SPATIAL EVALUATION SUPPORT DEVICE, SPATIAL EVALUATION SUPPORT SYSTEM, AND SPATIAL EVALUATION SUPPORT PROGRAM

Abstract

To provide a space evaluation support apparatus which allows a user to quantitatively determine the attractiveness of an existing infrastructure, a space evaluation support system, and a space evaluation support program.SOLUTION: A space evaluation support apparatus 10 includes: an acquisition unit 11A which acquires captured images obtained by imaging a space to be evaluated; an extraction unit 11B which extracts constituent components in the space from the captured images acquired by the acquisition unit 11A; and a derivation unit 11C which applies predetermined weights, for each type of the constituent components, to the constituent components extracted by the extraction unit 11B, and derives an evaluation value on at least one of safety and security for the space.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a space evaluation support device, a space evaluation support system, and a space evaluation support program. [Background technology]

[0002] Conventionally, the following technologies have been considered as technologies that can contribute to making users feel attracted to infrastructure and structures in cities, towns, tourist spots, etc.

[0003] Patent Document 1 discloses a town structure in which a main street area is provided that runs vertically and / or transversely through the town area, and energy plant facilities and lifeline infrastructure for supplying at least electricity and gas are provided above and / or underground of the main street area. In this town structure, an infrastructure network is constructed between the main street area and urban areas other than the main street area.

[0004] Patent Document 2 discloses a street structure in which a pedestrian waiting space is provided along the pedestrian-vehicle boundary that divides a roadway and a sidewalk that is 4m or more wide on at least one side of the roadway. In this street structure, the pedestrian waiting space is provided in a substantially rectangular area in plan view with the long side in the direction of the roadway, and the width that intersects with the direction of the roadway is set to 2m or more and half the width of the sidewalk. In this street structure, a walking floor made of a different material from the paved surface of the sidewalk is provided on the area, and benches, chairs, steps, and other seating areas are provided. In this street structure, the entire long side of the area on the roadway side and one or both short sides connected to the long side that are 1.5m or more on the roadway side are seamlessly surrounded by a vehicle protection body that rises to a height of 1m or more above the surface of the walking floor.

[0005] Furthermore, Patent Document 3 discloses an exterior structure of a house in which the main part of the site, where the building, garden, etc. are constructed, is separated from a corner part by a passageway, and the corner part is turned into an open space. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2019-75042 A [Patent Document 2] JP 2018-53661 A [Patent Document 3] JP 2002-106187 A Summary of the Invention [Problem to be solved by the invention]

[0007] However, the technologies disclosed in Patent Documents 1 to 3 were intended to contribute to the construction of attractive infrastructure in the future. For this reason, these technologies were not able to contribute to making existing infrastructure such as cities, townscapes, and tourist spots more attractive and attractive so that people would want to visit those infrastructure.

[0008] The present invention has been made in consideration of the above circumstances, and aims to provide a spatial evaluation support device, a spatial evaluation support system, and a spatial evaluation support program that enable users to quantitatively judge the attractiveness of existing infrastructure structures. [Means for solving the problem]

[0009] The space evaluation support device according to the present invention as set forth in claim 1 includes an acquisition unit that acquires an image of a space to be evaluated, an extraction unit that extracts components in the space from the image acquired by the acquisition unit, and a derivation unit that assigns a weighting to the components extracted by the extraction unit based on a predetermined weight for each type of the components, and derives an evaluation value for at least one of safety and security for the space, the components being classified according to each of the safety and security. the derivation unit derives the evaluation value regarding safety using an arithmetic expression in which an actual amount of the corresponding component in the space to be evaluated is divided by a maximum value of the component, and derives the evaluation value regarding security using an arithmetic expression in which a value obtained by dividing the actual amount of the corresponding component in the space to be evaluated by a maximum value of the component is subtracted from 1. It is something.

[0010] According to the space evaluation support device of the present invention as set forth in claim 1, a photographed image of a space to be evaluated is acquired, components of the space are extracted from the acquired photographed image, the extracted components are weighted according to the type of the components in advance, an evaluation value relating to at least one of safety and security for the space is derived, and the components are classified into components classified according to each of the safety and security. The evaluation value for safety is derived using an arithmetic formula in which the actual amount of the corresponding component in the space to be evaluated is divided by the maximum value of the component, and the evaluation value for peace of mind is derived using an arithmetic formula in which the actual amount of the corresponding component in the space to be evaluated is divided by the maximum value of the component, and the value obtained by dividing the actual amount of the corresponding component in the space to be evaluated is subtracted from 1. This allows users to quantitatively judge the attractiveness of existing infrastructure.

[0011] A spatial evaluation support device according to the present invention as set forth in claim 2 is the spatial evaluation support device as set forth in claim 1, further comprising a presentation unit that combines the evaluation value derived by the derivation unit with a map image and presents it.

[0012] According to the spatial evaluation support device of the present invention as described in claim 2, the derived evaluation value is synthesized and presented on a map image, thereby enabling users to more effectively quantitatively judge the attractiveness of existing infrastructure and structures.

[0013] A spatial evaluation support device according to the present invention as set forth in claim 3 is the spatial evaluation support device as set forth in claim 2, in which the map image is a social heat map image.

[0014] According to the spatial evaluation support device of the present invention as described in claim 3, by making the map image into a social heat map image, it is possible to more effectively allow users to quantitatively judge the attractiveness of existing infrastructure structures.

