JP7699428B2 - SPATIAL EVALUATION SUPPORT DEVICE, SPATIAL EVALUATION SUPPORT SYSTEM, AND SPATIAL EVALUATION SUPPORT PROGRAM - Google Patents

Description

The present invention relates to a spatial evaluation support device, a spatial evaluation support system, and a spatial evaluation support program.

Conventionally, the following technologies have been used to help users feel attracted to infrastructure and structures in cities, towns, tourist spots, etc.

Patent Document 1 discloses a town structure in which a main street area is provided that runs vertically and/or across a 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.

Patent Document 2 discloses a street structure in which a pedestrian waiting space is provided along the pedestrian-vehicle boundary that separates the roadway from the sidewalk, where a sidewalk 4m or more wide is provided 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 intersecting 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.

Furthermore, Patent Document 3 discloses an exterior structure for a house in which the main part of the site, where the building and garden are constructed, is separated from the corner part by a passageway, and the corner part is left as an open space.

JP 2019-75042 A JP 2018-53661 A JP 2002-106187 A

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 destinations more attractive and attractive so that people would want to visit those infrastructure structures.

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 and structures.

The spatial evaluation support device of the present invention described in claim 1 comprises an acquisition unit that acquires a photographed image of the space to be evaluated, an extraction unit that extracts store name information indicating the names of stores existing in the space from the photographed image acquired by the acquisition unit, an identification unit that identifies stores other than stores with multiple stores as highly original candidate stores from the stores indicated by the store name information extracted by the extraction unit, a derivation unit that derives evaluation information regarding the highly original candidate stores identified by the identification unit, and a presentation unit that synthesizes and presents the evaluation information derived by the derivation unit on a map image, wherein the evaluation information is an originality degree indicating the ratio of the number of stores that do not belong to the multiple store chain that exist in a district in the space to the total number of stores in the district , the space is an area that includes the location of a user terminal, which is a terminal owned by a target person to use the space, and is an area that is automatically applied, and the presentation unit synthesizes and presents the store names and the originality degree of the highly original candidate stores as text information at the corresponding positions on the map image .

According to the spatial evaluation support device of the present invention described in claim 1, a photographed image of the space to be evaluated is acquired, store name information indicating the names of stores existing in the space is extracted from the acquired photographed image, stores other than stores with multiple stores are identified as highly original candidate stores from among the stores indicated by the extracted store name information, and evaluation information regarding the identified highly original candidate stores is derived, and by referring to the evaluation information, the user can quantitatively judge the attractiveness of the existing infrastructure/structure.

According to the spatial evaluation support device of the present invention as described in claim 1 , the derived evaluation information is synthesized and presented on a map image, thereby enabling users to more effectively quantitatively judge the attractiveness of existing infrastructure and structures.

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 , in which the map image is a social heat map image.

According to the spatial evaluation support device of the present invention as described in claim 2 , 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 and structures.

The spatial evaluation support device of the present invention described in claim 3 is a spatial evaluation support device described in claim 1 or claim 2 , wherein the extraction unit extracts the store name information using a segmentation model trained using the photographed image acquired by the acquisition unit.

According to the spatial evaluation support device of the present invention described in claim 3 , the store name information can be extracted with higher accuracy by using a segmentation model trained using the acquired photographic images to extract the store name information.

A spatial evaluation support device according to the present invention as set forth in claim 4 is the spatial evaluation support device as set forth in any one of claims 1 to 3 , in which the captured image is an omnidirectional image.

According to the spatial evaluation support device of the present invention as set forth in claim 4 , by making the captured image an omnidirectional image, it is possible to extract store name information not only of the front but also of the surrounding area .

The spatial evaluation support system of the present invention as described in claim 5 includes a spatial evaluation support device as described in any one of claims 1 to 4 , a terminal equipped with a receiving unit that receives evaluation information derived by the derivation unit of the spatial evaluation support device from the spatial evaluation support device, and a display control unit that controls the display of the evaluation information received by the receiving unit on a display unit.

According to the spatial evaluation support system of the present invention as described in claim 5 , by displaying the evaluation information derived by the spatial evaluation support device of the present invention, it is possible for a user to quantitatively judge the attractiveness of existing infrastructure/structures by referring to the evaluation information.

