Evaluation assistance device, evaluation assistance system, evaluation assistance method, and program

Abstract

An evaluation assistance device (1) according to the present disclosure comprises: a flow of people information acquisition unit (15) that acquires flow of people information indicating the flow of people in the surroundings of an advertising medium (3); a range acquisition unit (11) that acquires a visibility range, which is the range in which the advertising medium (3) can be seen and is defined as three-dimensional data; and a number of views calculation unit (12) that uses the visibility range and the flow of people information to calculate a number of views, which is the number of people who have viewed the advertising medium (3).

Description

Evaluation support device, evaluation support system, evaluation support method, and program

[0001] The present disclosure relates to an evaluation support device, an evaluation support system, an evaluation support method, and a program that support the evaluation of advertising media.

[0002] The value of an advertising medium is mainly evaluated by the number of views, which is the number of people who viewed an advertisement displayed on the advertising medium. Patent Document 1 discloses an advertising effectiveness evaluation support method in which a camera attached to the frame of the advertising medium captures an image of the area around the camera, and using the captured image, the number of passersby and the number of people whose faces are facing the advertising medium are counted, and an audience rating is calculated using the number of passersby and the number of people whose faces are facing the advertising medium.

[0003] Japanese Patent Application Laid-Open No. 2007-18218

[0004] The advertising effectiveness evaluation support method described in Patent Document 1 requires that the camera be installed so that the range in which a person can view an advertisement is within the camera's field of view. Since the advertising effectiveness evaluation support method described in Patent Document 1 calculates the audience rating, even if the range in which a person can view an advertisement and the camera's field of view do not exactly match, there is little impact on the accuracy of the audience rating calculation. However, when the method described in Patent Document 1 is applied to calculating the number of views, an error occurs in the calculated number of views if the range in which a person can view an advertisement and the camera's field of view do not exactly match. Therefore, there is a problem in that strict camera installation conditions are required to calculate the number of views using the method described in Patent Document 1.

[0005] The present disclosure has been made in view of the above, and aims to provide an evaluation support device that can calculate the number of views without requiring strict installation conditions for the camera.

[0006] In order to solve the above-mentioned problems and achieve the objectives, the evaluation support device disclosed herein includes a people flow information acquisition unit that acquires people flow information indicating the flow of people around the advertising medium, a range acquisition unit that acquires a viewable range that is the range within which the advertising medium is viewable and is defined as three-dimensional data, and a view count calculation unit that uses the viewable range and the people flow information to calculate a view count, which is the number of people who viewed the advertising medium.

[0007] The evaluation support device of the present disclosure has the effect of being able to calculate the number of views without requiring strict installation conditions for the camera.

[0008] FIG. 1 shows an example of the configuration of an evaluation support system according to the first embodiment. FIG. 2 shows an example of the visible range of the first embodiment. FIG. 3 explains the consideration of obstacles in the first embodiment. FIG. 4 shows an example of the evaluation support processing procedure in the evaluation support device according to the first embodiment. FIG. 4 explains a person facing an advertising medium. FIG. 5 explains a person facing an advertising medium taking obstacles into consideration. FIG. 5 shows an example of the configuration of a computer system that realizes the evaluation support device according to the first embodiment. FIG. 6 shows an example of the configuration of an evaluation support system according to the second embodiment. FIG. 7 shows an example of a questionnaire in the second embodiment. FIG. 8 explains the movement route in the passerby information in the second embodiment. FIG. 9 shows an example of the passerby information in the second embodiment. FIG. 10 shows an example of the configuration of an evaluation support system according to the fourth embodiment. FIG. 11 shows an example of a display screen in the fourth embodiment. FIG. 12 shows an example of a simulation image in the fourth embodiment. FIG. 13 shows an example of the configuration of an evaluation support system according to the fifth embodiment. FIG. 14 shows an example of a reception screen for accepting input of desired conditions in the fifth embodiment. FIG. 15 shows an example of medium information in the fifth embodiment. FIG. 16 shows an example of a display screen for proposed information in the fifth embodiment. FIG. 17 shows an example of a map showing the installation location of the proposed advertising medium in the fifth embodiment. FIG. 18 shows an example of a display screen for detailed information in the fifth embodiment.

[0009] An evaluation support device, an evaluation support system, an evaluation support method, and a program according to embodiments will be described in detail below with reference to the accompanying drawings.

[0010] Embodiment 1. Fig. 1 is a diagram showing an example of the configuration of an evaluation support system according to embodiment 1. The evaluation support system 100 of this embodiment includes an advertising medium 3 and an evaluation support device 1 that supports the evaluation of the advertising medium 3. Although Fig. 1 shows one advertising medium 3, it is sufficient that there are one or more advertising media 3, and there may also be multiple advertising media 3.

[0011] The advertising medium 3 is, for example, a display on which advertisements are displayed, but is not limited to this and may be a non-digital medium such as a signboard on which pictures and text are directly written. The advertising medium 3 is also, for example, installed outdoors, but is not limited to this and may be installed indoors. The advertising medium 3 may be installed on the wall of a building or the like, or may be installed independently, and there are no particular restrictions on the installation location. The following mainly describes an example in which the advertising medium is a display on which advertisements are displayed, but as mentioned above, the advertising medium 3 may also be a non-digital medium.

[0012] The evaluation support device 1 calculates the number of views, which is the number of people who viewed the advertising medium 3, using a viewable range, which is the range within which the advertising medium 3 is viewable and is defined as three-dimensional data, and people flow information, which indicates the flow of people around the advertising medium 3. This allows the evaluation support device 1 to present the number of views to service users, who are users of the evaluation support device 1. Service users include, for example, organizations such as advertisers considering placing advertisements on the advertising medium 3, advertisers that have placed advertisements on the advertising medium 3, advertising agencies, and providers of the advertising medium 3, as well as people belonging to these organizations and people commissioned by these organizations, but are not limited to these.

[0013] In this embodiment, sensor information, which is information acquired by a sensor 2, is used as the people flow information. The sensor 2 may be any sensor capable of detecting people present within the visible range of the advertising medium 3, such as, but not limited to, a camera (visible light camera, infrared camera), LiDAR (Light Detection and Ranging), radar, etc. Although one sensor 2 is illustrated in FIG. 1 , multiple sensors 2 may be used. When multiple sensors 2 are used, multiple types of sensors 2 may be mixed. The sensor 2 may be mounted on the advertising medium 3 or installed separately from the advertising medium 3. A surveillance camera or the like may be used as the sensor 2. The sensor 2 may be included in the evaluation support system 100.

[0014] The evaluation support device 1 includes a range acquisition unit 11, a visible number calculation unit 12, an evaluation unit 13, an information storage unit 14, a people flow information acquisition unit 15, and a presentation unit 16. The people flow information acquisition unit 15 acquires sensor information from the sensor 2 and stores the acquired sensor information in the information storage unit 14. The sensor 2 may have a communication function, and the people flow information acquisition unit 15 may acquire the sensor information by communicating with the sensor 2, or the sensor 2 may be connected to another device such as a communication device (not shown), and the people flow information acquisition unit 15 may acquire the sensor information via the other device. The communication performed by the people flow information acquisition unit 15 may be wireless communication, wired communication, or both wireless communication and wired communication.

[0015] The range acquisition unit 11 acquires the viewable range of the advertising medium 3 and outputs the acquired viewable range to the view count calculation unit 12. Note that the range acquisition unit 11 may store the viewable range in the information storage unit 14, and the viewable number calculation unit 12 may read the viewable range from the information storage unit 14 when using the viewable range. When there are multiple advertising media 3 that are the subject of evaluation support by the evaluation support device 1, the range acquisition unit 11 acquires the viewable range for each advertising medium 3.

[0016] The range acquisition unit 11 may acquire the visible range by accepting a manually input visible range, or may acquire the visible range by receiving the visible range from another device (not shown). The range acquisition unit 11 may also acquire the visible range by calculating the visible range based on three-dimensional surrounding data, which is at least one of three-dimensional map data and three-dimensional measurement data, and the viewing angle of the advertising medium 3. That is, the visible range may be determined based on at least one of three-dimensional map data and three-dimensional measurement data. The viewing angle of the advertising medium 3 is the vertical and horizontal angular range within which the advertising medium 3 can be viewed when there are no obstacles around the advertising medium 3, and may be a specification value or may be measured by testing or the like when there are no obstacles around the advertising medium 3.