[0015] The spatial evaluation support device of the present invention as described in claim 4 is a spatial evaluation support device as described in any one of claims 1 to 3, wherein the extraction unit extracts the components using a segmentation model trained using the captured image acquired by the acquisition unit.

[0016] According to the spatial evaluation support device of the present invention as set forth in claim 4, the components are extracted using a segmentation model trained using the acquired photographic images, thereby making it possible to extract the components with higher accuracy.

[0017] The spatial evaluation support device of the present invention as described in claim 5 is a spatial evaluation support device as described in any one of claims 1 to 4, wherein the components include at least one of a sidewalk, a roadway, a pedestrian bridge, a flyer, graffiti, and a parked vehicle on the street.

[0018] According to the spatial evaluation support device of the present invention as set forth in claim 5, it is possible to derive an evaluation value according to the included components.

[0019] A spatial evaluation support device according to the present invention as set forth in claim 6 is the spatial evaluation support device as set forth in claim 5, in which the weighting is performed on at least one type of the components.

[0020] According to the spatial evaluation support device of the present invention as set forth in claim 6, by weighting at least one type of component, the weighted component can be reflected in the evaluation value to a degree corresponding to the weighting.

[0021] A spatial evaluation support device according to the present invention as set forth in claim 7 is the spatial evaluation support device as set forth in any one of claims 1 to 6, in which the captured image is an omnidirectional image.

[0022] According to the spatial evaluation support device of the present invention as set forth in claim 7, by making the captured image an omnidirectional image, it is possible to derive a more effective evaluation value that takes into account not only the situation in front but also the surroundings.

[0023] The spatial evaluation support system of the present invention as described in claim 8 includes a spatial evaluation support device as described in any one of claims 1 to 7, a terminal including a receiving unit that receives from the spatial evaluation support device an evaluation value derived by the derivation unit of the spatial evaluation support device, and a display control unit that controls information indicating the evaluation value received by the receiving unit to be displayed on a display unit.

[0024] According to the spatial evaluation support system of the present invention as described in claim 8, by displaying information showing the evaluation value derived by the spatial evaluation support device of the present invention, the user can quantitatively judge the attractiveness of existing infrastructure structures.

[0025] A space evaluation support program according to the present invention as set forth in claim 9 includes acquiring an image of a space to be evaluated, extracting components in the space from the acquired image, and A process of performing a weighting for each type of the extracted components to derive an evaluation value for at least one of safety and security for the space, the components being classified according to each of the safety and security. the evaluation value regarding safety is derived using an arithmetic expression in which an actual amount of the corresponding component in the space to be evaluated is divided by a maximum value of the component, and the evaluation value regarding peace of mind is derived using an arithmetic expression in which a value obtained by dividing an actual amount of the corresponding component in the space to be evaluated by a maximum value of the component is subtracted from 1. The processing is executed by a computer.

[0026] According to the space evaluation support program of the present invention as set forth in claim 9, a photographed image of a space to be evaluated is acquired, components of the space are extracted from the acquired photographed image, a weighting is applied to the extracted components according to a type of the component, an evaluation value relating to at least one of safety and security for the space is derived, and the components are classified into components classified according to each of the safety and security. The evaluation value for safety is derived using an arithmetic formula in which the actual amount of the corresponding component in the space to be evaluated is divided by the maximum value of the component, and the evaluation value for peace of mind is derived using an arithmetic formula in which the actual amount of the corresponding component in the space to be evaluated is divided by the maximum value of the component, and the value obtained by dividing the actual amount of the corresponding component in the space to be evaluated is subtracted from 1. This allows users to quantitatively judge the attractiveness of existing infrastructure. Effect of the Invention

[0027] As described above, according to the present invention, it is possible to allow users to quantitatively judge the attractiveness of existing infrastructure. [Brief description of the drawings]

[0028] [Figure 1] 1 is a block diagram showing an example of a hardware configuration of a space evaluation support system according to an embodiment. [Diagram 2] FIG. 1 is a diagram for explaining a segmentation model according to an embodiment, in which the left diagram shows an example of an image obtained by shooting, and the right diagram shows an example of a classification result of the image shown in the left diagram. [Diagram 3] 1 is a block diagram showing an example of a functional configuration of a space evaluation support system according to an embodiment. [Figure 4] FIG. 2 is a schematic diagram showing an example of a configuration of an image information database according to the embodiment. [Diagram 5] FIG. 4 is a schematic diagram showing an example of a configuration of a weighting information database according to the embodiment. [Figure 6] FIG. 2 is a schematic diagram showing an example of a configuration of an evaluation value information database according to the embodiment. [Figure 7] 11 is a flowchart illustrating an example of a space evaluation support process according to the embodiment. [Figure 8] 11 is a flowchart illustrating an example of an evaluation value presentation process according to the embodiment. [Figure 9] 11 is a flowchart illustrating an example of an evaluation value display process according to the embodiment. [Figure 10] FIG. 4 is a front view showing an example of a configuration of an initial screen according to the embodiment. [Figure 11] FIG. 13 is a front view showing an example of a configuration of an evaluation result screen according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0029] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In this embodiment, the present invention will be described as being applied to a space evaluation support system including a space evaluation support device configured by a server computer or the like, and a plurality of subject terminals, each of which is a terminal used individually by a subject.

[0030] First, the configuration of a spatial evaluation support system 90 according to this embodiment will be described with reference to Figs. 1 to 3. Fig. 1 is a block diagram showing an example of the hardware configuration of the spatial evaluation support system 90 according to this embodiment. Fig. 2 is a diagram for explaining a segmentation model according to this embodiment, in which the left diagram shows an example of an image obtained by shooting, and the right diagram shows an example of a classification result of the image shown in the left diagram. Furthermore, Fig. 3 is a block diagram showing an example of the functional configuration of the spatial evaluation support system 90 according to this embodiment.