The space evaluation support program of the present invention described in claim 6 is a process of acquiring a photographed image of a space to be evaluated, extracting store name information indicating the names of stores existing in the space from the acquired photographed image, identifying stores other than stores with multiple stores from among the stores indicated by the extracted store name information as highly original candidate stores, deriving evaluation information regarding the identified highly original candidate stores , and synthesizing and presenting the derived evaluation information on a map image, wherein the evaluation information is an originality degree indicating the ratio of the number of stores existing in a district in the space that do not belong to the stores with multiple stores to the total number of stores in the district , and the space is an area including the location of a user terminal, which is a terminal owned by a target person to use the space , and is an area that is automatically applied,
The computer executes a process of synthesizing the store names and the originality levels of the highly original candidate stores as text information at corresponding positions on the map image and presenting the synthesized information .

According to the spatial evaluation support program of the present invention described in claim 6 , an image of the space to be evaluated is obtained, store name information indicating the names of stores existing in the space is extracted from the obtained image, and from the stores indicated by the extracted store name information, stores other than stores with multiple stores are identified as highly original candidate stores. Evaluation information is derived regarding the identified highly original candidate stores, and by referring to the evaluation information, the user can quantitatively judge the attractiveness of the existing infrastructure structure.

As described above, the present invention allows users to quantitatively judge the attractiveness of existing infrastructure and structures.

1 is a block diagram showing an example of a hardware configuration of a space evaluation support system according to an embodiment. 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. 1 is a block diagram showing an example of a functional configuration of a space evaluation support system according to an embodiment. FIG. 2 is a schematic diagram showing an example of a configuration of an image information database according to the embodiment. FIG. 2 is a schematic diagram illustrating an example of a configuration of a store information database according to the embodiment. FIG. 2 is a schematic diagram illustrating an example of a configuration of an original store information database according to the embodiment. 11 is a flowchart illustrating an example of a space evaluation support process according to the embodiment. 13 is a flowchart illustrating an example of an evaluation result presentation process according to the embodiment. 13 is a flowchart illustrating an example of an evaluation result display process according to the embodiment. FIG. 4 is a front view showing an example of a configuration of an initial screen according to the embodiment. FIG. 13 is a front view showing an example of a configuration of an evaluation result screen according to the embodiment.

Hereinafter, an example of 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 spatial evaluation support system that includes a spatial evaluation support device configured with a server computer or the like, and multiple subject terminals that are terminals used individually by each subject.

First, the configuration of the spatial evaluation support system 90 according to this embodiment will be described with reference to Figures 1 to 3. Figure 1 is a block diagram showing an example of the hardware configuration of the spatial evaluation support system 90 according to this embodiment. Also, Figure 2 is a diagram used to explain the segmentation model according to this embodiment, with the left diagram showing an example of an image obtained by photography, and the right diagram showing an example of the classification results of the image shown in the left diagram. Furthermore, Figure 3 is a block diagram showing an example of the functional configuration of the spatial evaluation support system 90 according to this embodiment.

As shown in FIG. 1, the spatial evaluation support system 90 according to this embodiment includes a spatial evaluation support device 10 and multiple subject terminals 30, each of which can access a network 80. Examples of the spatial evaluation support device 10 include information processing devices such as personal computers and server computers. Examples of the subject terminals 30 include portable terminals such as smartphones, tablet terminals, and PDAs (Personal Digital Assistants, mobile information terminals).

The subject terminal 30 according to this embodiment is a terminal held 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 media read/write 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 media read/write 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 media read/write device 36 reads information written in the recording medium 37 and writes information to the recording medium 37.

The storage unit 33 is realized by a hard disk drive (HDD), a solid state drive (SSD), a flash memory, or the like. The storage unit 33, which serves as a storage medium, stores an evaluation result display program 33A. The evaluation result display program 33A is stored in the storage unit 33 when a recording medium 37 on which the evaluation result display program 33A is written is set in the medium reading and writing device 36, and the medium reading and writing device 36 reads the evaluation result display program 33A from the recording medium 37. The CPU 31 reads the evaluation result display program 33A from the storage unit 33, expands it in the memory 32, and sequentially executes the processes of the evaluation result display program 33A.