[0017] When calculating the visible range based on the three-dimensional surrounding data, the range acquisition unit 11 acquires the three-dimensional surrounding data by, for example, receiving the data from another device (not shown), but the method of acquiring the three-dimensional surrounding data is not limited thereto. The other device may be a measurement device that acquires three-dimensional measurement data, or an information processing device that provides three-dimensional measurement data, three-dimensional map data, etc. An example of the three-dimensional map data is, but is not limited to, PLATEAU provided by the Ministry of Land, Infrastructure, Transport and Tourism. The three-dimensional measurement data may be, for example, three-dimensional point cloud data acquired by a LiDAR, a stereo camera, a three-dimensional scanner, etc., but is not limited thereto.

[0018] FIG. 2 is a diagram showing an example of the viewable range in this embodiment. Note that the viewable range in this embodiment is a range in which the advertising medium 3 can be viewed when a person faces the advertising medium 3. In detail, for example, the viewable range is a range in which the advertising medium 3 can be viewed when a person's eyes are within the viewable range and face the advertising medium 3, but is not limited to this. The range 200 shown in FIG. 2 indicates the viewable range of the advertising medium 3. As shown in FIG. 2, in this embodiment, the viewable range is defined in three dimensions. That is, the viewable range is defined as three-dimensional data. The viewable range is indicated, for example, by three-dimensional coordinate values. Note that the viewable range indicated by the three-dimensional coordinate values ​​may be displayed by a map viewer or the like together with a three-dimensional map of the periphery of the advertising medium 3. This display may be performed by the presentation unit 16, or the viewable range indicated by the three-dimensional coordinate values ​​may be transmitted to an external device, and the external device may display the viewable range together with the three-dimensional map. It should be noted that the range 200 shown in FIG. 2 is merely an image of the visible range, and the actual visible range is not limited to this example.

[0019] If the viewable range is defined in two dimensions, i.e., in a horizontal plane, based on the viewing angle of the advertising medium 3, the height of the advertising medium 3 is not taken into consideration. In particular, when the advertising medium 3 is installed outdoors, the advertising medium 3 may be installed at a certain height, and the range in which the advertising medium 3 can be viewed varies depending on the installation height. A viewable range defined in two dimensions, taking into consideration only the field of view in a horizontal plane without taking the height direction into consideration, cannot accurately represent whether the advertising medium 3 can actually be viewed. In this embodiment, by defining the viewable range in three dimensions, the viewable range can be defined more accurately than when defined in two dimensions.

[0020] The visible range may also be defined taking into consideration obstacles such as buildings, plants, etc. In Fig. 2, obstacles such as buildings 4 and plants 5 exist around the advertising medium 3, and depending on the height at which the advertising medium 3 is installed and the height of the obstacles, the advertising medium 3 may not be visible due to the obstacles even if it is within the range of the field of view of the advertising medium 3. For this reason, the visible range may be determined taking the obstacles into consideration.

[0021] FIG. 3 is a diagram illustrating the consideration of obstacles in this embodiment. FIG. 3 is a diagram illustrating an advertising medium 3 and its surroundings as viewed from above. FIG. 3 shows an example in which, due to the presence of an obstacle, there is an area in which the advertising medium 3 cannot be seen even within the field of view of the advertising medium 3. In the example shown in FIG. 3, the advertising medium 3 cannot be seen in an area 201 in which an obstacle exists and an area 202 in which the advertising medium 3 cannot be seen due to the shadow of the obstacle. Therefore, the visible range can be more appropriately defined by defining area 200, which is the range in which areas 201 and 202 are excluded from the field of view of the advertising medium 3, as the visible range. Note that FIG. 3 illustrates the concept of considering obstacles and does not show the actual shapes of area 200, area 201, and area 202.

[0022] Depending on the height of the advertising medium 3 and the height of the obstacle, there may be an area where the advertising medium 3 is visible at a position farther from the advertising medium 3 than the shadow area 202. In such cases, this area is also considered to be within the visible range. For example, the visible range can be determined by taking the obstacle into consideration, i.e., by using three-dimensional peripheral data to trace a ray of light that is within the field of view of the advertising medium 3 starting from the advertising medium 3. However, the method for determining the visible range is not limited to this. As described above, the visible range may be input to the evaluation support device 1. In this case, a three-dimensionally defined visible range (data indicating the visible range) based on the viewing angle of the advertising medium 3 is generated by an external device (not shown) or manually, and the generated visible range is input to the evaluation support device 1. Note that when only passersby passing on the ground are considered in the evaluation of the advertising medium 3, the visible range may be determined based on the maximum expected human height, excluding the range above this maximum height.

[0023] Returning to the description of FIG. 1 , the view count calculation unit 12 calculates the number of views of the advertising medium 3 using the viewable range received from the range acquisition unit 11 and the sensor information read from the information storage unit 14, and outputs the calculated number of views to the evaluation unit 13. The view count calculation unit 12 includes a gaze estimation unit 121 and a counting unit 122. The gaze estimation unit 121 identifies people present within the viewable range using the viewable range and the sensor information, and estimates the gazes (gaze directions) of the identified people. The counting unit 122 counts the number of gazes directed toward the advertising medium 3 among the gazes estimated by the gaze estimation unit 121, and calculates the number of views based on the counting result. The view count calculation unit 12 may output not only the number of views but also data obtained during the calculation of the number of views (hereinafter also referred to as intermediate data) to the evaluation unit 13. The view count calculation unit 12 may also store the calculated number of views, data obtained during the calculation of the number of views, and the like in the information storage unit 14. The calculation of the number of views by the view number calculation unit 12 will be described in detail later.

[0024] The evaluation unit 13 calculates the evaluation value of the advertising medium 3 using the number of views acquired from the view count calculation unit 12. The evaluation unit 13 may calculate the evaluation value of the advertising medium 3 using the intermediate data acquired from the view count calculation unit 12, or may calculate the evaluation value of the advertising medium 3 using the number of views and the intermediate data acquired from the view count calculation unit 12. The evaluation unit 13 may calculate multiple types of evaluation values, and some of the multiple evaluation values ​​may be calculated based on data other than the number of views and the intermediate data. The evaluation unit 13 may include the number of views itself and the intermediate data itself acquired from the view count calculation unit 12 in the evaluation value. Details of the calculation of the evaluation value by the evaluation unit 13 will be described later.

[0025] The evaluation unit 13 stores the calculated evaluation value in the information storage unit 14 as part of the medium information. The medium information is information about the advertising medium 3, and includes, for example, identification information of the advertising medium 3, the installation location of the advertising medium 3, and the evaluation value of the advertising medium 3. The identification information of the advertising medium 3 is, for example, but is not limited to, the name of the advertising medium 3. When there are multiple advertising media 3, the identification information of the advertising medium 3, the installation location of the advertising medium 3, and the evaluation value of the advertising medium 3 for each advertising medium are stored in the information storage unit 14 as medium information. The evaluation value of the advertising medium 3 is calculated by the evaluation unit 13 as described above. The number of views calculated by the view count calculation unit 12, or the number of views and intermediate data, are stored in the information storage unit 14 by the evaluation unit 13 or the view count calculation unit 12 as evaluation values ​​in the medium information. Alternatively, the number of views calculated by the view count calculation unit 12, or the number of views and intermediate data, may be stored in the information storage unit 14 as part of the medium information, separate from the evaluation value.

[0026] The presentation unit 16 presents information stored in the information storage unit 14. The presentation unit 16 presents, for example, the number of views. The information to be presented may be predetermined, or the presentation unit 16 or an input receiving unit (not shown) may receive designation of the information to be presented from the service user, and the presentation unit 16 may present the information designated by the service user. For example, the presentation unit 16 displays information stored in the information storage unit 14 to present the information to the service user, who is a user using the evaluation support device 1. The presentation unit 16 may also present the information stored in the information storage unit 14 to at least one of a display device (not shown) and a terminal device (not shown) operable by the service user, thereby presenting the information to the service user, who is a user using the evaluation support device 1. The display device and the terminal device (not shown) operable by the service user display the information upon receiving the information from the evaluation support device 1. The terminal device (not shown) operable by the service user may be, for example, a personal computer, a smartphone, a tablet, or a computer system managed by the organization that will be the service user, but is not limited to these.

[0027] The information storage unit 14 stores sensor information, ratio information, and medium information. The ratio information indicates various ratios used for calculating the number of views in the view count calculation unit 12 and for calculating the evaluation value in the evaluation unit 13. Details of the ratio information will be described later.

[0028] 1 shows an example in which the evaluation support device 1 includes the evaluation unit 13, but the present invention is not limited to this, and the evaluation support device 1 may not include the evaluation unit 13. For example, the service user may evaluate the advertising medium 3 using the number of views calculated by the evaluation support device 1 itself as an evaluation value, or may evaluate the advertising medium 3 by calculating another evaluation value using the number of views calculated by the evaluation support device 1.