[0031] As shown in Fig. 1, a space evaluation support system 90 according to this embodiment includes a space evaluation support device 10 and a plurality of subject terminals 30, each of which is capable of accessing a network 80. Examples of the space evaluation support device 10 include information processing devices such as a personal computer and a server computer. Examples of the subject terminals 30 include portable terminals such as a smartphone, a tablet terminal, and a PDA (Personal Digital Assistant, mobile information terminal).

[0032] The subject terminal 30 according to this embodiment is a terminal carried by each of a plurality of subjects who are to use the space evaluation support system 90. The subject terminal 30 includes a CPU (Central Processing Unit) 31, a memory 32 as a temporary storage area, a non-volatile storage unit 33, an input unit 34 such as a touch panel, a display unit 35 such as a liquid crystal display, and a medium reading and writing device (R / W) 36. The subject terminal 30 also includes a camera 38, a microphone 39, a GPS (Global Positioning Systems) 40, and a wireless communication unit 42. The CPU 31, the memory 32, the storage unit 33, the input unit 34, the display unit 35, the medium reading and writing device 36, the camera 38, the microphone 39, the GPS 40, and the wireless communication unit 42 are connected to each other via a bus B1. The medium reading and writing device 36 reads information written in the recording medium 37 and writes information to the recording medium 37.

[0033] The storage unit 33 is realized by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. An evaluation value display program 33A is stored in the storage unit 33 as a storage medium. The evaluation value display program 33A is stored in the storage unit 33 by setting a recording medium 37, on which the evaluation value display program 33A is written, in the medium reading and writing device 36, and the medium reading and writing device 36 reading the evaluation value display program 33A from the recording medium 37. The CPU 31 reads the evaluation value display program 33A from the storage unit 33, expands it in the memory 32, and sequentially executes the processes of the evaluation value display program 33A.

[0034] On the other hand, the space evaluation support device 10 is a device that collectively stores and manages various information handled by the space evaluation support system 90. The space evaluation support device 10 includes a CPU 11, a memory 12 as a temporary storage area, a non-volatile storage unit 13, an input unit 14 such as a keyboard and a mouse, a display unit 15 such as a liquid crystal display, a medium reading and writing device 16, and a communication interface (I / F) unit 18. The CPU 11, the memory 12, the storage unit 13, the input unit 14, the display unit 15, the medium reading and writing device 16, and the communication I / F unit 18 are connected to each other via a bus B2. The medium reading and writing device 16 reads information written in a recording medium 17 and writes information to the recording medium 17.

[0035] The storage unit 13 is realized by an HDD, an SSD, a flash memory, or the like. The storage unit 13 as a storage medium stores a space evaluation support program 13A and an evaluation value presentation program 13B. The space evaluation support program 13A is stored in the storage unit 13 by setting the recording medium 17 in which the space evaluation support program 13A is written to the medium reading and writing device 16, and the medium reading and writing device 16 reading the space evaluation support program 13A from the recording medium 17. The evaluation value presentation program 13B is stored in the storage unit 13 by setting the recording medium 17 in which the evaluation value presentation program 13B is written to the medium reading and writing device 16, and the medium reading and writing device 16 reading the evaluation value presentation program 13B from the recording medium 17. The CPU 11 reads the space evaluation support program 13A and the evaluation value presentation program 13B from the storage unit 13, expands them in the memory 12, and sequentially executes the processes that the space evaluation support program 13A and the evaluation value presentation program 13B each have.

[0036] The storage unit 13 also stores a segmentation model 13C. The segmentation model 13C according to this embodiment is a segmentation model in which image information showing a captured image of a space to be evaluated by the space evaluation support system 90 is used as input information, and a segmentation image in which regions of predetermined types of components from the captured image are classified by type is used as output information. In this embodiment, the types of the above-mentioned components are flyers (mainly used as advertising media) pasted on sidewalks, roadways, pedestrian bridges, walls, and utility poles, graffiti written on fences and building shutters, and cars parked on the street. However, the types are not limited to these, and in addition to these components, any one or a combination of moving bicycles, brightness of the space, garbage, visibility of the road, etc. may be applied as the types of the above-mentioned components.

[0037] In the spatial evaluation support system 90 according to this embodiment, a model using a semantic segmentation technique using deep learning technology is applied as the segmentation model 13C. FIG. 2 shows examples of images before and after classification by each element using image segmentation technology. The left diagram in FIG. 2 is an example of an image before classification (referred to as "original image" in FIG. 2), and the right diagram in FIG. 2 is an example of an image after classification for that image (referred to as "segmented image" in FIG. 2). In the example shown in FIG. 2, vegetation, sidewalks, roadways, buildings, and sky are applied as components, and each component is represented with a different density.

[0038] In addition, in this embodiment, training data is created using omnidirectional images collected by Google for Google Street View, and the segmentation model 13C is trained. However, this is not limited to this form, and an image obtained by photographing using the camera 38 by the subject terminal 30 may be applied as the omnidirectional image. Furthermore, the photographed image is not limited to the omnidirectional image, and an image obtained by photographing only the normal front may be applied.

