areas from the received image data.

[0040] For example, the image analysis device 20 identifies the types of facilities (e.g., houses, vacant lots, infrastructure facilities, railway stations) existing in each area by performing image analysis on the received image data. In another example, the image analysis device 20 identifies the causes of the disaster (e.g., fire, landslide, tsunami, house collapse). In this way, the image analysis device 20 can acquire information regarding the damage status of each area from the image data generated by the drone A200-1.

[0041] Then, the image analysis device 20 evaluates the damage of each of the plurality of areas based on the information regarding the damage status of each of the plurality of areas. The image analysis device 20 outputs the evaluation results (e.g., "urgent", "important", "non-urgent", "non-important") of the damage of the plurality of areas.

[0042] (Effects of this embodiment) According to the configuration of this embodiment, the image analysis device 10 divides the area to be analyzed by image into a plurality of areas, identifies the disaster area among the plurality of areas, receives the image data obtained by photographing the disaster area after the disaster, creates map data corresponding to the disaster area using the received image data, and updates the corresponding part in the original map data created before the disaster with the created map data.

[0043] As a result, map data reflecting the damage situation in the affected area is created and provided to the relevant parties. The image analysis device 10 can quickly provide information regarding the damage situation during a disaster.

[0044] Also, according to the configuration of the present embodiment, the image analysis device 20 divides the area to be analyzed for images into a plurality of areas, performs image analysis, obtains information regarding the damage situation of each of the divided plurality of areas, evaluates the damage of each of the plurality of areas based on the information regarding the damage situation of each of the obtained plurality of areas, and outputs information based on the damage of each of the evaluated plurality of areas.

[0045] As a result, information based on the damage of each of the plurality of areas (for example, the evaluation results of the damage of each of the plurality of areas) is provided to the relevant parties. The image analysis device 20 can quickly provide information regarding the damage situation during a disaster.

[0046] [Embodiment 2] Embodiment 2 will be described with reference to FIGS. 4 to 6. In the present Embodiment 2, the configuration and operation of the image analysis device 10 constituting the drone control system 1 (FIG. 1) according to the above Embodiment 1 will be described.

[0047] (Configuration of Image Analysis Device 10) With reference to FIG. 4, the configuration of the image analysis device 10 according to the present Embodiment 2 will be described. FIG. 4 is a block diagram showing the configuration of the image analysis device 10.

[0048] As shown in FIG. 4, the image analysis device 10 includes a specifying unit 11, a receiving unit 12, a creating unit 13, and an updating unit 14.

[0049] The specifying unit 11 divides the area to be analyzed for images into a plurality of areas, performs image analysis, and specifies the affected area among the plurality of areas. The specifying unit 11 is an example of specifying means.

[0050] For example, the specifying unit 11 divides the area to be analyzed in the image into areas of a certain size and the same shape.

[0051] Also, the specifying unit 11 receives the image data received from the drone A200-1 (Fig. 1) from the drone base 100. The specifying unit 11 specifies the disaster area based on the difference between the first image data and the second image data. For example, the specifying unit 11 compares the first image data generated by the drone A200-1 before the disaster with the second image data generated by the drone A200-1 after the disaster. When the difference between the pixel value corresponding to an arbitrary area in the first image data and the pixel value corresponding to the same area in the second image data is greater than the threshold value, the specifying unit 11 specifies that the area is the disaster area.

[0052] The specifying unit 11 transmits information indicating the disaster area (for example, the position information of the disaster area) to the drone B200-2 (Fig. 1) via the drone base 100 (Fig. 1).

[0053] The receiving unit 12 receives the image data obtained by photographing the disaster area after the disaster. The receiving unit 12 is an example of receiving means.

[0054] For example, the receiving unit 12 receives the image data generated by the drone B200-2 (Fig. 1) from the drone base 100.

[0055] The receiving unit 12 outputs the received image data to the creating unit 13.

[0056] The creating unit 13 creates map data corresponding to the disaster area using the received image data. The creating unit 13 is an example of creating means.

[0057] For example, the creation unit 13 receives, from the reception unit 12, the image data generated by the drone B200-2. Using existing image processing techniques, the creation unit 13 creates map data corresponding to the disaster area from the image data received by the reception unit 12. For example, the creation unit 13 creates map data corresponding to a narrow area (e.g., the disaster area among a plurality of areas) photographed by the drone B200-2.