[0029] Next, the operation of this embodiment will be described. Fig. 4 is a flowchart showing an example of an evaluation support processing procedure in the evaluation support device 1 of this embodiment. As shown in Fig. 4, the evaluation support device 1 acquires a viewable range (step S1). In detail, the range acquisition unit 11 acquires a viewable range defined as three-dimensional data and outputs the acquired viewable range to the view number calculation unit 12. As described above, the viewable range may be input manually, or may be calculated by the range acquisition unit 11 based on three-dimensional surrounding data, which is at least one of three-dimensional map data and three-dimensional measurement data, and the viewing angle of the advertising medium 3.

[0030] The evaluation support device 1 acquires sensor information (step S2). Specifically, the people flow information acquisition unit 15 acquires the sensor information by receiving the sensor information from the sensor 2, and stores the acquired sensor information in the information storage unit 14.

[0031] The evaluation support device 1 identifies people within the visible range (step S3). Specifically, the gaze estimation unit 121 of the visible number calculation unit 12 identifies people within the visible range using the visible range received from the range acquisition unit 11 and the sensor information stored in the information storage unit 14. Note that one sensor 2 may cover the entire visible range, or the visible range may be covered by multiple sensors 2. That is, one sensor 2 may be able to detect the entire visible range, or the field of view ranges of the multiple sensors 2 may be complementary so that the multiple sensors 2 can detect the entire visible range.

[0032] The gaze estimation unit 121 detects a person in the field of view of the sensor 2, for example, by using sensor information. For example, if the sensor 2 is a camera, the gaze estimation unit 121 may detect a person by extracting an area corresponding to predetermined human characteristics from an image captured by the camera through image analysis, or may detect a person using a trained model generated by machine learning for detecting a person. Furthermore, the gaze estimation unit 121 may detect a person by recognizing a face through facial recognition processing, or may detect a person's skeleton using a skeletal model. Note that the method of person detection by the gaze estimation unit 121 is not limited to these, and any method may be used. Even if the sensor 2 is not a camera, person detection is performed using a method depending on the type of the sensor 2.

[0033] The gaze estimation unit 121 identifies the position of the detected person in the coordinate system of the sensor 2. Note that if the sensor 2 acquires two-dimensional data, such as a monocular camera, the position in the depth direction cannot be measured. However, the three-dimensional position of the detected person may be calculated based on, for example, the size of an average person, or the three-dimensional position of the detected person may be calculated using sensor information from multiple sensors 2. The gaze estimation unit 121 aligns the sensor 2 with the visible range and, after the alignment, identifies the person within the visible range. For example, if the visible range is defined by the position of the eyes, the gaze estimation unit 121 calculates the position of the detected person's eyes, and then uses the position of the sensor 2 and the field of view of the sensor 2 to convert the three-dimensional position of the person's eyes from the coordinate system of the sensor 2 to a coordinate system representing the visible range, and determines whether the three-dimensional position of the person's eyes after the coordinate conversion is within the visible range, thereby identifying the person within the visible range. The three-dimensional position of the person's eyes may be determined by facial recognition processing, skeletal detection, or the like, or may be determined based on the person's horizontal position calculated based on sensor information and the average person's eye height.

[0034] When multiple sensors 2 are used, there is a possibility that the same person may be detected based on the sensor information acquired by each sensor 2. Therefore, the gaze estimation unit 121 determines whether a person detected from the sensor information is the same person as a person detected from the sensor information of another sensor 2. Then, using the determination result, the gaze estimation unit 121 identifies people within the visible range by treating the same person as one person. Note that people identified by the gaze estimation unit 121 as being within the visible range (people within the visible range) are also called OTSs (Opportunity To See), and the number of OTSs may be used to evaluate the advertising medium 3 or to calculate an evaluation value. The gaze estimation unit 121 may output the number of people within the visible range to the evaluation unit 13 as intermediate data. The gaze estimation unit 121 may also store the number of people within the visible range in the information storage unit 14 as part of the medium information or separately from the medium information.

[0035] Note that even if the evaluation support device 1 uses the sensor information of all the sensors 2 from which it acquires sensor information, there may be a range in the visible range that cannot be detected by the sensor 2. That is, even if the visual field ranges of all the sensors 2 are combined, there may be a range in the visible range that is not included in the visual field range of the sensor 2. That is, in this case, the gaze estimation unit 121 cannot detect all people in the visible range, and therefore, when calculating the number of people seen, which will be described later, adjustment is made using, for example, a predetermined coefficient. In this case, the coefficient is determined by a demonstration experiment or the like, and is stored in the information storage unit 14 as part of the ratio information.

[0036] Next, the evaluation support device 1 estimates the gaze (step S4). In detail, the gaze estimation unit 121 estimates the gaze (gaze direction) of the person identified as being within the visible range. The gaze may be calculated using a skeletal model, or if the sensor information is an image, it may be calculated by determining the facial orientation through image processing. Furthermore, if the sensor information is acquired in chronological order, i.e., if multiple pieces of sensor information corresponding to different times are acquired, the gaze estimation unit 121 may calculate the movement direction of the person identified as being within the visible range, calculate the body orientation from the movement direction, and estimate the gaze by assuming that the body orientation is the facial orientation.

[0037] Next, the evaluation support device 1 calculates the number of people looking at the advertising medium 3 (step S5). In detail, the counting unit 122 of the view count calculation unit 12 counts the number of people whose gaze is directed at the advertising medium 3 based on the estimation result of the gaze estimation unit 121. FIG. 5 is a diagram for explaining people looking at the advertising medium 3. The human-shaped figures shown in FIG. 5 indicate people within the viewable range of the advertising medium 3, and the arrows indicate the direction of the gaze. The solid arrows indicate people whose gaze is directed at the advertising medium 3, i.e., people who are looking at the advertising medium 3, and the dashed arrows indicate people whose gaze is not directed at the advertising medium 3, i.e., people who are not looking at the advertising medium 3.

[0038] Furthermore, the number of people looking at the advertising medium 3 may be calculated taking obstacles into consideration. FIG. 6 is a diagram for explaining people looking at the advertising medium 3, taking obstacles into consideration. Like the people whose gazes are indicated by dashed lines in FIG. 6 , people whose gazes are directed toward the advertising medium 3 but who cannot see the advertising medium 3 because they are shaded by obstacles may be excluded from people looking at the advertising medium 3. Note that if obstacles are taken into consideration when defining the viewable range, that is, if the viewable range is determined taking obstacles into consideration as a position where the advertising medium 3 can be seen if the eyes are located there and the gaze is directed toward the advertising medium 3, the obstacles have already been taken into consideration when defining the viewable range. Therefore, in this case, the counting unit 122 may determine whether the gaze is directed toward the advertising medium 3 based on the direction of the gaze without taking obstacles into consideration.

[0039] The people looking at the advertising medium 3 are also called OTCs (Opportunity To Contact), and the number of OTCs may be used to evaluate the advertising medium 3 or to calculate an evaluation value. The gaze estimation unit 121 may output the number of people looking at the advertising medium 3 as intermediate data to the evaluation unit 13. The gaze estimation unit 121 may also store the number of people looking at the advertising medium 3 in the information storage unit 14 as part of the medium information or separately from the medium information.

[0040] The gaze estimation unit 121 may estimate the attributes of the OTC or OTS based on the sensor information, and store attribute information indicating the estimated attributes as medium information in the information storage unit 14. For example, if the sensor 2 includes a camera, attributes such as gender and age of each of the OTC and OTS may be estimated using an image acquired by the camera, and the number of people for each attribute may be stored in the information storage unit 14 as attribute information, or the ratio of attributes, such as the ratio of genders, may be stored in the information storage unit 14 as attribute information.

[0041] Returning to the explanation of Figure 4, the evaluation support device 1 calculates the number of views (step S6). In detail, the counting unit 122 calculates the number of views by multiplying the number of people counted in step S5 by the predetermined visibility rate read from the information storage unit 14, and outputs the calculated number of views to the evaluation unit 13. The number of views is the number of people estimated to have actually viewed the advertising medium 3 (the advertisement displayed on the advertising medium 3). The visibility rate is stored in the information storage unit 14 as ratio information.