[0039] The technology of semantic segmentation using deep learning technology is described in "ICUC10_Fang-Ying GONG_GSV-ViewFactorMaps_6-10 August 2018," "Quantifying street elements in dense urban environments for climate research using Google Street View," "Badrinarayanan, V., Kendall, A., & Cipolla, R. (2017). Segnet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE transactions on pattern analysis and machine intelligence, 39(12), 2481-2495." "Chen, LC, Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, AL (2017). Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE transactions on pattern analysis and machine intelligence, 40(4), 834-848, etc., and since this is a widely known technique, further explanation will be omitted here.

[0040] In this way, in the spatial evaluation support system 90 according to the present embodiment, a model using a semantic segmentation technique using deep learning technology is applied as the segmentation model 13C, but the present invention is not limited to this form. For example, a model using other image segmentation techniques such as instance-aware segmentation may be applied as the segmentation model 13C.

[0041] Furthermore, an image information database 13D, a weighting information database 13E, and an evaluation value information database 13F are stored in the storage unit 13. The image information database 13D, the weighting information database 13E, and the evaluation value information database 13F will be described in detail later.

[0042] Next, the functional configuration of the space evaluation support device 10 and the subject terminal 30 according to this embodiment will be described with reference to FIG.

[0043] 3, the spatial evaluation support device 10 includes an acquisition unit 11A, an extraction unit 11B, a derivation unit 11C, and a presentation unit 11D. The CPU 11 of the spatial evaluation support device 10 executes the spatial evaluation support program 13A and the evaluation value presentation program 13B, thereby functioning as the acquisition unit 11A, the extraction unit 11B, the derivation unit 11C, and the presentation unit 11D.

[0044] The acquisition unit 11A according to this embodiment acquires a captured image of a space to be evaluated (hereinafter, referred to as "evaluation target space"). In this embodiment, as the captured image, an omnidirectional image collected by Google for Google Street View is applied, similar to the captured image used when training the segmentation model 13C. However, this is not limited to this form, and as the omnidirectional image, an image obtained by shooting using the camera 38 of the subject terminal 30 may be applied, and instead of the omnidirectional image, a captured image obtained by shooting only the normal front may be applied, which is similar to the captured image applied in training the segmentation model 13C.

[0045] Moreover, the extraction unit 11B according to the present embodiment extracts components in the evaluation target space from the photographed image acquired by the acquisition unit 11A. Here, the extraction unit 11B according to the present embodiment extracts components in the evaluation target space using a segmentation model 13C trained using the photographed image acquired by the acquisition unit 11A. This allows the components to be extracted with higher accuracy than when a segmentation model trained using a photographed image other than the photographed image acquired by the acquisition unit 11A is used. However, this is not limited to this form, and the components may be extracted from the photographed image of the evaluation target space using a segmentation model trained using a photographed image other than the photographed image acquired by the acquisition unit 11A. Also, each component may be extracted from the photographed image of the evaluation target space using a conventionally known image recognition technology without using a segmentation model.

[0046] The derivation unit 11C according to the present embodiment assigns a weighting factor determined in advance for each type of component extracted by the extraction unit 11B, and derives an evaluation value for both safety and security for the evaluation target space. In this manner, the derivation unit 11C according to the present embodiment derives evaluation values ​​for both safety and security, but is not limited thereto, and the derivation unit 11C may derive an evaluation value for only either safety or security.

[0047] Moreover, the presenting unit 11D according to the present embodiment combines the evaluation value derived by the derivation unit 11C with a map image and presents it. The presenting unit 11D according to the present embodiment presents the evaluation value by transmitting information indicating the evaluation value to the requested subject terminal 30 and displaying it on the display unit 35 of the subject terminal 30, but is not limited to this. For example, the evaluation value may be presented by displaying it on the display unit 15 of the space evaluation support device 10. Furthermore, the presentation of the evaluation value by the presenting unit 11D is not limited to presentation by display on the display unit, and may be presentation by voice or presentation by printing by an image forming device (so-called printer).

[0048] In addition, in this embodiment, a social heat map image is applied as the map image. The social heat map image is an image showing a map in which areas with different densities or colors are displayed on a map image that is normally displayed in the corresponding area, emphasizing locations where there is a lot of information that matches the target's category. That is, in this embodiment, each target is asked to answer a number of questions in advance, and the answer results are analyzed and classified to determine the category of each target in advance. Then, the social heat map image according to this embodiment is displayed on the map image so that the density increases as the amount of information (in this embodiment, information posted on SNS (Social Networking Service)) that matches the target's category increases. However, this is not limited to a form of changing the density, and the color may be changed in order from high density to low density, such as red → yellow → green.

[0049] In this embodiment, the space evaluation support device 10 is connected to a server that provides the latest version of each social heat map image of the area (hereinafter referred to as the "target area") that the space evaluation support system 90 handles via a network 80 or the like. The space evaluation support device 10 acquires the latest version of the social heat map image from this server and sequentially updates the social heat map image stored in the image information database 13D (see also FIG. 4) described later. However, this is not limited to this form, and the space evaluation support device 10 itself may sequentially update the social heat map image corresponding to each target person.

[0050] Meanwhile, the subject terminal 30 according to this embodiment includes a receiving unit 31A and a display control unit 31B. The CPU 31 of the subject terminal 30 executes an evaluation value display program 33A to function as the receiving unit 31A and the display control unit 31B.

[0051] The receiving unit 31A according to this embodiment receives information indicating the evaluation value derived by the derivation unit 11C of the spatial evaluation support device 10 from the spatial evaluation support device 10. In addition, the display control unit 31B controls the display of the information indicating the evaluation value received by the receiving unit 31A on the display unit 35.