[0058] The creation unit 13 outputs the created map data to the update unit 14.

[0059] The update unit 14 updates the corresponding part in the original map data created before the disaster with the created map data. The update unit 14 is an example of an update means.

[0060] For example, the update unit 14 receives, from the creation unit 13, map data corresponding to a narrow area photographed by the drone B200-2. Also, the update unit 14 acquires the original map data created before the disaster. Then, the update unit 14 updates the corresponding part in the original map data with the created map data.

[0061] The update unit 14 outputs or saves the updated map data. For example, the update unit 14 displays the updated map data on a display device (not shown). Thereby, after the disaster, compared with related techniques for photographing the area to be analyzed by image analysis, the image analysis apparatus 10 can quickly provide information regarding the damage situation to relevant persons and the like.

[0062] (Operation of the Image Analysis Apparatus 10) Referring to FIG. 5, the operation of the image analysis apparatus 10 according to the second embodiment will be described. FIG. 5 is a flowchart showing the operation of the image analysis apparatus 10.

[0063] As shown in FIG. 5, the specifying unit 11 divides the area to be analyzed by image analysis into a plurality of areas, performs image analysis, and specifies the disaster area among the plurality of areas (S101).

[0064] The specific unit 11 transmits information indicating the disaster area (for example, the location information of the disaster area) to the drone B200-2 (FIG. 1) via the drone base 100 (FIG. 1).

[0065] Next, the receiving unit 12 receives the image data obtained by the drone B200-2 photographing the disaster area after the disaster (S102).

[0066] The receiving unit 12 outputs the received image data to the creating unit 13.

[0067] The creating unit 13 creates map data corresponding to the disaster area using the received image data (S103).

[0068] The creating unit 13 outputs the created map data to the updating unit 14.

[0069] The updating unit 14 updates the part corresponding to the created map data in the original map data created before the disaster (S104).

[0070] The updating unit 14 outputs or stores the updated map data.

[0071] Thus, the operation of the image analysis device 10 according to the second embodiment ends.

[0072] (An example of map data) FIG. 6 is a diagram showing the distribution of disaster areas in the area to be analyzed for images. This is an example of the map data created by the image analysis device 10. In the example shown in FIG. 6, the map data is divided into a plurality of areas, and among them, disaster areas A, B, and C are shown. The map data shown in FIG. 6 is also an example of information regarding the damage situation.

[0073] (Effects of this embodiment) According to the configuration of this embodiment, the specific part 11 divides the area to be analyzed in the image into a plurality of areas for image analysis, and identifies the disaster area among the plurality of areas. The receiving part 12 receives the image data obtained by photographing the disaster area after the disaster. The creating part 13 creates map data corresponding to the disaster area using the received image data. The updating part 14 updates the corresponding part of the original map data created before the disaster with the created map data.

[0074] The image analysis device 10 provides the updated map data to relevant persons and the like. The updated map data reflects the change in the disaster area from before to after the disaster. Thereby, the image analysis device 10 can quickly provide information regarding the damage situation during a disaster.

[0075] 〔Embodiment 3〕 Embodiment 3 will be described with reference to FIGS. 7 to 10. In this Embodiment 3, the configuration and operation of the image analysis device 20 that constitutes the drone control system 1 (FIG. 1) according to Embodiment 1 will be described.

[0076] In this Embodiment 3, for the components common to Embodiment 2, the description in Embodiment 2 is cited and the description here is omitted.

[0077] (Configuration of Image Analysis Device 20) With reference to FIG. 7, the configuration of the image analysis device 20 according to this Embodiment 3 will be described. FIG. 7 is a block diagram showing the configuration of the image analysis device 20.

[0078] As shown in FIG. 7, the image analysis device 20 includes an acquisition part 21, an evaluation part 22, and an output part 23.

[0079] The acquisition part 21 divides the area to be analyzed in the image into a plurality of areas for image analysis, and acquires information regarding the damage situation of each of the divided plurality of areas. The acquisition part 21 is an example of acquisition means.