[0042] The number of people who are estimated to have actually viewed the advertising medium 3 is also called VAC (Visibility Adjusted Contact) or impressions. The number of VAC can be calculated by multiplying the number of OTCs by the ratio (visibility rate) of people who are estimated to have viewed the advertisement (the advertisement displayed on the advertising medium 3). The visibility rate is calculated in advance, for example, through an experiment using an eye-tracking camera, but the method for calculating the visibility rate is not limited to this and any other method may be used. The counting unit 122 may store the number of views in the information storage unit 14 as part of the medium information. Note that if there is a range within the viewable range that cannot be detected by the sensor 2, the counting unit 122 calculates the number of views by multiplying the number of people counted in step S5 by the visibility rate and a coefficient included in the ratio information described above. Note that the above-mentioned method can be used to calculate the number of views based on the acquisition cycle of sensor information. When calculating the number of views for a long unit of time such as one hour, one day, or one week, the counting unit 122 may calculate the number of views for the unit of time by aggregating the calculated number of views for the unit of time. In this case, the view number calculation unit 12 may identify the same person detected in multiple different time periods within the unit of time and treat them as one person.

[0043] In this embodiment, the number of views is calculated using the viewable range defined as three-dimensional data and the sensor information. Therefore, it is not necessary to install a camera that matches the viewable range of the advertising medium 3, and the number of views can be calculated without strict camera installation conditions. Furthermore, when estimating the gaze using face recognition processing using a camera image, the camera needs to capture a frontal image of a person. However, by using a skeletal model to identify the OTS based on the orientation of the body or face, or by estimating the gaze based on the direction of movement, the view number calculation unit 12 can estimate the gaze even when the orientation of the sensor 2 does not detect the front of the person. The view number calculation unit 12 may estimate the gaze by combining two or more of face recognition processing, estimation using a skeletal model, and estimation using the direction of movement. Therefore, the evaluation support device 1 of this embodiment can estimate the number of views using sensors 2 installed in various positions and orientations, such as a surveillance camera installed in a position different from the advertising medium 3.

[0044] Next, the evaluation support device 1 calculates an evaluation value (step S7). Specifically, the evaluation unit 13 calculates an evaluation value for evaluating the advertising medium 3 using the number of views and stores the calculated evaluation value in the information storage unit 14 as part of the medium information. The evaluation unit 13 may calculate the evaluation value, for example, using an advertising price set for the advertising medium 3 and the number of views. The advertising price is a usage fee for the advertising medium and is also called an advertisement posting price. Specifically, the evaluation unit 13 calculates, as the evaluation value, a cost-per-viewer acquisition obtained by dividing the advertising price by the number of views. In this case, the advertising price is stored in advance in the information storage unit 14 as medium information. The evaluation unit 13 may also calculate a viewer rating (advertising viewer rating), which is the ratio of the number of views (the number of people in the VAC) to the number of people within the viewable range (the number of people in the OTS).

[0045] The evaluation unit 13 may also calculate the evaluation value using intermediate data such as the number of OTC users and the number of OTS users calculated by the view count calculation unit 12. As described above, the number of views (number of VACs, number of impressions) itself may be used as the evaluation value, or the intermediate data itself may be used as the evaluation value. The evaluation value calculated by the evaluation unit 13 is not limited to the above-described examples, and may include CPM (Cost Per Mille), number of reach clicks, CTR (Click Through Rate), CPC (Cost Per Click), CV (Conversions), CVR (Conversion Rate), number of sessions, CPA (Cost Per Acquisition), etc. Regarding evaluation values ​​that use click-related numerical values, for example, the number of views, number of OTC users, number of OTS users, etc. may be used in place of click-related numerical values ​​as appropriate depending on the evaluation value.

[0046] The evaluation support device 1 presents the calculation result (step S8) and ends the process. Specifically, the presentation unit 16 presents to the service user the number of views, intermediate data, evaluation value, etc. stored in the information storage unit 14. As described above, the number of views and intermediate data may be included in the evaluation value.

[0047] Note that Figure 4 is an example, and the order of each process is not limited to the example shown in Figure 4. For example, in Figure 4, step S8 is presented after the evaluation value is calculated, but if the service user wants to check the number of views and intermediate data, step S8 may be presented before the evaluation value is calculated. In this way, the timing of presenting each piece of information to the service user is not limited to the example shown in Figure 4. Furthermore, step S1 may be performed at a timing separate from the timing of the processes from step S2 onwards. Step S1 may be performed when an advertising medium 3 is added or deleted, the specifications of the advertising medium 3 are changed, or when there is a change in the circumstances surrounding the advertising medium 3, or it may be performed at regular intervals such as every six months.

[0048] Next, the hardware configuration of the evaluation support device 1 of this embodiment will be described. The evaluation support device 1 of this embodiment shown in FIG. 1 functions as the evaluation support device 1 by executing a computer program, which is a computer program that describes the processing in the evaluation support device 1, on the computer system. FIG. 7 is a diagram showing an example of the configuration of a computer system that realizes the evaluation support device 1 of this embodiment. As shown in FIG. 7, this computer system includes a control unit 101, an input unit 102, a memory unit 103, a display unit 104, a communication unit 105, and an output unit 106, which are connected via a system bus 107. The control unit 101 and the memory unit 103 form a processing circuit.

[0049] In FIG. 7 , the control unit 101 is a processor such as a CPU (Central Processing Unit) that executes a program describing the processing of the evaluation support device 1 of this embodiment. Note that a portion of the control unit 101 may be realized by dedicated hardware such as a GPU (Graphics Processing Unit) or an FPGA (Field-Programmable Gate Array). The input unit 102 includes buttons, a keyboard, a mouse, a touchpad, and the like. The storage unit 103 includes various types of memory, such as a RAM (Random Access Memory) and a ROM (Read Only Memory), and a storage device, such as a hard disk, and stores programs to be executed by the control unit 101, necessary data obtained during processing, and the like. The storage unit 103 is also used as a temporary storage area for programs. The display unit 104 is, for example, a display, such as an LCD (Liquid Crystal Display). Note that the display unit 104 and the input unit 102 may be integrated and realized as a touch panel, etc. The communication unit 105 is a receiver and transmitter that perform communication processing. The output unit 106 is a speaker or the like. Note that Fig. 7 is just an example, and the configuration of the computer system is not limited to the example of Fig. 7. For example, the computer system that realizes the evaluation support device 1 does not need to include the input unit 102, the display unit 104, and the output unit 106.

[0050] Here, an example of the operation of the computer system until the program of this embodiment is ready to be executed will be described. In the computer system having the above configuration, for example, a computer program is installed into the storage unit 103 from a CD-ROM or DVD-ROM inserted in a CD (Compact Disc)-ROM drive or DVD (Digital Versatile Disc)-ROM drive (not shown). Then, when the program is executed, the program read from the storage unit 103 is stored in the main storage area of ​​the storage unit 103. In this state, the control unit 101 executes the processing as the evaluation support device 1 of this embodiment in accordance with the program stored in the storage unit 103.

[0051] In the above explanation, a program describing the processing in the evaluation support device 1 is provided using a CD-ROM or DVD-ROM as a recording medium, but this is not limited to this, and it is also possible to use a program provided via a transmission medium such as the Internet, depending on the configuration of the computer system, the capacity of the program to be provided, etc.

[0052] The program of this embodiment, for example, causes a computer system to execute the steps of acquiring people flow information indicating the flow of people around the advertising medium 3, acquiring the viewable range, and calculating the number of views, which is the number of people who viewed the advertising medium 3, using the viewable range and the people flow information.

[0053] The view count calculation unit 12 and the evaluation unit 13 shown in FIG. 1 are realized by the control unit 101 shown in FIG. 7 executing a computer program stored in the storage unit 103 shown in FIG. 7. The storage unit 103 shown in FIG. 7 is also used to realize the view count calculation unit 12 and the evaluation unit 13. The range acquisition unit 11 shown in FIG. 1 may be realized by at least one of the input unit 102 and the communication unit 105, or may be realized by the control unit 101 shown in FIG. 7. The people flow information acquisition unit 15 shown in FIG. 1 is realized by the communication unit 105 shown in FIG. 7. The presentation unit 16 shown in FIG. 1 is realized by at least one of the display unit 104 and the communication unit 105 shown in FIG. 7. The presentation unit 16 shown in FIG. 1 may further be realized by the control unit 101 shown in FIG. 7 or the input unit 102 shown in FIG. 7. The evaluation support device 1 may be realized by multiple computer systems. For example, the evaluation support device 1 may be realized by a cloud computer system.

[0054] As described above, in this embodiment, the evaluation support device 1 calculates the number of views using the viewable range defined as three-dimensional data and sensor information. Therefore, it is not necessary to install a camera that matches the viewable range of the advertising medium 3, and it is possible to calculate the number of views without requiring strict camera installation conditions.