On the other hand, the spatial evaluation support device 10 is a device that comprehensively stores and manages various information handled by the spatial evaluation support system 90. The spatial evaluation support device 10 comprises 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 mouse, a display unit 15 such as a liquid crystal display, a media reading and writing device 16, and a communication interface (I/F) unit 18. The CPU 11, memory 12, storage unit 13, input unit 14, display unit 15, media reading and writing device 16, and communication interface (I/F) unit 18 are connected to each other via a bus B2. The media reading and writing device 16 reads information written in the recording medium 17 and writes information to the recording medium 17.

The storage unit 13 is realized by a HDD, SSD, flash memory, etc. The storage unit 13 as a storage medium stores the space evaluation support program 13A and the evaluation result 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 result presentation program 13B is stored in the storage unit 13 by setting the recording medium 17 in which the evaluation result presentation program 13B is written to the medium reading and writing device 16, and the medium reading and writing device 16 reading the evaluation result presentation program 13B from the recording medium 17. The CPU 11 reads the space evaluation support program 13A and the evaluation result 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 result presentation program 13B each have.

The memory 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 spatial 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. Note that in this embodiment, the types of components used are items on which a store name is written or displayed, such as signs, shop curtains, paper lanterns, building shutters, and electronic bulletin boards (hereinafter referred to as "items with store names"). The types of "signs" used here include all types, such as parapet signs, wall signs, protruding signs, outdoor signs, stand signs, and banner stands.

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 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 elements, and each element is represented with a different density.

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 using the training data. However, this is not limited to this form, and an image obtained by capturing an image using the camera 38 on the subject terminal 30 may be applied as the omnidirectional image. Furthermore, the captured image is not limited to an omnidirectional image, and an image obtained by capturing an image of only the front in general may be applied.

For details of semantic segmentation using deep learning technology, see "ICUC10_Fang-Ying GONG_GSV-ViewFactorMaps_6-10 August 2018," "Using Google Street View to quantify street elements in dense urban environments for climate research," "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, L. C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (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." and is a widely known technology, so further explanation will be omitted here.

In this way, 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, but this is not the only possible form. For example, a model using other image segmentation techniques such as instance-aware segmentation may be applied as the segmentation model 13C.

The storage unit 13 also stores an image information database 13D, a store information database 13E, and an original store information database 13F. The image information database 13D, the store information database 13E, and the original store information database 13F will be described in detail later.

Next, referring to FIG. 3, the functional configuration of the spatial evaluation support device 10 and the subject terminal 30 according to this embodiment will be described.

As shown in FIG. 3, the spatial evaluation support device 10 includes an acquisition unit 11A, an extraction unit 11B, a specification unit 11C, a derivation unit 11D, and a presentation unit 11E. The CPU 11 of the spatial evaluation support device 10 executes the spatial evaluation support program 13A and the evaluation result presentation program 13B, thereby functioning as the acquisition unit 11A, the extraction unit 11B, the specification unit 11C, the derivation unit 11D, and the presentation unit 11E.

The acquisition unit 11A according to this embodiment acquires a captured image of the space to be evaluated (hereinafter referred to as the "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 the omnidirectional image may be an image obtained by capturing an image using the camera 38 of the subject terminal 30, or instead of the omnidirectional image, an image obtained by capturing only the normal forward view may be applied, similar to the captured image applied in training the segmentation model 13C.

The extraction unit 11B according to this embodiment extracts store name information (the above-mentioned "store name attachment" in this embodiment) indicating the store name present in the evaluation target image from the photographed image acquired by the acquisition unit 11A. Here, the extraction unit 11B according to this embodiment extracts the store name information present in the evaluation target space using the segmentation model 13C trained using the photographed image acquired by the acquisition unit 11A. This allows the store name information to be extracted with higher accuracy than when a segmentation model trained using photographed images other than those acquired by the acquisition unit 11A is used. However, this is not limited to this form, and the store name information may be extracted from the photographed image of the evaluation target space using a segmentation model trained using photographed images other than those acquired by the acquisition unit 11A. Also, the store name information may be extracted from the photographed image of the evaluation target space using a conventionally known image recognition technology without using a segmentation model.

The identification unit 11C according to this embodiment identifies stores other than stores with multiple store chains as highly original candidate stores from among the stores indicated by the store name information extracted by the extraction unit 11B. The derivation unit 11D according to this embodiment then derives evaluation information regarding the highly original candidate stores identified by the identification unit 11C.