[0080] For example, the acquisition unit 21 receives the image data generated by the drone A200-1 after a disaster from the drone base 100. The acquisition unit 21 acquires information on the damage status of each of a plurality of areas from the received image data. In one example, the acquisition unit 21 identifies the types of facilities (e.g., houses, vacant lots, infrastructure facilities, railway stations) existing in each area by performing image analysis on the received image data. In another example, the acquisition unit 21 identifies the types of facilities (e.g., houses, vacant lots, infrastructure facilities, railway stations) existing in each area by referring to a map information site provided by an existing information service organization.

[0081] The acquisition unit 21 outputs the information on the damage status thus acquired to the evaluation unit 22.

[0082] The evaluation unit 22 evaluates the damage of each of the plurality of areas based on the information on the damage status of each of the plurality of acquired areas. The evaluation unit 22 is an example of an evaluation means.

[0083] For example, the evaluation unit 22 receives information on the damage status of each of the plurality of areas from the acquisition unit 21. The evaluation unit 22 evaluates the damage of each of the plurality of areas based on the information on the damage status of each of the plurality of acquired areas.

[0084] In one example, the evaluation unit 22 evaluates the damage status of each area according to the following expression.

[0085] (Damage status of the area) = (Area of the area) × (Importance of the base in the area) × (Importance of the disaster factor) An example of the parameters according to the importance of the base in the area and the importance of the disaster factor will be described later.

[0086] Note that the evaluation unit 22 may evaluate the damage of the area in consideration of the damage status of the area adjacent to the area in addition to the damage status of the area. For example, the evaluation unit 22 calculates the damage index of each area based on the following expression.

[0087] (Damage Index of Area) = (Weight Coefficient of Area) × (Damage Situation of Area) Here, the weight coefficient of an area is proportional to the number or area of the disaster - affected areas adjacent to that area.

[0088] Referring to FIG. 6, for areas A, B, and C, the weight coefficients of each area will be explained. Area A is adjacent to 8 disaster - affected areas. Therefore, the weight coefficient of area A is 8 + 1 = 9. Disaster - affected area B is adjacent to 2 disaster - affected areas. Therefore, the weight coefficient of area B is 2 + 1 = 3. Area C is adjacent to 4 disaster - affected areas. Therefore, the weight coefficient of area C is 4 + 1 = 5. Alternatively, the weight coefficient may be these numerical values multiplied by an arbitrary constant coefficient α1.

[0089] The evaluation unit 22 outputs the evaluation results of the damage of each of the plurality of areas to the output unit 23.

[0090] For example, the evaluation unit 22 outputs an index (evaluation value) indicating the severity of the damage as the evaluation result of the damage of the area. In one example, the evaluation value is expressed by the following expression.

[0091] (Evaluation Value) = (Damage Index of Area) + α2 (constant coefficient) × (Damage Situation of Adjacent Areas) / (Number of Adjacent Areas) The output unit 23 outputs information based on the damage of each of the evaluated plurality of areas. The output unit 23 is an example of an output means.

[0092] For example, the output unit 23 receives the evaluation results of the damage of each of the plurality of areas from the evaluation unit 22. The output unit 23 outputs information based on the damage of each of the plurality of areas based on the evaluation results of the damage of each of the plurality of areas.

[0093] In one example, the output unit 23 acquires the map data of the area to be the target of image analysis and displays the information based on the evaluation value calculated by the evaluation unit 22 on the acquired map data.

[0094] (Operation of Image Analysis Device 20) With reference to FIG. 8, the operation of the image analysis device 20 according to Embodiment 3 will be described. FIG. 8 is a flowchart showing the operation of the image analysis device 20.

[0095] As shown in FIG. 8, the acquisition unit 21 divides the area to be analyzed in the image into a plurality of areas for image analysis, and acquires information regarding the damage situation of each of the divided plurality of areas (S201).

[0096] The acquisition unit 21 outputs the information regarding the damage situation thus acquired to the evaluation unit 22.

[0097] The evaluation unit 22 evaluates the damage of each of the plurality of areas based on the information regarding the damage situation of each of the acquired plurality of areas (S202).

[0098] The evaluation unit 22 outputs the evaluation result of the damage of each of the plurality of areas to the output unit 23.

[0099] The output unit 23 outputs information based on the damage of each of the evaluated plurality of areas (S203).

[0100] Thus, the operation of the image analysis device 20 according to Embodiment 3 ends.

[0101] (An Example of Parameters According to the Importance of Bases) FIG. 9 is a table showing an example of parameters according to the importance of bases in the area, which are used to calculate the damage situation of a plurality of areas.