[0055] Second Embodiment. Figure 8 is a diagram showing an example of the configuration of an evaluation support system according to a second embodiment. The evaluation support system 100a of this embodiment includes an evaluation support device 1a and an advertising medium 3. The advertising medium 3 is the same as that of the first embodiment. The evaluation support device 1a is the same as the evaluation support device 1 of the first embodiment, except that it includes a view count calculation unit 12a instead of the view count calculation unit 12, and the people flow information acquisition unit 15 uses people flow information provided by the people flow information providing device 6 instead of sensor information as people flow information. Components having the same functions as those of the first embodiment are assigned the same reference numerals as those of the first embodiment, and redundant explanations will be omitted. Below, differences from the first embodiment will be mainly explained.

[0056] In this embodiment, the people flow information acquisition unit 15 acquires people flow information from the people flow information providing device 6 and stores the acquired people flow information in the information storage unit 14. The people flow information providing device 6 provides people flow information indicating the flow of people around the advertising medium 3. People such as passersby around the advertising medium 3 are audiences that advertisers, advertising agencies, etc. want to see advertisements displayed on the advertising medium 3, and hereinafter, people around the advertising medium 3 will also be referred to as passersby or general users.

[0057] The people flow information provided by the people flow information providing device 6 may be, for example, questionnaire responses obtained from terminal devices 7 that can be operated by general users who are passersby, and location information indicating the location of the terminal devices 7. The terminal devices 7 are, for example, smartphones, tablets, personal computers, etc., and are terminal devices carried by general users. The terminal devices 7 are equipped with a location detection device that detects their own location, such as a GPS (Global Positioning System) receiver. The location information is, for example, time-series information associated with the location time of the terminal devices 7, and the terminal devices 7 transmit the location information to the people flow information providing device 6. For example, the questionnaire is distributed to terminal devices 7 in the vicinity of the advertising medium 3, and general users input responses by operating the terminal devices 7, and the terminal devices 7 transmit the input responses to the people flow information providing device 6.

[0058] The questionnaire includes a question asking whether or not the user has viewed the advertising medium 3, i.e., whether or not the user has seen the advertising medium 3. FIG. 9 is a diagram showing an example of a questionnaire in this embodiment. In the example shown in FIG. 9, three options are displayed on the terminal device 7 for an advertisement displayed on a certain advertising medium 3 (denoted as XX in FIG. 9): "Saw (are seeing)," "May have seen," and "Did not see." A general user selects an answer from the options by operating the terminal device 7. The terminal device 7 transmits the answers to the questionnaire to the people flow information providing device 6. Note that the number of options when asking whether or not the user has viewed the advertising medium 3 is not limited to the example shown in FIG. 9; two options, "Saw" or "Did not see," or four or more options may be displayed.

[0059] The questionnaire may also include questions about the attributes of general users. The attributes may include, for example, at least one of gender and age. The attributes are not limited to this, but may also include age, hobbies, occupation, educational background, annual income, assets, place of residence, place of work, nationality, family structure, hobbies, tastes / lifestyle, health status, etc. Although two terminal devices 7 are illustrated in FIG. 8 , the number of terminal devices 7 is not limited to this.

[0060] Furthermore, the people flow information provided by the people flow information providing device 6 may be information indicating the number of passersby (number of passersby) or location information obtained from a terminal device 7 that can be operated by a general user. The people flow information provided by the people flow information providing device 6 is not limited to information indicating the flow of people around the advertising medium 3. Hereinafter, the survey results and location information will also be referred to as survey information, and information indicating the number of passersby will also be referred to as passerby information. The people flow information provided by the people flow information providing device 6 may be two or more of the survey information, passerby information, and location information of the terminal device 7. Furthermore, a people flow information providing device 6 may be provided for each type of people flow information, and the people flow information acquisition unit 15 may acquire each type of people flow information from the people flow information providing device 6.

[0061] The passerby information may be information indicating the flow of people for each travel route, i.e., the number of passersby for each travel route. A travel route is represented by the section and direction of travel, such as a route traveling from X to Y on road A toward Y. FIG. 10 is a diagram for explaining travel routes in passerby information of this embodiment. Travel routes R-1 to R-14 shown in FIG. 10 are examples of travel routes around advertising medium 3. The direction of the arrow indicates the direction of travel of passersby. FIG. 11 is a diagram showing an example of passerby information of this embodiment. In the example shown in FIG. 11, the passerby information includes the number of passersby in each time period for each travel route shown in FIG. 10. FIG. 10 is an example, and the definition of each travel route is not limited to the example shown in FIG. 10.

[0062] Furthermore, the passerby information may be calculated based on actual measurements taken using a camera or the like, acquired through a traffic volume survey, or may be an analysis result calculated based on location information from a smartphone or the like, such as in Mobile Spatial Statistics (registered trademark). The analysis results may be calculated for each day of the week, season, weather, or the like. The passerby information may also include attribute information regarding the attributes of passersby. For example, attribute ratios such as the gender ratio (gender composition) and age ratio (age composition) of passersby may be calculated based on a past survey, and these ratios may be included in the passerby information as attribute information, or the number of passersby may be calculated as the number of people for each attribute. Note that the method for determining the number of passersby and the method for determining attribute information for the number of passersby are not limited to these examples.

[0063] The view count calculation unit 12a calculates the number of views using the same viewable range as in the first embodiment and the people flow information stored in the information storage unit 14. In the first embodiment, the view count calculation unit 12 calculates the number of views at the time (period) that is the subject of evaluation of the advertising medium 3, but in the present embodiment, the view count calculation unit 12a may calculate the number of views in order to calculate the view rate described in the first embodiment. That is, the view count calculation unit 12a performs at least one of calculating the number of views at the time that is the subject of evaluation of the advertising medium 3 and calculating the number of views for calculating the view rate.

[0064] Here, first, the processing of the visible number calculation unit 12a when the people flow information includes survey information will be described. When the people flow information includes survey information, the visible number calculation unit 12a uses the visible range and the location information in the survey information to identify responding users who passed through the visible range among the responding users corresponding to the location information. That is, the visible number calculation unit 12a uses the location information and the visible range to identify people who passed through the visible range among the passersby corresponding to the survey responses (response information). The responding users are general users who answered the survey. The visible number calculation unit 12a calculates the number of responding users who were present within the visible range per unit time based on the determination result. The responding users who were present within the visible range are general users who answered the survey in the OTS.

[0065] Next, the view count calculation unit 12a estimates the gazes of responding users who were present within the viewable range based on the location information. For example, the view count calculation unit 12a uses the location information to determine the movement direction of the responding users and estimates their gazes based on the movement direction. The view count calculation unit 12a uses the gaze estimation result to identify people who were looking toward the advertising medium 3 among the responding users who were present within the viewable range, and calculates the number of people who were looking toward the advertising medium 3 using the identification result. In this way, the view count calculation unit 12a calculates the number of people with a viewing opportunity who were looking toward the advertising medium 3, using location information corresponding to people identified as having passed within the viewable range. People who were looking toward the advertising medium 3 among the responding users who were present within the viewable range are general users of OTC who responded to the questionnaire.

[0066] Next, the view count calculation unit 12a calculates the number of views of the advertising medium 3 using the questionnaire responses corresponding to those of the responding users who were present within the viewable range and who were looking at the advertising medium 3. The calculated number of views is the number of general users who responded to the questionnaire among the VAC. Note that, as illustrated in FIG. 9 , in cases where the responses include not only whether they saw the advertisement or not, but also intermediate options such as "may have seen the advertisement," the view count calculation unit 12a may calculate the number of views by regarding the intermediate responses as a number less than 1, such as 0.5 people or 0.75 people, rather than counting them as one person.

[0067] The view count calculation unit 12a calculates the visibility rate by dividing the number of views of the advertising medium 3 by the number of people looking at the advertising medium 3. In this way, the view count calculation unit 12a calculates the number of view responses, which is the number of survey responses indicating that the advertising medium 3 was viewed among the survey responses corresponding to viewing opportunity holders, and calculates the visibility rate based on the number of viewing opportunity holders and the number of view responses. Although the responding users who were present within the viewable range do not represent all general users who were present within the viewable range, if the number of responding users is sufficient, the visibility rate calculated for the responding users can be considered to be the same as the visibility rate for all general users. For example, a threshold value is set based on an acceptable error, and in a case where the responding users are the threshold value, the visibility rate is calculated by dividing the number of views of the advertising medium 3 by the number of people looking at the advertising medium 3, as described above. In this way, the visibility rate may be calculated based on the location information of the terminal device 7 carried by a passerby who passed near the advertising medium 3 and the questionnaire response (response information) input by the passerby, which includes information indicating whether or not the passerby viewed the advertising medium 3. The method of determining the threshold value for the responding users is not limited to this example.