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

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 that highlights locations where there is a lot of information that matches the target's category by displaying areas with different densities or colors over the map image that is normally displayed for the corresponding area. That is, in this embodiment, each target is asked to answer multiple 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 over the map image so that the density increases in locations where there is a lot of information that matches the target's category (in this embodiment, information posted on SNS (Social Networking Service)). However, this is not limited to changing the density, and the color may be changed in order from high density to low density, such as red → yellow → green.

In this embodiment, the spatial evaluation support device 10 is connected via a network 80 or the like to a server that provides the latest social heat map images of the areas (hereinafter referred to as "target areas") that are the subject of the spatial evaluation support system 90. The spatial evaluation support device 10 then obtains the latest social heat map images from this server, and sequentially updates the social heat map images stored in the image information database 13D (see also FIG. 4) described below. However, this is not the only possible form, and the spatial evaluation support device 10 itself may sequentially update the social heat map images corresponding to each subject.

On the other hand, 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 the evaluation result display program 33A, thereby functioning as the receiving unit 31A and the display control unit 31B.

The receiving unit 31A according to this embodiment receives the above-mentioned evaluation information derived by the derivation unit 11D of the spatial evaluation support device 10 from the spatial evaluation support device 10. The display control unit 31B also controls the display of the evaluation information received by the receiving unit 31A on the display unit 35.

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.

The image information database 13D according to this 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 this embodiment stores information such as the target area name, social heat map image, omnidirectional image, target district position, and target district ID (Identification).

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 location is information indicating the location of the district where the corresponding omnidirectional image was taken (hereinafter referred to as the "target district").

In this embodiment, the target area is divided into areas surrounded by a rectangle of a predetermined size in a plan view, and each divided area is applied as the target district. In addition, in this embodiment, the target district position is defined as the coordinate position in a two-dimensional coordinate system of a pair of diagonal corners 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.

Furthermore, the above-mentioned target area ID is information that is assigned in advance and is different for each target area in order to individually identify the corresponding target area.

Next, the store 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 store information database 13E according to this embodiment.

The store information database 13E according to this embodiment stores information about the above-mentioned stores that are part of a multi-store chain, which is used when deriving the above-mentioned evaluation information. As shown in FIG. 5, the store information database 13E according to this embodiment stores information about the chain store name, store name, and address.

The chain store name is information indicating a collective name for a group of stores that are operated as a chain store within a predetermined area (in this embodiment, within Japan). The store name is information indicating the name of each store that belongs to the corresponding chain store, and the address is information indicating the location of the corresponding store.

Next, the original store 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 original store information database 13F according to this embodiment.

The original store information database 13F according to this embodiment registers evaluation information and the like obtained by executing the spatial evaluation support program 13A. As shown in FIG. 6, the original store information database 13F according to this embodiment stores information such as the target area name, target district ID, store name, store location, and originality.

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. Furthermore, the store name is information indicating the name of the highly original candidate store described above, and the store location is information indicating the location when the address of the corresponding highly original candidate store is transformed into the same two-dimensional coordinate system as the target district location described above. Furthermore, the originality is information indicating the level of originality of a store located in the corresponding target district, and is information equivalent to the evaluation information described above.

In the spatial evaluation support system 90 according to this embodiment, the originality is derived by calculating it according to the following formula (1). In formula (1), OD represents the originality, ON represents the number of stores that are not part of a chain and that exist in the corresponding target area, and TN represents the total number of stores that exist in the corresponding target area.

OD=100×(ON/TN) (1)

In other words, in the spatial evaluation support system 90 according to this embodiment, the originality OD is calculated by calculating the ratio (percentage) of the number of stores that are not part of a chain and are present in the target area to the total number of stores in the target area.

In this way, in the spatial evaluation support system 90 according to this embodiment, the originality OD for all types of stores that do not belong to a chain store in each target area is applied as the above evaluation information, but this is not limited to this form. For example, stores may be classified by type, such as restaurants, clothing stores, coffee shops, etc., and the originality OD for each type may be applied as the above evaluation information. In this form, the weighted average value of the originality OD for each type may also be applied as the overall evaluation information for the target area.