[0102] In the example shown in FIG. 9, when "infrastructure facilities" exist in the area, the parameter according to the importance of the base is "100" for that area. As shown in FIG. 9, the parameter according to the importance of the base may vary depending on the date and time. For example, the importance of the "event venue" may be high during the period when the event is being held and low during the period when the event is not being held.

[0103] (An example of parameters according to the cause of disaster) FIG. 10 is a table showing an example of parameters according to the importance of a disaster, which is used to calculate the damage situation of a plurality of areas.

[0104] In the example shown in FIG. 10, when the cause of the disaster is "fire", the parameter according to the importance of the disaster is "100". For disasters such as "heavy rain" or "heavy snow" shown in FIG. 10, the parameters according to the importance of the disaster may vary depending on the threat of the disaster (for example, precipitation amount).

[0105] (Effect of this embodiment) According to the configuration of this embodiment, the acquisition unit 21 divides the area to be analyzed by image into a plurality of areas for image analysis, and acquires information on the damage situation of each of the divided plurality of areas. The evaluation unit 22 evaluates the damage of each of the plurality of areas based on the information on the damage situation of each of the acquired plurality of areas. The output unit 23 outputs information based on the damage of each of the evaluated plurality of areas.

[0106] The image analysis apparatus 20 provides the evaluation results of the damage of each of the plurality of areas to the relevant persons and the like. The evaluation results of the damage of each of the plurality of areas reflect the information on the damage situation of each of the plurality of areas. Thereby, the image analysis apparatus 20 can quickly provide information on the damage situation during a disaster.

[0107] 〔Embodiment 4〕 Referring to FIGS. 11 to 12, Embodiment 4 will be described. In this Embodiment 4, the configuration and operation of the image analysis apparatus 30 constituting the drone control system 1 (FIG. 1) according to Embodiment 1 will be described.

[0108] In this Embodiment 4, for the components common to Embodiment 3, the description in Embodiment 3 is cited and the description here is omitted.

[0109] (Configuration of image analysis apparatus 30) Referring to FIG. 11, the configuration of the image analysis apparatus 30 according to Embodiment 4 will be described. FIG. 11 is a block diagram showing the configuration of the image analysis apparatus 30.

[0110] As shown in FIG. 11, the image analysis apparatus 30 includes an acquisition unit 21, an evaluation unit 22, and an output unit 23. The image analysis apparatus 30 further includes a determination unit 34.

[0111] Based on the evaluation value (in the above-described Embodiment 2) calculated by the evaluation unit 22, the determination unit 34 determines a disaster-affected area to be a shooting target among a plurality of areas. Then, the determination unit 34 causes the imaging device to image the determined disaster-affected area. The determination unit 34 is an example of a determination means.

[0112] For example, the determination unit 34 receives the evaluation result (e.g., evaluation value) of the damage of each of the plurality of areas from the evaluation unit 22. The determination unit 34 compares the evaluation values of the damage of each of the plurality of areas, and determines the area with the highest evaluation value as the disaster-affected area to be a shooting target. Alternatively, the determination unit 34 may determine the areas from the highest to the Nth in terms of the evaluation value as the disaster-affected areas to be shooting targets.

[0113] Thereafter, the determination unit 34 instructs the drone base 100 to cause the drone B200-2 (an example of an imaging device) to image the determined disaster-affected area.

[0114] (Operation of the image analysis apparatus 30) Referring to FIG. 12, the operation of the image analysis apparatus 30 according to Embodiment 4 will be described. FIG. 12 is a flowchart showing the operation of the image analysis apparatus 30.

[0115] As shown in FIG. 12, the acquisition unit 21 divides the area to be analyzed into a plurality of areas for image analysis, and acquires information on the damage situation of each of the divided plurality of areas (S301).

[0116] The acquisition unit 21 outputs the information on the damage situation thus acquired to the evaluation unit 22.

[0117] Based on the information regarding the damage situation of each of the acquired multiple areas, the evaluation unit 22 evaluates the damage of each of the multiple areas (S302).

[0118] The evaluation unit 22 outputs the evaluation results of the damage of each of the multiple areas to the output unit 23 and the determination unit 34.

[0119] The output unit 23 outputs information based on the damage of each of the evaluated multiple areas (S303).