[0052] Next, the image information database 13D according to this embodiment will be described with reference to Fig. 4. Fig. 4 is a schematic diagram showing an example of the configuration of the image information database 13D according to this embodiment.

[0053] The image information database 13D according to the present embodiment is a database in which omnidirectional images and the like used for learning the segmentation model 13C and as captured images of the evaluation target space are registered. As shown in Fig. 4, the image information database 13D according to the present embodiment stores information on the target area name, the social heat map image, the omnidirectional image, the target district position, and the target district ID (Identification).

[0054] The target area name is information indicating the name of each of the target areas, and the social heat map image is information indicating the above-mentioned social heat map image for each subject in the target area indicated by the corresponding target area name. The omnidirectional image is information indicating the above-mentioned omnidirectional image taken within the corresponding target area, and the target district position is information indicating the location of the district where the corresponding omnidirectional image was taken (hereinafter referred to as the "target district").

[0055] In this embodiment, the target area is divided into areas surrounded by a rectangle of a predetermined size in a plan view, and each of the divided areas is applied as the target district. In this embodiment, the target district position is defined as a coordinate position in a two-dimensional coordinate system of a pair of diagonals of the rectangle indicating the corresponding target district. However, this is not limited to this form, and for example, other shapes such as a circle or an ellipse may be applied instead of the rectangle, and latitude and longitude may be applied instead of the coordinate position in the two-dimensional coordinate system.

[0056] Furthermore, the target district ID is information that is assigned in advance and is different for each target district in order to individually identify the corresponding target district.

[0057] Next, the weighting information database 13E according to this embodiment will be described with reference to Fig. 5. Fig. 5 is a schematic diagram showing an example of the configuration of the weighting information database 13E according to this embodiment.

[0058] The weighting information database 13E according to the present embodiment is a database in which information for specifying weighting for each component element, which is used when deriving the above-mentioned evaluation value, is registered. As shown in Fig. 5, the weighting information database 13E according to the present embodiment stores information on the type, the component element, the maximum value, and the weight value.

[0059] The type is information indicating each type of safety and security, the components are information indicating the above-mentioned components in the space to be evaluated, the maximum value is information indicating a maximum value expected for the corresponding component, and the weight value is information indicating the importance of the corresponding component.

[0060] In the space evaluation support system 90 according to this embodiment, the evaluation value of each component element (hereinafter, referred to as "element-specific evaluation value") is calculated individually by the following formulas (1) and (2). In formula (1), F m represents the element-specific evaluation value of the mth type of component related to safety, and fv m represents the actual quantity of the component in the evaluation target space, and fmax m represents the maximum value of the component. In addition, in formula (2), R n represents the element-specific evaluation value of the nth type of component related to security, and rv n represents the actual quantity of the component in the evaluation target space, and rmax n represents the maximum value of the component.

[0061] F m =fv m / fmax m (1)

[0062] R n =1-rv n / rmax n (2)

[0063] In the spatial evaluation support system 90 according to this embodiment, as described below, an evaluation value regarding safety (hereinafter referred to as "safety level") and an evaluation value regarding security (hereinafter referred to as "security level") are derived by calculating a weighted average of the evaluation values ​​for each element. For this reason, the weighting information database 13E according to this embodiment registers maximum values ​​and weights for each category of safety and security and for each type of component. Note that, although the example shown in FIG. 5 shows a case where the maximum weight value is "10", it goes without saying that this is not limited to this.

[0064] Next, the evaluation value information database 13F according to this embodiment will be described with reference to Fig. 6. Fig. 6 is a schematic diagram showing an example of the configuration of the evaluation value information database 13F according to this embodiment.

[0065] The evaluation value information database 13F according to this embodiment is a database in which evaluation values ​​obtained by executing the spatial evaluation support program 13A are registered. As shown in Fig. 6, the evaluation value information database 13F according to this embodiment stores information on the target area name, the target district ID, and the evaluation value.

[0066] The target area name and the target district ID are the same information as the target area name and the target district ID in the image information database 13D. The evaluation value is information indicating the evaluation value of the corresponding target district, and as shown in Fig. 6, three types of evaluation values, safety level, security level, and overall level, are applied in this embodiment.

[0067] In the space evaluation support system 90 according to the present embodiment, the safety level, security level, and overall level are derived by calculation using the following formulas (4) to (6). In formula (1), FD represents the safety level, F1 to F m represents the element-by-element evaluation value of each safety component, and FW1 to FW m represents the weight value of the corresponding component. In addition, in equation (2), RD represents the degree of security, and R1 to R n represents the evaluation value for each component related to peace of mind, and RW1 to RW n represents the weight value of the corresponding component. Furthermore, TD in equation (3) represents the degree of synthesis.

[0068] FD = (F1 × FW1 + F2 × FW2 + + F m ×FW m ) / (FW1+FW2+···+FW m ) (4)

[0069] RD = (R1 × RW1 + R2 × RW2 + + R n ×RW n ) / (RW1+RW2+···+RW n ) (5)

[0070] TD=(FD+RD) / 2 (6)

[0071] As shown in formulas (4) and (5), in the space evaluation support system 90 according to this embodiment, a weighted average value using element-specific evaluation values ​​corresponding to each component is applied as the safety degree FD and the security degree RD. However, this is not limited to this form, and for example, an arithmetic mean value of element-specific evaluation values ​​corresponding to each component may be applied as the safety degree FD and the security degree RD. Also, as shown in formula (5), in the space evaluation support system 90 according to this embodiment, an arithmetic mean value of the safety degree FD and the security degree RD is applied as the overall degree TD. However, this is not limited to this form, and for example, a weighted average value of the safety degree FD and the security degree RD may be applied as the overall degree TD.