Next, the operation of the spatial 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 spatial evaluation support process according to this embodiment. Fig. 8 is a flowchart showing an example of the evaluation result presentation process according to this embodiment. Fig. 9 is a flowchart showing an example of the evaluation result display process according to this embodiment. Fig. 10 is a front view showing an example of the configuration of the initial screen according to this embodiment. Furthermore, Fig. 11 is a front view showing an example of the configuration of the evaluation result screen according to this embodiment.

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 store 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.

In step 100 of FIG. 7, the CPU 11 reads all information (hereinafter referred to as "store information") from the store information database 13E.

In step 102, the CPU 11 reads one of the images to be evaluated (hereinafter referred to as the "image to be processed") from the image information database 13D, together with the corresponding target area name and target district ID. In step 104, the CPU 11 reads the trained segmentation model 13C from the memory unit 13.

In step 106, the CPU 11 inputs the image to be processed into the segmentation model 13C. In response to the input of the image to be processed, a corresponding segmentation image is output from the segmentation model 13C, and in step 108, the CPU 11 acquires the segmentation image output from the segmentation model 13C.

In step 110, the CPU 11 extracts the above-mentioned store name information from the acquired segmentation image. In step 112, the CPU 11 determines whether the store name included in the extracted store name information (hereinafter referred to as the "extracted store name") is included in the store name in the read store information, thereby determining whether the store with the extracted store name belongs to a certain chain store. If the determination is positive, the process proceeds to step 116 described below, whereas if the determination is negative, the process proceeds to step 114. The store name included in the above-mentioned store name information can be obtained by conventional character recognition technology such as OCR (Optical Character Recognition) technology.

In step 114, the CPU 11 stores the extracted store name and store location in the original store information database 13F as information corresponding to the read target area name and target district ID. Here, the store location is information indicating a location when the address of the corresponding store is converted into the same two-dimensional coordinate system as the target district location described above, as described above. In this embodiment, the address of the corresponding store searched from another device via the network 80 is converted into a position in the two-dimensional coordinate system and applied as the store location. The store indicated by the extracted store name stored in the original store information database 13F by the processing of this step 114 is a store that does not belong to any chain store and is estimated to be highly original, and corresponds to the highly original candidate store described above.

In step 116, the CPU 11 determines whether the above processing has been completed for all images to be evaluated. If the determination is negative, the process returns to step 102, whereas if the determination is positive, the process proceeds to step 118. When the processing of steps 102 to 116 is repeatedly executed, in step 102, an image to be evaluated that has not been the subject of processing up until that point becomes the image to be processed.

In step 118, the CPU 11 sets the number of store names for each target district stored in the original store information database 13F as the number of stores ON described above, and identifies the total number of stores in the corresponding target district from the read store information, and sets this total number as the total number of stores TN described above. The CPU 11 then substitutes the number of stores ON and the total number of stores TN into equation (1) to derive the originality OD for each target district.

In step 120, the CPU 11 stores the derived originality degree OD for each target area in the original store information database 13F, and then ends this spatial evaluation support process.

The above spatial evaluation support process will result in the construction of an original store information database 13F, as shown in Figure 6 as an example.

Next, referring to FIG. 8, the operation of the spatial evaluation support device 10 according to this embodiment when executing the evaluation result presentation process will be described.

In the spatial evaluation support system 90 according to this embodiment, when a subject wishes to refer to the above-mentioned evaluation information for each location in a target area, the subject uses the subject's own terminal 30 to execute the evaluation result display process described below. In this evaluation result display process, the subject transmits reference request information including information indicating the target area for which the subject wishes to refer to evaluation information (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 result presentation program 13B, thereby executing the evaluation result presentation process shown in FIG. 8. Note that, in order to avoid confusion, a case will be described here where the original store information database 13F has already been constructed.

In step 150 of FIG. 8, the CPU 11 extracts the specified target area information from the received reference request information. In step 152, the CPU 11 reads out the target area IDs, store names, and evaluation information (originality OD) of all target areas included in the target area indicated by the specified target area information (hereinafter referred to as the "processing target area") from the original store information database 13F. Stores with the store names read out here are estimated to be highly original and are the highly original candidate stores mentioned above.

In step 154, the CPU 11 reads out from the image information database 13D the target area location corresponding to the read target area ID, the processing target area, and the social heat map image corresponding to the target person who is the access source.

In step 156, the CPU 11 uses the read social heat map image, the store names and evaluation information for each target area, and the information on the target area location 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 from which the access originated, and then ends this evaluation result presentation process.