[0120] Based on the evaluation value calculated by the evaluation unit 22 (the second embodiment), the determination unit 34 determines the damaged area to be photographed after the disaster among the multiple areas (S304). Then, the determination unit 34 causes a camera such as the drone B200-2 (FIG. 1) to photograph the determined damaged area.

[0121] Thus, the operation of the image analysis device 30 according to the fourth embodiment ends.

[0122] (Modification example) In one modification example, the image analysis device 30 receives image data obtained by the drone B200-2 (FIG. 1) photographing the damaged area after the disaster, like the image analysis device 10 according to the second embodiment.

[0123] The image analysis device 30 creates map data (FIG. 6) corresponding to the damaged area using the received image data, and updates the corresponding part in the original map data created before the disaster.

[0124] (Effect of this embodiment) According to the configuration of the present embodiment, the acquisition unit 21 divides the area to be analyzed in the image into a plurality of areas for image analysis, and acquires information on the damage status of each of the divided plurality of areas. The evaluation unit 22 evaluates the damage of each of the plurality of areas based on the information on the damage status of each of the acquired plurality of areas. The output unit 23 outputs information based on the damage of each of the evaluated plurality of areas.

[0125] The image analysis device 30 provides the evaluation results of the damage of each of the plurality of areas to the relevant persons and the like. The evaluation results of the damage of each of the plurality of areas reflect the information on the damage status of each of the plurality of areas. Thereby, the image analysis device 30 can quickly provide information on the damage status during a disaster.

[0126] Furthermore, according to the configuration of the present embodiment, the determination unit 34 determines the damaged area to be photographed after the disaster based on the evaluation value calculated by the evaluation unit 22. Then, the determination unit 34 causes the camera to photograph the determined damaged area. Thereby, the image analysis device 30 can provide the image data obtained by photographing the damaged area as information on the damage status.

[0127] (Hardware Configuration) Each component of the image analysis devices 10, 20, and 30 described in the above Embodiments 2 to 4 indicates a block of a functional unit. Some or all of these components are realized by, for example, an information processing device as shown in FIG. 13. FIG. 13 is a block diagram showing an example of the hardware configuration of the information processing device.

[0128] As shown in FIG. 13, the computer 110 includes a CPU (Central Processing Unit) 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader / writer 116, and a communication interface 117. These components are connected to each other via a bus 121 so as to be capable of data communication with each other. Note that the computer 110 may include a GPU (Graphics Processing Unit) or an FPGA (Field-Programmable Gate Array) in addition to or instead of the CPU 111.

[0129] The CPU 111 expands the programs (codes) in the present embodiment stored in the storage device 113 into the main memory 112 and executes them in a predetermined order, thereby performing various operations. The main memory 112 is typically a volatile storage device such as a DRAM (Dynamic Random Access Memory). Also, the programs in the present embodiment are provided in a state stored in a computer-readable recording medium 120. Note that the programs in the present embodiment may be distributed on the Internet connected via the communication interface 117.

[0130] Specific examples of the storage device 113 include a hard disk drive and a semiconductor storage device such as a flash memory. The input interface 114 mediates data transmission between the CPU 111 and an input device 118 such as a keyboard and a mouse. The display controller 115 is connected to a display device 119 and controls the display on the display device 119.

[0131] The data reader / writer 116 mediates data transmission between the CPU 111 and the recording medium 120, and reads programs from the recording medium 120 and writes the processing results in the computer 110 to the recording medium 120. The communication interface 117 mediates data transmission between the CPU 111 and other computers.

[0132] Further, specific examples of the recording medium 120 include general-purpose semiconductor memory devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), magnetic recording media such as Flexible Disk, or optical recording media such as CD-ROM (Compact Disk Read Only Memory).

[0133] (Appendix) Some or all of the above embodiments may be described as follows in the appendix, but are not limited thereto.