[0068] The view count calculation unit 12a stores the calculated view rate as ratio information in the information storage unit 14. This view rate may be used, for example, by the evaluation support device 1a when calculating the number of views at the time of evaluation of the advertising medium 3, or may be used to calculate the number of views in a device that calculates the number of views in a manner similar to that of the evaluation support device 1 of embodiment 1. Note that the people flow information acquisition unit 15 of the evaluation support device 1a may further acquire sensor information from the sensor 2 described in embodiment 1, and the view count calculation unit 12a may also function as the view count calculation unit 12 of embodiment 1. In this case, when the view count calculation unit 12a calculates the number of views described in embodiment 1, the view rate calculated using the questionnaire information described in this embodiment may be used.

[0069] In addition, the view count calculation unit 12a may calculate the encounter probability, which is the ratio of the number of OTS users to the number of OTC users, by dividing the number of responding users who were within the visible range and were looking toward the advertising medium 3 by the number of responding users who were within the visible range and were looking toward the advertising medium 3, and store this encounter probability in the information storage unit 14 as ratio information.

[0070] Furthermore, the view count calculation unit 12a may use the location information to calculate the view rate for each travel route as illustrated in Fig. 10. Furthermore, the view count calculation unit 12a may calculate the view count for each attribute based on the questionnaire responses and store the calculated result as medium information in the information storage unit 14, or may calculate the number of responding users for each attribute and store the calculated result as medium information in the information storage unit 14.

[0071] Furthermore, the view count calculation unit 12a may use the questionnaire responses to calculate the number of views at the time of evaluation of the advertising medium 3. For example, if the time of evaluation of the advertising medium 3 is in the past, the number of views can be calculated using questionnaire information of responding users who were within the viewable range at the time of evaluation. In detail, for example, the view count calculation unit 12a uses location information to calculate the number of views using questionnaire information in the same manner as described above. Since this number of views is the number of views related to the responding users, the view count calculation unit 12a calculates the total number of views by multiplying the calculated number of views by a predetermined ratio. This ratio is the ratio of the number of responding users to the number of general users, i.e., passersby, and is determined, for example, by demonstration experiments, statistical analysis, etc., and is stored in advance as ratio information in the information storage unit 14.

[0072] Next, the processing of the view number calculation unit 12a when the pedestrian flow information includes passerby information will be described. When the pedestrian flow information includes passerby information at the time of estimation of the advertising medium 3, the view number calculation unit 12a calculates the number of people looking at the advertising medium 3 within the viewable range (the number of OTCs) by using the viewable range, passerby information, and ratio information stored in the information storage unit 14. For example, for each movement route, the ratio of people looking at the advertising medium 3 among passersby traveling on that movement route is determined as a route unit ratio through demonstration experiments, analysis, etc., and the route unit ratio is stored in advance in the information storage unit 14 as ratio information. The view number calculation unit 12a calculates the number of OTCs for each movement route by multiplying the number of passersby for each movement route in the passerby information by the route unit ratio corresponding to that movement route. The view count calculation unit 12a calculates the total number of people using the OTC for each travel route as the number of people using the OTC, and calculates the number of people using the OTC by multiplying the number of people using the OTC by the view rate stored as ratio information in the information storage unit 14. This view rate may be a view rate calculated based on the questionnaire information described in this embodiment, or may be a view rate calculated by another method.

[0073] Next, the processing of the view count calculation unit 12a when the pedestrian flow information includes the location information of the terminal device 7 will be described. When the pedestrian flow information includes the location information of the terminal device 7 at the time of estimation of the advertising medium 3, the view count calculation unit 12a calculates the number of people looking at the advertising medium 3 within the viewable range (the number of OTC users) using the viewable range, the location information, and the acquisition ratio stored in the information storage unit 14. The acquisition ratio is the ratio of the number of terminal devices 7 whose location information can be acquired to the total number of passersby. Because some passersby cannot acquire the location of the terminal device 7, the view count calculation unit 12a calculates the movement direction of each terminal device 7 based on the location information, identifies people looking at the advertising medium 3 within the viewable range based on the movement direction, calculates the number of identified people, and calculates the number of OTC users by dividing the calculated number by the acquisition ratio. The view count calculation unit 12a calculates the number of OTC users by multiplying the number of OTC users by the visibility rate stored as ratio information in the information storage unit 14. This visibility rate may be a visibility rate calculated based on the questionnaire information described in the present embodiment, or may be a visibility rate calculated by another method.

[0074] The evaluation unit 13 calculates the evaluation value in the same manner as in embodiment 1, using the number of views of the advertising medium 3 at the time of estimation target, as exemplified in this embodiment. In this embodiment, too, the evaluation unit 13 may use intermediate data such as the number of views or the number of OTS users as the evaluation value. As described above, the people flow information acquisition unit 15 of the evaluation support device 1a may further acquire sensor information, and the view count calculation unit 12a may also function as the view count calculation unit 12 of embodiment 1. The view rate calculated using the questionnaire information described in this embodiment may be used in calculating the view count described in embodiment 1. The operation of the evaluation support device 1a other than that described above is the same as in embodiment 1.

[0075] The evaluation support device 1a of this embodiment is realized, for example, by the computer system illustrated in FIG. 7, similar to the evaluation support device 1 of embodiment 1. The view count calculation unit 12a illustrated in FIG. 8 is realized by the control unit 101 illustrated in FIG. 7 executing a computer program stored in the storage unit 103 illustrated in FIG. 7. The storage unit 103 illustrated in FIG. 7 is also used to realize the view count calculation unit 12a. The evaluation support device 1a may be realized by multiple computer systems. Furthermore, for example, the evaluation support device 1a may be realized by a cloud computer system.

[0076] As described above, in this embodiment, the number of sighted objects is calculated based on the visible range and at least one of the questionnaire information, the passerby information, and the location information of the terminal device 7. This makes it possible to achieve the same effects as in the first embodiment. In addition, the number of sighted objects can be calculated without the need to install the sensor 2.

[0077] Embodiment 3 Next, embodiment 3 will be described. The configuration of the evaluation support system 100 of this embodiment is the same as embodiment 1. Below, differences from embodiment 1 will be mainly described, and explanations that overlap with embodiment 1 will be omitted.

[0078] In this embodiment, the viewable range is determined based on the specifications of each advertising medium 3. The specifications of the advertising medium 3 include, for example, at least one of brightness, viewing angle, and curvature information indicating the shape of the screen curvature. The range acquisition unit 11 may accept input of the viewable range taking the specifications into consideration, or may calculate the viewable range based on 3D map data or 3D measurement data taking the specifications into consideration. Furthermore, if the brightness can be changed by setting, the range acquisition unit 11 may acquire information indicating the setting and change the viewable range according to the setting.

[0079] Similarly, in the evaluation support system 100a described in the second embodiment, the viewable range may be determined based on specifications. This allows the viewable range of the advertising medium 3 to be defined with high precision.

[0080] Fourth Embodiment Fig. 12 is a diagram showing an example of the configuration of an evaluation support system according to a fourth embodiment. An evaluation support system 100b according to this embodiment includes an evaluation support device 1b and an advertising medium 3. The advertising medium 3 is the same as that of the first embodiment. The evaluation support device 1b is the same as the evaluation support device 1 of the first embodiment, except that a receiving unit 17 and a prediction unit 18 are added. Components having the same functions as those of the first embodiment are given the same reference numerals as those of the first embodiment, and redundant explanations will be omitted. Below, differences from the first embodiment will be mainly explained.

[0081] In this embodiment, the reception unit 17 receives input from the service user. Note that the reception unit 17 may receive input directly from the service user, or may receive input information input to a terminal device that the service user can operate, thereby receiving input from the service user.

[0082] The receiving unit 17, for example, receives designation of information to be displayed from the service user and notifies the presentation unit 16 of designation information indicating the content of the designation from the service user. The designation information may include the advertising medium 3 to be displayed, the date and time to be displayed, etc. The date and time to be displayed may be a period. The information to be displayed may be the number of views, intermediate data, evaluation value, attribute information, etc. calculated by the evaluation support system 100b, information processed based on such information, or the installation location of the advertising medium 3, advertising price, etc. included in the medium information. Note that the presentation unit 16 may present the service user with options for information to be displayed, and the service user may select information to be displayed from the options, thereby designating the information to be displayed. Each option may be a combination of multiple pieces of information. The designation information may also include a display format, such as whether the information is to be displayed as numerical values, a pie chart, a line graph, or a bar graph.

[0083] The presentation unit 16 reads information to be displayed from the information storage unit 14 based on the specified information notified by the reception unit 17, and presents the read information. The presentation method by the presentation unit 16 is the same as in the first embodiment, and may be displaying information or transmitting information to another device such as a display device or a service user's terminal device. When the presentation unit 16 presents information by transmitting it to another device, display information for displaying a display screen may be transmitted to the other device, or the information to be displayed and information indicating a display format, etc. may be transmitted to the other device, and the other device may generate a display screen. Furthermore, an initial screen to be presented to the service user when there is no specification from the service user may be determined, and the presentation unit 16 may present the initial screen when the specified information is not notified.