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

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 the specified information is input.

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 in which the target area name for which evaluation information is to be referenced is input. When the initial screen shown in FIG. 10 is displayed by the display unit 35, the subject uses the input unit 34 to input the name of the target area for which evaluation information is to be referenced 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 target area name is input on the initial screen in a form in which the target area name is directly input, but this is not limited thereto, and it is also possible to display all target area names for which evaluation information can be referenced in a pull-down format, and to select the desired target area name from the displayed target area names.

In step 204, the CPU 31 transmits the above-mentioned reference request information to the spatial evaluation support device 10. In response to this, the spatial evaluation support device 10 executes the evaluation result presentation process as described above, and transmits the evaluation result screen information to the target user terminal 30 from which the access originates.

Therefore, in step 206, the CPU 31 waits until evaluation result screen information is received from the spatial 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 result display process.

As an example, as shown in FIG. 11, the evaluation result screen according to this embodiment displays the store name and originality OD of the highly original candidate store described above in the target district included in the processing target area at a corresponding position on the social heat map image of the processing target area. Note that the corresponding position is the position indicated by the target district position described above.

Therefore, by referring to the evaluation results screen, the target person can grasp the evaluation information for each area in the processing area, along with the social heat map image and the names of the highly original candidate stores.

As described above, this embodiment includes an acquisition unit 11A that acquires images of the space to be evaluated, an extraction unit 11B that extracts store name information indicating the names of stores existing in the space from the images acquired by the acquisition unit 11A, an identification unit 11C that identifies stores other than those with multiple stores as highly original candidate stores from the stores indicated by the store name information extracted by the extraction unit 11B, and a derivation unit 11D that derives evaluation information regarding the highly original candidate stores identified by the identification unit 11C. Therefore, it is possible for users to quantitatively judge the attractiveness of existing infrastructure and structures.

In addition, according to this embodiment, the derived evaluation information is synthesized and presented on a map image. This allows users to more effectively quantitatively judge the attractiveness of existing infrastructure and structures.

Furthermore, according to this embodiment, the map image is a social heat map image. Therefore, it is possible to more effectively allow users to quantitatively judge the attractiveness of existing infrastructure and structures.

In addition, according to this embodiment, the store name information is extracted using a segmentation model trained using the captured images acquired by the acquisition unit 11A. Therefore, the store name information can be extracted with higher accuracy.

Furthermore, according to this embodiment, the captured image is an omnidirectional image. Therefore, it is possible to extract store name information not only for the area ahead, but also for the surrounding area.

In the above embodiment, a case has been described in which the evaluation result screen displays only the evaluation information (originality OD) of the target area in the processing target area and the store names of the highly original candidate stores superimposed on the social heat map image, but this is not limited to this. For example, in addition to this information, a corresponding omnidirectional image may be displayed near this information.

In the above embodiment, the subject himself/herself specifies the processing target area, but this is not limiting. For example, a GPS 40 built into the subject terminal 30 held by the subject may be used to automatically apply an area including the location of the subject terminal 30 as the processing target area. In addition, information indicating the subject's preference trends may be acquired in advance by the spatial evaluation support device 10, and information on the target area according to the subject's preferences may be provided to the subject at any time.

In addition, in the above embodiment, the spatial evaluation support process is executed in the spatial evaluation support device 10, but this is not limited to the above. 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.

In the above embodiment, a case has been described in which an image showing a map that highlights locations with a lot of information that matches the target person's category is applied as the social heat map image, but the present invention is not limited to this. For example, an image in which the higher the originality OD of an area is, the deeper the red color, may be applied as the social heat map image.

In the above embodiment, a chain store is used as a store with multiple stores, but the present invention is not limited to this. For example, a franchise store may be used as a store with multiple stores.

In the above embodiment, the name of the highly original candidate store is displayed in association with the position indicated by the target district position of the corresponding target district, but this is not limited to the above. For example, the name of the highly original candidate store may be displayed in association with the position indicated by the corresponding store position stored in the original store information database 13F.

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

In addition, in the above embodiment, no particular mention is made of what happens after the subject refers to the evaluation result screen, but if the originality displayed on the evaluation result screen is different from the subject's own subjective opinion, the subject's own subjective originality may be reflected in the original store information database 13F using the subject's terminal 30.