[0134] (Appendix 1) An acquisition means for dividing the area to be analyzed in the image into a plurality of areas, performing image analysis, and acquiring information on the damage status of each of the divided plurality of areas; An evaluation means for evaluating the damage of each of the plurality of areas based on the information on the damage status of each of the plurality of acquired areas; An output means for outputting information based on the damage of each of the plurality of evaluated areas; An image analysis apparatus comprising:

[0135] (Appendix 2) Displaying an evaluation value, which is an index indicating the severity of the damage of each of the plurality of areas, on the map data corresponding to the area to be analyzed in the image The image analysis apparatus according to Appendix 1, characterized in that

[0136] (Appendix 3) Based on an evaluation value, which is an index indicating the severity of the damage of each of the plurality of areas, determining a disaster-stricken area to be photographed after a disaster, Causing the determined disaster-stricken area to be photographed by a camera Further comprising a determination means The image analysis apparatus according to Appendix 1, characterized in that

[0137] (Appendix 4) Receiving image data obtained by photographing the disaster area after a disaster, using the received image data to create map data corresponding to the disaster area, updating a portion corresponding to the created map data in the original map data created before the disaster, the image analysis apparatus according to appended note 3, characterized in that.

[0138] (Appended note 5) the information regarding the damage situation represents the area and importance of each of the plurality of areas, as well as the cause of the disaster, the image analysis apparatus according to appended note 1, characterized in that.

[0139] (Appended note 6) a computer, dividing an area to be subjected to image analysis into a plurality of areas for image analysis, obtaining information regarding the damage situation of each of the divided plurality of areas, evaluating the damage of each of the plurality of areas based on the information regarding the damage situation of each of the plurality of areas obtained, outputting information based on the damage of each of the plurality of areas evaluated, an image analysis method.

[0140] (Appended note 7) displaying an evaluation value, which is an index indicating the severity of the damage of each of the plurality of areas, on map data corresponding to the area to be subjected to image analysis, the image analysis method according to appended note 6, characterized in that.

[0141] (Appended note 8) determining a disaster area to be photographed after a disaster based on an evaluation value, which is an index indicating the severity of the damage of each of the plurality of areas, causing the determined disaster area to be photographed by a camera, the image analysis method according to appended note 6, characterized in that.

[0142] (Appended note 9) Receiving image data obtained by photographing the disaster area after a disaster, using the received image data to create map data corresponding to the disaster area, updating a portion corresponding to the created map data in the original map data created before the disaster The image analysis method according to appended note 8, characterized in that.

[0143] (Appended note 10) The information regarding the damage situation represents the area and importance of each of the plurality of areas, as well as the cause of the disaster The image analysis method according to appended note 6, characterized in that.

[0144] (Appended note 11) A process of dividing the area to be analyzed by image into a plurality of areas, performing image analysis, and acquiring information regarding the damage situation of each of the divided plurality of areas; A process of evaluating the damage of each of the plurality of areas based on the information regarding the damage situation of each of the plurality of areas obtained; A process of outputting information based on the damage of each of the plurality of areas evaluated; A program for causing a computer to execute.

[0145] (Appended note 12) To the computer, displaying, on map data corresponding to the area to be analyzed by image, an evaluation value which is an index indicating the severity of the damage of each of the plurality of areas The program according to appended note 11, characterized in that the computer is caused to execute the process.

[0146] (Appended note 13) To the computer, determining a disaster area to be photographed after a disaster based on an evaluation value which is an index indicating the severity of the damage of each of the plurality of areas, causing the determined disaster area to be photographed by a camera The image analysis method according to Supplementary Note 11, characterized by causing the processing to be executed.

[0147] (Supplementary Note 14) Causing the computer to Receive image data obtained by photographing the disaster area after the disaster, Create map data corresponding to the disaster area using the received image data, Update the corresponding part in the original map data created before the disaster with the created map data The program according to Supplementary Note 13, characterized by causing the processing to be executed.

[0148] (Supplementary Note 15) The information regarding the damage situation represents the area and importance of each of the plurality of areas, as well as the cause of the disaster The program according to Supplementary Note 11, characterized by this.

[0149] (Supplementary Note 16) Specific means for dividing the area to be analyzed for images into a plurality of areas, performing image analysis, and identifying the disaster area among the plurality of areas, Receiving means for receiving image data obtained by photographing the disaster area after the disaster, Creating means for creating map data corresponding to the disaster area using the received image data, Updating means for updating the corresponding part in the original map data created before the disaster with the created map data, An image analysis apparatus comprising:

[0150] (Supplementary Note 17) The computer Divides the area to be analyzed for images into a plurality of areas, performs image analysis, identifies the disaster area among the plurality of areas, Receives image data obtained by photographing the disaster area after the disaster, Creates map data corresponding to the disaster area using the received image data, In the original map data created before the disaster, update the part corresponding to the created map data. Image analysis method.