[0084] Furthermore, when displaying information in the form of a graph, for example, the presentation unit 16 creates a graph based on the information read from the information storage unit 14 and presents the created graph. The presentation unit 16 may present at least one of the number of pedestrians (number of OTCs) which is the number of pedestrians who passed through the visible range, information on the flow of people by attribute, and an audience rating calculated based on the number of views.

[0085] FIG. 13 is a diagram showing an example of a display screen according to this embodiment. The display screen shown in FIG. 13 may be displayed by the presentation unit 16, or may be displayed by another device as a result of display information for displaying the display screen being transmitted to the other device by the presentation unit 16. In the example shown in FIG. 13, advertising medium A is specified by the specification information. In the example shown in FIG. 13, the date and time to be displayed can be specified by entering a date and time in the blank space in the line labeled "Submission Period." FIG. 13 shows a state in which a date and time have been specified once and each piece of information is displayed. In this state, by entering a date and time and pressing the button labeled "Calculate," information corresponding to the entered date and time is displayed.

[0086] In the example shown in FIG. 13 , the "number of passersby within the viewable range," "ad viewership rating," and "number of ad viewers" are displayed in the rectangular area. The "number of passersby within the viewable range" is the number of people within the viewable range, i.e., the number of OTCs, and the "number of ad viewers" is the number of views, i.e., the number of VACs. The numerical values ​​of these items are shown as totals for a specified date and time (period). As described in the first embodiment, these numerical values ​​are calculated by the view count calculation unit 12 or the evaluation unit 13 and stored in the information storage unit 14 as medium information. If the date and time of the display target can be specified, for information whose numerical values ​​vary depending on the date and time, the information may be calculated for each specified unit time and stored as medium information, for example, so that information corresponding to each date and time can be tallied.

[0087] In the example shown in FIG. 13 , three graphs are displayed. The left graph shows the number of OTS passengers, the number of OTC passengers, and the number of VAC passengers, with the horizontal axis representing time (date and time). The center graph shows the gender ratio, and the right graph shows the age distribution. The gender distribution and age distribution may be calculated based on attributes determined based on sensor information as described in the first embodiment, or based on questionnaire responses as described in the second embodiment, or may be analysis results included in the provided people flow information. The gender distribution and age distribution are examples of information regarding people flow by attribute. Here, the gender distribution and age distribution are assumed to be the same for OTS, OTC, and VAC, and may correspond to any of OTS, OTC, and VAC. FIG. 13 is an example, and the displayed information, display format, display position, design, etc. are not limited to the example shown in FIG. 13 .

[0088] Furthermore, in the present embodiment, when a service user specifies a date and time to be displayed and information corresponding to the date and time is not stored in the information storage unit 14, the prediction unit 18 may make a prediction corresponding to the specified date and time, output the prediction result to the presentation unit 16, and the presentation unit 16 may present the prediction result. The prediction unit 18 predicts the information for the date and time to be displayed based on the information stored in the information storage unit 14. For example, when displaying the number of views, the prediction unit 18 predicts the number of views for the date and time to be displayed based on the number of views stored in the information storage unit 14. When making the prediction, conditions related to the date and time (time period, day of the week, season, month, weekday / holiday), weather, etc. may be taken into consideration. The prediction target information to be predicted by the prediction unit 18 may be, for example, at least one of the number of views, the number of passersby, information on people flow by attribute, and audience rating.

[0089] Furthermore, the conditions taken into consideration when making a prediction may include the type of industry of the advertisement displayed on the advertising medium 3, the type of product advertised, an outline of the advertisement design (whether it is a video or a still image, the use of color, etc.), whether a commercial is being aired on television, the length of the advertisement period, etc. For example, the prediction unit 18 may calculate the average value of the number of views stored in the information storage unit 14 for each condition and use the average value as the predicted value, or may determine a prediction formula for predicting the average value based on changes in these average values ​​over time and obtain the predicted value based on the prediction formula. The prediction formula may also use the above-mentioned conditions related to time, weather, etc.

[0090] The prediction unit 18 may also obtain a predicted value using a trained model for inferring a predicted value from input feature quantities through machine learning. For example, the feature quantities include at least one of the above-mentioned time-related conditions and conditions such as weather. For example, when the number of pedestrians is predicted, a trained model is generated through supervised learning using multiple training datasets each consisting of feature quantities and the number of pedestrians as ground truth data. Any algorithm may be used for machine learning, but a neural network (neural network model) may be used, for example. The prediction unit 18 inputs feature quantities corresponding to a specified date and time into the trained model, thereby obtaining a predicted value for the number of pedestrians as the output of the trained model. Note that if the feature quantities include weather, the prediction unit 18 may obtain a weather forecast value for the specified date and time from an external device that provides weather data and use the forecast value as the feature quantity.

[0091] Furthermore, the feature amount may be changed depending on the type of information to be predicted. For example, the feature amount may be changed when the prediction target is the number of passersby and when the prediction target is the number of sightings. A trained model may be generated for each type of information, or a trained model that predicts multiple types of information may be generated by providing multiple types of information as correct answer data and performing training. For example, a trained model that infers the number of passersby and the number of sightings may be generated by including both the number of passersby and the number of sightings as correct answer data.

[0092] A trained model is generated for each advertising medium 3, but if there are advertising media 3 with similar surrounding conditions, specifications, etc., these may be considered as one group and a trained model may be generated for each group.

[0093] Furthermore, when predicting information for each attribute, such as the number of passersby for each attribute, a trained model that outputs a predicted value for each attribute may be generated by including the attribute in the feature, or a trained model that outputs a predicted value for each attribute may be generated by training using information for each attribute as correct answer data. The feature and correct answer data described above are merely examples, and the feature and correct answer data are not limited to the above examples.

[0094] The machine learning algorithm is not limited to neural networks, but may be other algorithms such as support vector machines. Furthermore, the machine learning used to generate the trained model is not limited to supervised learning, but may be reinforcement learning or the like.

[0095] The trained model may be generated by the prediction unit 18, or may be generated by a model generation unit (not shown) provided in the evaluation support device 1b. Alternatively, a learning device that generates the trained model may be provided separately from the evaluation support device 1b, and the trained model generated by the learning device may be used by the prediction unit 18. The trained model may be stored in the prediction unit 18 or in the information storage unit 14.

[0096] In addition to the prediction results described above, the prediction unit 18 may also generate creative samples, which are advertisement sample images simulating advertisements to be displayed on the advertising medium 3, and output the generated creative samples to the presentation unit 16, which then presents the creative samples. For example, the service user may specify at least one of the following conditions for the creative sample: the type of industry of the advertisement, the type of product in the advertisement, an image of the product, the target attributes of the advertisement, and design preferences. The prediction unit 18 may then generate the creative samples based on these conditions. Attributes targeted by the advertisement include, but are not limited to, at least one of gender, age, occupation, annual income, assets, place of residence, nationality, family structure, educational background, occupation, hobbies and interests, lifestyle habits, and health status. For example, if young men are targeted by the advertisement, attributes such as male gender and teens to twenties may be specified as target attributes.

[0097] For example, a sample image may be created in advance for each condition and stored in the information storage unit 14, and the prediction unit 18 may select a sample image according to the condition from the stored sample images and use the selected sample image as a creative sample. Alternatively, the creative sample may be generated by machine learning. Furthermore, part images that will be part of the creative sample, such as background images, may be stored in advance in the information storage unit 14, and the prediction unit 18 may generate a creative sample by superimposing an image of a product input as a condition on a part image selected according to the condition. The method for generating a creative sample may be any method and is not limited to the above-described example.

[0098] Furthermore, the presentation unit 16 may generate a simulation image (simulation image) simulating a state in which an advertisement is displayed on the advertising medium 3 by superimposing a creative sample on an area of ​​an image corresponding to the advertising medium 3 based on the image including the advertising medium 3, and output the simulation image to the presentation unit 16, which may then present the simulation image. The prediction unit 18 may generate a simulation image by superimposing an image showing the viewable range and a prediction result on an image of the periphery of the advertising medium 3. That is, the prediction unit 18 may generate a creative sample simulating an advertisement displayed on the advertising medium 3 based on specified conditions, and generate a simulation image by superimposing the creative sample and an image showing the prediction result on an image including the advertising medium 3. The image including the advertising medium 3 is an image of the periphery of the advertising medium 3, and may be photographed for each advertising medium 3 and stored in the information storage unit 14 as medium information, or may be generated based on sensor information, 3D map data, or the like.