In addition, in the above embodiment, a case has been described in which store name information is extracted from a captured image using a segmentation model, but this is not limited to this. For example, store name information from a captured image may be extracted by applying an object detection model other than a segmentation model.

It goes without saying that formula (1) is merely an example and can be modified as appropriate without departing from the spirit of the present invention.

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, identification unit 11C, derivation unit 11D, and presentation unit 11E can be the various processors 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 electrical circuit, which is a processor with a circuit configuration designed specifically to execute a specific process, such as an ASIC (Application Specific Integrated Circuit), etc.

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 (e.g., 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.

As an example of configuring the processing unit as a single processor, first, there is a form in which one processor is configured as a combination of one or more CPUs and software, as typified by computers such as clients and servers, and this processor functions as the processing unit. Secondly, there is a form in which a processor is used to realize the functions of the entire system, including the processing unit, in a single IC (Integrated Circuit) chip, as typified by systems on chips (SoCs). In this way, the processing unit is configured as a hardware structure using one or more of the various processors listed above.

More specifically, the hardware structure of these various processors can be an electrical circuit that combines circuit elements such as semiconductor elements.

10 space evaluation support device 11 CPU
Description of the Reference Numerals 11A Acquisition unit 11B Extraction unit 11C Identification unit 11D Derivation unit 11E Presentation unit 12 Memory 13 Storage unit 13A Space evaluation support program 13B Evaluation result presentation program 13C Segmentation model 13D Image information database 13E Store information database 13F Original store information database 14 Input unit 15 Display unit 16 Medium reading and writing device 17 Recording medium 18 Communication I/F unit 30 Target person terminal 31 CPU
31A Receiving unit 31B Display control unit 32 Memory 33 Storage unit 33A Evaluation result display program 34 Input unit 35 Display unit 36 Medium reading and writing device 37 Recording medium 38 Camera 39 Microphone 40 GPS
42 Wireless communication unit 80 Network 90 Space evaluation support system

Claims (6)

An acquisition unit that acquires a captured image of a space to be evaluated;
an extraction unit that extracts store name information indicating the names of stores existing in the space from the photographed image acquired by the acquisition unit;
a specifying unit that specifies a store other than a store with multiple stores as a candidate store for high originality from among the stores indicated by the store name information extracted by the extracting unit;
A derivation unit that derives evaluation information regarding the highly original candidate store identified by the identification unit;
a presentation unit that combines the evaluation information derived by the derivation unit with a map image and presents the combined evaluation information;
Equipped with
The evaluation information is an originality degree indicating a ratio of the number of stores that are not part of the multiple store chain and that are present in a district in the space to the total number of stores present in the district ,
The space is an area including a location where a user terminal, which is a terminal owned by a target person to be used , is located, and is an area to be automatically applied;
The presentation unit presents the store names and the originality degrees of the highly original candidate stores as text information at corresponding positions on the map image.
Spatial evaluation support device . The map image is a social heatmap image.
The space evaluation support device according to claim 1 . The extraction unit extracts the store name information using a segmentation model trained using the photographed image acquired by the acquisition unit.
3. The spatial evaluation support device according to claim 1 or 2 . The captured image is an omnidirectional image.
The space evaluation support device according to any one of claims 1 to 3 . A space evaluation support device according to any one of claims 1 to 4 ,
a terminal including a receiving unit that receives the evaluation information derived by the derivation unit of the space evaluation support device from the space evaluation support device, and a display control unit that controls the evaluation information received by the receiving unit to be displayed on a display unit;
A spatial evaluation support system including: Acquire an image of the space to be evaluated,
extracting store name information indicating the names of stores existing in the space from the acquired photographed image;
From the stores indicated by the extracted store name information, stores other than those with multiple stores are identified as highly original candidate stores;
Derive evaluation information regarding the identified highly original candidate stores,
The derived evaluation information is synthesized and presented on a map image.
Processing,
The evaluation information is an originality degree indicating a ratio of the number of stores that are not part of the multiple store chain and that are present in a district in the space to the total number of stores present in the district ,
The space is an area including a location where a user terminal, which is a terminal owned by a target person to be used , is located, and is an area to be automatically applied;
The store names and the originality levels of the candidate stores are displayed in a corresponding position on the map image as text information.
A spatial evaluation support program for executing processing on a computer.