[0151] (Appendix 18) Divide the area to be analyzed in the image into a plurality of areas for image analysis, and identify the disaster-affected area among the plurality of areas, and Receive the image data obtained by photographing the disaster-affected area after the disaster, and Create map data corresponding to the disaster-affected area using the received image data, and In the original map data created before the disaster, update the part corresponding to the created map data, and A program for causing a computer to execute.

[0152] The present disclosure has been described above with reference to several embodiments. However, the present disclosure is not limited to the above embodiments. Each embodiment can be combined with other embodiments as appropriate. Also, various changes that can be understood by those skilled in the art can be made to the configuration and details of the above embodiments within the scope of the present disclosure.

Industrial Applicability

[0153] The present disclosure can be used, for example, in fire fighting activities and in creating map data using drones.

Explanation of Signs

[0154] 1 Drone control system 10 Image analysis device 11 Identification unit 12 Reception unit 13 Creation unit 14 Update unit 20 Image analysis device 21 Acquisition unit 22 Evaluation unit 23 Output unit 30 Image analysis device 21 Acquisition unit 22 Evaluation Unit 23 Output Unit 34 Decision Unit

Claims

1. An acquisition means for dividing an area to be subjected to image analysis into a plurality of areas, performing image analysis, and acquiring information on the damage situation of each of the divided plurality of areas; An evaluation means for evaluating the damage of each of the plurality of areas based on the information on the damage situation of each of the plurality of acquired areas; An output means for outputting information based on the damage of each of the plurality of evaluated areas; An image analysis apparatus comprising the above.

2. The output means displays an evaluation value, which is an index indicating the severity of the damage of each of the plurality of areas, on map data corresponding to the area to be subjected to image analysis. The image analysis apparatus according to claim 1, characterized in that.

3. Based on an evaluation value, which is an index indicating the severity of the damage of each of the plurality of areas, a damaged area to be photographed after a disaster is determined, The determined damaged area is caused to be photographed by a camera. Further comprising a determination means. The image analysis apparatus according to claim 1, characterized in that.

4. Receiving image data obtained by photographing the damaged area after a disaster, Using the received image data to create map data corresponding to the damaged area, Updating a portion corresponding to the created map data in the original map data created before the disaster. The image analysis apparatus according to claim 3, characterized in that.

5. The information on the damage situation represents the area and importance of each of the plurality of areas, as well as the cause of the disaster. The image analysis apparatus according to claim 1, characterized in that.

6. A computer, Dividing an area to be subjected to image analysis into a plurality of areas, performing image analysis, and acquiring information on the damage situation of each of the divided plurality of areas, Evaluating the damage of each of the plurality of areas based on the information on the damage situation of each of the plurality of acquired areas, Outputting information based on the damage of each of the plurality of evaluated areas. An image analysis method.

7. A process of dividing an area to be subjected to image analysis into a plurality of areas, performing image analysis, and acquiring information on the damage situation of each of the divided plurality of areas, A process of evaluating the damage of each of the plurality of areas based on the information on the damage situation of each of the plurality of acquired areas, A process of outputting information based on the damage of each of the plurality of evaluated areas. A program for causing a computer to execute.

8. Specific means for dividing the area to be subjected to image analysis into a plurality of areas, performing image analysis, and identifying a disaster area among the plurality of areas; Receiving means for receiving image data obtained by photographing the disaster area after the disaster; Creating means for creating map data corresponding to the disaster area using the received image data; Updating means for updating a portion corresponding to the created map data in the original map data created before the disaster; An image analysis apparatus comprising the same.

9. The computer: Divides the area to be subjected to image analysis into a plurality of areas, performs image analysis, and identifies a disaster area among the plurality of areas; Receives image data obtained by photographing the disaster area after the disaster; Creates map data corresponding to the disaster area using the received image data; Updates a portion corresponding to the created map data in the original map data created before the disaster An image analysis method.

10. A process of dividing the area to be subjected to image analysis into a plurality of areas, performing image analysis, and identifying a disaster area among the plurality of areas; A process of receiving image data obtained by photographing the disaster area after the disaster; A process of creating map data corresponding to the disaster area using the received image data; A process of updating a portion corresponding to the created map data in the original map data created before the disaster; A program for causing a computer to execute.

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