[0072] Next, the operation of the space evaluation support system 90 according to this embodiment will be described with reference to Figs. 7 to 11. Fig. 7 is a flowchart showing an example of the space evaluation support process according to this embodiment. Fig. 8 is a flowchart showing an example of the evaluation value presentation process according to this embodiment. Fig. 9 is a flowchart showing an example of the evaluation value display process according to this embodiment. Fig. 10 is a front view showing an example of the configuration of an initial screen according to this embodiment. Furthermore, Fig. 11 is a front view showing an example of the configuration of an evaluation result screen according to this embodiment.

[0073] First, referring to FIG. 7, the operation of the spatial evaluation support device 10 according to this embodiment when executing the spatial evaluation support process will be described. When a user of the spatial evaluation support device 10 (for example, an administrator of the spatial evaluation support system 90) inputs an instruction to start the execution of the spatial evaluation support process via the input unit 14, the CPU 11 of the spatial evaluation support device 10 executes the spatial evaluation support program 13A, thereby executing the spatial evaluation support process shown in FIG. 7. Note that, in order to avoid confusion, a case will be described here in which the image information database 13D and the weighting information database 13E have already been constructed. Also, in order to avoid confusion, a case will be described here in which the segmentation model 13C has already been trained using some of the omnidirectional images registered in the image information database 13D. Furthermore, in order to avoid confusion, a case will be described here in which the omnidirectional image to be evaluated (hereinafter, referred to as the "evaluation target image") in the image information database 13D is specified in advance.

[0074] 7, the CPU 11 reads out one of the evaluation target images (hereinafter, referred to as a “processing target image”) from the image information database 13D together with the corresponding target district ID. In step 102, the CPU 11 reads out the trained segmentation model 13C from the storage unit 13.

[0075] In step 104, CPU 11 inputs the processing target image to segmentation model 13C. In response to the input of this processing target image, a corresponding segmentation image is output from segmentation model 13C, and therefore in step 106, CPU 11 acquires the segmentation image output from segmentation model 13C.

[0076] In step 108, the CPU 11 extracts each of the above-mentioned components from the acquired segmentation image, and uses the extracted components to derive the safety level FD, the security level RD, and the overall level TD according to the above-mentioned equations (1) to (5).

[0077] In step 110, the CPU 11 stores the derived safety level FD, security level RD, and overall level TD together with the target district ID read in the processing of step 100 in the evaluation value information database 13F.

[0078] In the next step 112, the CPU 11 judges whether or not the above processing has been completed for all images to be evaluated, and if the judgment is negative, the process returns to step 100, whereas if the judgment is positive, the present space evaluation support processing is terminated. When the processing of steps 100 to 112 is repeatedly executed, in step 100, an image to be evaluated that has not been processed up to that point is treated as an image to be processed.

[0079] By the above-mentioned spatial evaluation support process, an evaluation value information database 13F shown in FIG. 6 is constructed as an example.

[0080] Next, the operation of the space evaluation support device 10 according to this embodiment when performing the evaluation value presentation process will be described with reference to FIG.

[0081] In the spatial evaluation support system 90 according to this embodiment, when any subject wants to refer to the above-mentioned evaluation values ​​of various places in any target area, an evaluation value display process described later is executed using the subject's own terminal 30. In this evaluation value display process, the subject transmits reference request information including information indicating the target area for which the subject wants to refer to the evaluation value (hereinafter referred to as "designated target area information") to the spatial evaluation support device 10. When this reference request information is received, the CPU 11 of the spatial evaluation support device 10 executes the evaluation value presentation program 13B, thereby executing the evaluation value presentation process shown in FIG. 8. Note that, in order to avoid confusion, a case will be described here where the evaluation value information database 13F has already been constructed.

[0082] 8, the CPU 11 extracts the designated target area information from the received reference request information. In step 152, the CPU 11 reads out the target area IDs and evaluation values ​​(safety level FD, security level RD, and overall level TD) of all target areas included in the target area (hereinafter referred to as the "processing target area") indicated by the designated target area information from the evaluation value information database 13F.

[0083] In step 154, the CPU 11 reads out from the image information database 13D a social heatmap image that corresponds to the target district position corresponding to the read target district ID and the processing target area, and also corresponds to the target person who is the access source.

[0084] In step 156, the CPU 11 uses the read social heat map image, the evaluation value of each target district, and the target district position information to create information showing an evaluation result screen with a predetermined configuration (hereinafter referred to as "evaluation result screen information"). In step 158, the CPU 11 transmits the created evaluation result screen information to the target user terminal 30 that is the access source, and then ends this evaluation value presentation process.

[0085] Next, the operation of the subject terminal 30 according to this embodiment when executing the above-mentioned evaluation value display process will be described with reference to Fig. 9. The evaluation value display process shown in Fig. 9 is executed by the CPU 31 of any of the subject terminals 30 executing the evaluation value display program 33A. The evaluation value display process shown in Fig. 9 is executed, for example, when an instruction to execute the evaluation value display process is input from any of the subjects (hereinafter referred to as "subject") via the input unit 34 of his / her subject terminal 30.

[0086] In step 200 of FIG. 9, the CPU 31 controls the display unit 35 to display an initial screen having a predetermined configuration, and in step 202, the CPU 31 waits until predetermined information is input.

[0087] As an example, as shown in FIG. 10, the initial screen according to this embodiment displays a message prompting input of the target area name, and also displays an input area 35A for inputting the target area name for which the evaluation value is to be referred to. When the initial screen shown in FIG. 10 is displayed on the display unit 35, the subject uses the input unit 34 to input the name of the target area for which the evaluation value is to be referred to in the input area 35A, and then selects the end button 35B. In response to this, step 202 is judged to be positive, and the process proceeds to step 204. Note that, in this embodiment, the input of the target area name on the initial screen is in the form of directly inputting the target area name, but this is not limited thereto. It is also possible to display all the target area names for which the evaluation value can be referred to in a pull-down format, and to select the desired target area name from the displayed target area names.

[0088] In step 204, the CPU 31 transmits the above-mentioned reference request information to the space evaluation support device 10. In response to this, the space evaluation support device 10 executes the evaluation value presentation process as described above, and transmits evaluation result screen information to the target user terminal 30 that is the access source.

[0089] Therefore, in step 206, the CPU 31 waits until evaluation result screen information is received from the space evaluation support device 10. In step 208, the CPU 31 controls the display unit 35 to display the evaluation result screen indicated by the received evaluation result screen information, and in step 210, the CPU 31 waits until predetermined information is input, and then ends this evaluation value display process.

[0090] As an example, as shown in Fig. 11, the evaluation result screen according to this embodiment displays three types of evaluation values, namely, the safety level FD, the security level RD, and the overall level TD, of the target area included in the processing target area at corresponding positions on the social heat map image of the processing target area. Note that the corresponding positions are positions indicated by the target area positions described above.

[0091] Therefore, by referring to the evaluation result screen, the subject can understand the evaluation values ​​of each area within the processing area along with the social heat map image.

[0092] As described above, according to this embodiment, the system includes an acquisition unit 11A that acquires a captured image of a space to be evaluated, an extraction unit 11B that extracts components in the space from the captured image acquired by the acquisition unit 11A, and a derivation unit 11C that assigns a predetermined weight to each type of the components extracted by the extraction unit 11B and derives an evaluation value related to at least one of safety and security for the space. Therefore, the user can quantitatively judge the attractiveness of the existing infrastructure.

[0093] Furthermore, according to this embodiment, the derived evaluation value is synthesized and displayed on a map image, so that the user can quantitatively determine the attractiveness of the existing infrastructure more effectively.

[0094] Furthermore, according to this embodiment, the map image is a social heat map image, which allows users to quantitatively judge the attractiveness of existing infrastructure more effectively.

[0095] Moreover, according to the present embodiment, the components are extracted using a segmentation model trained using the captured image acquired by the acquisition unit 11A. Therefore, the components can be extracted with higher accuracy.

[0096] Furthermore, according to this embodiment, the above components include sidewalks, roadways, pedestrian bridges, flyers, graffiti, parked vehicles, etc. Therefore, it is possible to derive an evaluation value according to the included components.

[0097] Furthermore, according to this embodiment, the weighting is applied to at least one type of component element, and therefore the weighted component element can be reflected in the evaluation value to a degree according to the weighting.

[0098] Furthermore, according to this embodiment, the captured image is an omnidirectional image, so that it is possible to derive a more effective evaluation value that takes into account not only the forward view but also the surrounding conditions.

[0099] In the above embodiment, the evaluation result screen is described as being displayed by superimposing only the evaluation values ​​of the target area in the processing target area on the social heat map image, but the present invention is not limited to this. For example, in addition to each evaluation value, an all-directional image that is the target of derivation of the evaluation value may be displayed near the evaluation value.

[0100] In the above embodiment, the subject himself / herself specifies the processing target area, but the present invention is not limited to this. For example, the GPS 40 built into the subject terminal 30 held by the subject may be used to automatically apply the area including the location of the subject terminal 30 as the processing target area. In addition, the spatial evaluation support device 10 may acquire information indicating the subject's taste tendencies in advance, and provide the subject with information on the target area according to the subject's taste at any time.

[0101] In the above embodiment, the case where three types of evaluation values, namely, the safety level FD, the security level RD, and the overall level TD, are applied as the evaluation value is described, but the present invention is not limited to this. For example, only one type or a combination of two types of these may be applied as the evaluation value.

[0102] In the above embodiment, the spatial evaluation support process is executed in the spatial evaluation support device 10, but the present invention is not limited to this. For example, the spatial evaluation support process may be executed by each subject terminal 30. In this case, the spatial evaluation support device 10 of the present invention is included in the subject terminal 30.

[0103] In the above embodiment, the social heat map image is an image showing a map that highlights places with a lot of information that matches the target person's category, but the present invention is not limited to this. For example, the social heat map image may be an image in which the redder the area is, the higher the safety level FD, the security level RD, and the overall level TD are.

[0104] In the above embodiment, the input of the processing target area is performed on the initial screen using the input unit 34, but the present invention is not limited to this. For example, the processing target area may be input as voice information using the microphone 39.

[0105] In addition, in the above embodiment, no specific mention was made of what happens after the subject refers to the evaluation result screen, but if the evaluation value displayed on the evaluation result screen is different from the subject's own subjective evaluation, the subject's own subjective evaluation can be reflected in the evaluation value information database 13F using the subject terminal 30.

[0106] In the above embodiment, the segmentation model is used to extract components from a captured image, but the present invention is not limited to this. For example, an object detection model other than the segmentation model may be applied to extract components from a captured image. The following methods can be used as examples of the model construction method in this case.

[0107] First, a category of objects that subjectively compromise safety and security, such as trash cans, is determined through experiments with subjects or workshops. Next, a large number of examples of the determined object category are collected through questionnaires, etc. Then, the object detection model is trained using the collected data as training data.

[0108] In addition, by using other conventionally known artificial intelligence instead of the object detection model, the safety and security levels may be derived directly from the captured image instead of extracting components from the captured image. In this case, the learning method of the artificial intelligence may be exemplified as follows.

[0109] First, subjects are asked to subjectively evaluate the safety and security levels using multiple existing photographic images taken in experiments, workshops, etc., using multiple levels of scores or ratings such as good, average, and bad. Then, the AI ​​is trained using these evaluation results and the corresponding photographic images as training data.

[0110] Furthermore, in the above embodiment, no particular reference is made to a method for determining the weighting values ​​in the weighting information database 13E. However, for example, the weighting values ​​may be determined from the results of a questionnaire survey of a plurality of people.

[0111] Furthermore, it goes without saying that the calculation formulas (1) to (5) are merely examples and can be modified as appropriate within the scope of the present invention.

[0112] In the above embodiment, for example, the hardware structure of the processing unit that executes each process of the acquisition unit 11A, extraction unit 11B, derivation unit 11C, and presentation unit 11D may be various processors as shown below. As described above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as a processing unit, as well as a programmable logic device (PLD), which is a processor whose circuit configuration can be changed after manufacture such as an FPGA (Field-Programmable Gate Array), a dedicated electric circuit, which is a processor having a circuit configuration designed specifically for executing specific processes such as an ASIC (Application Specific Integrated Circuit), etc.

[0113] The processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA).The processing unit may also be configured with a single processor.

[0114] As an example of configuring the processing unit with one processor, first, there is a form in which one processor is configured with a combination of one or more CPUs and software, as represented by computers such as client and server, and this processor functions as the processing unit. Second, there is a form in which a processor is used that realizes the functions of the entire system including the processing unit with one IC (Integrated Circuit) chip, as represented by System On Chip (SoC), etc. In this way, the processing unit is configured using one or more of the above various processors as a hardware structure.

[0115] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. [Explanation of symbols]

[0116] 10. Spatial evaluation support device 11 CPU 11A Acquisition Department 11B Extraction part 11C Derivation part 11D Presentation section 12. Memory 13 Storage section 13A Spatial Evaluation Support Program 13B Evaluation value presentation program 13C Segmentation Model 13D image information database 13E Weighting Information Database 13F Evaluation value information database 14 Input section 15 Display section 16 Media Read / Write Device 17 Recording media 18 Communication I / F section 30 Target device 31 CPU 31A Receiver 31B Display control unit 32 Memory 33 Storage section 33A Evaluation value display program 34 Input section 35 Display section 36 Media Read / Write Device 37 Recording media 38 Camera 39. Mike 40 GPS 42 Wireless Communication Section 80 Network 90 Spatial evaluation support system

Claims

1. An acquisition unit that acquires a captured image of a space to be evaluated; an extraction unit that extracts components in the space from the captured image acquired by the acquisition unit; a derivation unit that performs a weighting process for each type of the component extracted by the extraction unit, and derives an evaluation value related to at least one of safety and security for the space; Equipped with The components are classified into components for each of the safety and the security, The derivation unit derives the evaluation value regarding safety using an arithmetic expression in which an actual amount of the corresponding component in the space to be evaluated is divided by a maximum value of the component, and derives the evaluation value regarding security using an arithmetic expression in which a value obtained by dividing the actual amount of the corresponding component in the space to be evaluated by a maximum value of the component is subtracted from 1. Spatial evaluation support device.

2. a presentation unit that combines the evaluation value derived by the derivation unit with a map image and presents the combined evaluation value; The spatial evaluation support device according to claim 1 , further comprising:

3. The map image is a social heatmap image. The space evaluation support device according to claim 2.

4. The extraction unit extracts the components using a segmentation model trained using the captured image acquired by the acquisition unit. The space evaluation support device according to any one of claims 1 to 3.

5. The components include at least one of a sidewalk, a roadway, a pedestrian bridge, a flyer, graffiti, and a parked vehicle; The space evaluation support device according to any one of claims 1 to 4.

6. The weighting is performed on at least one type of the components. The space evaluation support device according to claim 5.

7. The captured image is an omnidirectional image. The space evaluation support device according to any one of claims 1 to 6.

8. A space evaluation support device according to any one of claims 1 to 7, a terminal including a receiving unit that receives the evaluation value derived by the derivation unit of the spatial evaluation support device from the spatial evaluation support device, and a display control unit that controls a display unit to display information indicating the evaluation value received by the receiving unit; A spatial evaluation support system including:

9. Acquire an image of the space to be evaluated, Extracting components in the space from the acquired photographed image; A predetermined weight is applied to the extracted components for each type of the components, and an evaluation value regarding at least one of safety and security for the space is derived. Processing, The components are classified into components for each of the safety and the security, The evaluation value regarding safety is derived using an arithmetic expression in which an actual amount of the corresponding component in the space to be evaluated is divided by a maximum value of the component, and the evaluation value regarding peace of mind is derived using an arithmetic expression in which a value obtained by dividing an actual amount of the corresponding component in the space to be evaluated by a maximum value of the component is subtracted from 1. A spatial evaluation support program for executing processing on a computer.

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