[0099] FIG. 14 is a diagram illustrating an example of a simulation image according to the present embodiment. In the example illustrated in FIG. 14, a creative sample image 300 is displayed in the area of ​​the simulation image corresponding to the advertising medium 3. The hatched area in FIG. 14 is a two-dimensional projection of the viewable range. Circles in FIG. 14 represent people, double circles represent VACs, black hatched circles (including double circles) represent OTCs, and open circles represent OTSs excluding OTCs. In this manner, the predicted numbers of VACs, OTCs, and OTSs may be displayed as images. The positions of the VACs, OTCs, and OTSs displayed in the simulation image may be determined randomly or according to predetermined rules within the viewable range based on the number of VACs, OTCs, and OTSs. Displaying a simulation image such as that illustrated in FIG. 14 allows service users to easily understand the situation when placing an advertisement on the advertising medium 3.

[0100] 12 shows an example in which the evaluation support device 1b includes the prediction unit 18, but the present invention is not limited to this, and the evaluation support device 1b may not include the prediction unit 18 and may not perform prediction or generate a simulation image. Furthermore, the evaluation support device 1b may include an image generation unit that generates a creative sample instead of the prediction unit 18 and superimposes it on an image of the periphery of the advertising medium 3 to generate a simulation image, and the presentation unit 16 may present the simulation image generated by the image generation unit.

[0101] The evaluation support device 1b of this embodiment is realized, for example, by the computer system illustrated in FIG. 7 , similar to the evaluation support device 1 of the first embodiment. The prediction unit 18 illustrated in FIG. 12 is realized by the control unit 101 illustrated in FIG. 7 executing a computer program stored in the storage unit 103 illustrated in FIG. 7 . The storage unit 103 illustrated in FIG. 7 is also used to realize the prediction unit 18. The communication unit 105 illustrated in FIG. 7 may also be used to realize the prediction unit 18. The reception unit 17 illustrated in FIG. 12 is realized by at least one of the input unit 102 and the communication unit 105 illustrated in FIG. 7. The evaluation support device 1b may be realized by multiple computer systems. Furthermore, for example, the evaluation support device 1b may be realized by a cloud computer system.

[0102] As described above, in this embodiment, the information stored in the information storage unit 14 is presented to the service user based on the service user's specification. This provides the same effects as in the first embodiment, and allows the service user to check the desired information. Furthermore, by the evaluation support device 1b displaying prediction results, simulation images, etc., the service user can easily understand the situation assuming that he or she places an advertisement on the advertising medium 3, and can support the consideration of placing an advertisement.

[0103] In the above example, the reception unit 17 and the prediction unit 18 are added to the evaluation support device 1 of embodiment 1, but this is not limiting. The operation of this embodiment may be performed by adding the reception unit 17 and the prediction unit 18 to the evaluation support device 1a described in embodiment 2 or the evaluation support device 1 described in embodiment 3.

[0104] Fifth Embodiment Fig. 15 is a diagram showing an example of the configuration of an evaluation support system according to a fifth embodiment. An evaluation support system 100c according to this embodiment includes an evaluation support device 1c and an advertising medium 3. The advertising medium 3 is the same as that of the first embodiment. The evaluation support device 1c is the same as the evaluation support device 1 of the first embodiment, except that a receiving unit 17 and a proposal information generating unit 19 are added. Components having the same functions as those of the first embodiment are assigned the same reference numerals as those of the first embodiment, and redundant explanations will be omitted. Below, differences from the first embodiment will be mainly explained.

[0105] The reception unit 17 receives input from the service user, similar to the reception unit 17 in embodiment 4. In this embodiment, the reception unit 17 receives input of desired conditions related to advertisements from the service user and outputs the received desired conditions to the proposal information generation unit 19. The presentation unit 16 may present a screen for receiving the desired conditions to the service user, and the reception unit 17 may receive the input of the desired conditions by receiving the selection result.

[0106] FIG. 16 is a diagram illustrating an example of a reception screen for accepting input of desired conditions according to the present embodiment. In the example illustrated in FIG. 16 , the desired conditions include the advertisement period, budget (advertising budget), gender, age group, annual income, asset amount (assets), the desired area (area) for installation of the advertising medium 3, the number of passersby, the number of views (number of viewers), the cost per view, residence, place of employment, nationality, family structure, occupation, educational background, hobbies, tastes / lifestyle, and health condition. Note that gender, age group, annual income, asset amount, residence, place of employment, nationality, family structure, occupation, educational background, hobbies, tastes / lifestyle, and health condition are attributes of general users targeted by the advertisement. The desired conditions illustrated in FIG. 16 are merely exemplary, and the desired conditions may be the advertisement period, budget (advertising budget), gender, and age group; the desired conditions are not limited to the example illustrated in FIG. 16 . Furthermore, the input method for the desired conditions is not limited to the example illustrated in FIG. 16 .

[0107] The proposal information generation unit 19 generates one or more plans (submission plans) including information about advertising media 3 that match the desired conditions, and generates proposal information including the generated one or more submission plans. In detail, the proposal information generation unit 19 determines advertising media 3 to be proposed to the service user for use by searching for medium information stored in the information storage unit 14 based on the desired conditions, determines one or more submission plans including information indicating the determined advertising media 3, and generates proposal information indicating the determined submission plans. Note that multiple advertising media 3 may be combined into one plan.

[0108] FIG. 17 is a diagram showing an example of medium information according to the present embodiment. Like the medium information according to the first embodiment, the medium information according to the present embodiment includes information such as the identification information of the advertising medium, the installation location, the advertising price, the number of views, and the evaluation value. In the present embodiment, the medium information stores information used to select advertising media 3 according to desired conditions. For example, if the desired conditions include gender, the medium information may include a gender ratio (gender composition) such as the male-to-female ratio, or may include the number of views by gender, the number of passersby, and the like. Information about these attributes may be estimated based on sensor information, or may be obtained by conducting a questionnaire asking about attributes as in the second embodiment, or may be obtained from a device that provides analysis results of people flow information, such as the people flow information providing device 6 described in the second embodiment.

[0109] The proposal information generation unit 19 refers to the medium information based on the desired conditions, selects advertising media 3 that satisfy the desired conditions, and determines an advertising plan that includes the use of the selected advertising media 3. The proposal information generation unit 19 selects advertising media 3 whose desired conditions, for example, advertising price, area, cost per view, and number of views, satisfy the desired conditions, and selects from the selected advertising media 3 advertising media 3 that will increase the number of views corresponding to the target attributes specified as the desired conditions, depending on the number of views for each attribute. In determining the advertising plan, a priority may be set for each item constituting the desired conditions, and the proposal information generation unit 19 may determine the advertising plan using the priority. The priority may also be specified by the service user. Note that the method of determining the advertising plan in the proposal information generation unit 19 is not limited to this. The proposal information generation unit 19 generates proposal information including the advertising plan and outputs the generated proposal information to the presentation unit 16. The presentation unit 16 presents the proposal information. The proposal information may include multiple advertising plans.

[0110] The advertising plan includes at least information indicating the advertising medium 3 to be used (identification information of the advertising medium 3). The identification information of the advertising medium 3 is, for example, but not limited to, the name of the advertising medium 3 (advertising medium name). The advertising plan may include the number of views, the number of passersby, the advertising price, the evaluation value, etc. corresponding to the advertising medium 3. Furthermore, the advertising plan may include not only information extracted from the medium information but also information determined based on desired conditions. For example, the proposal information generation unit 19 may use at least a portion of the desired conditions to determine the optimal time period for displaying the advertisement, an outline of the advertisement to be displayed (creative outline), etc., and include the determined information in the advertising plan. Furthermore, the proposal information generation unit 19 may determine a particularly recommended plan, and the presentation unit 16 may present it in a manner that indicates that it is a recommended plan. For example, criteria for determining a recommended plan are set in advance, and the proposal information generation unit 19 determines the recommended plan based on the criteria.

[0111] The optimal time period is a time period when there is a large flow of people who are the target of the advertisement, and is determined, for example, based on information indicating the target of the advertisement and people flow data (including information such as the gender ratio for each time, day of the week, and date, age group, and annual income). Alternatively, the optimal time period may be determined based on information indicating the target of the advertisement and age group and gender ratio acquired by a camera, sensor, etc. The information indicating the target of the advertisement may be specified by the service user, or may be determined by the proposal information generation unit 19 based on the product targeted by the advertisement. For example, if the product targeted by the advertisement is cosmetics for young men, the optimal time period would be a time period when many young men (e.g., those in their 30s or younger) pass by.

[0112] The proposal information generation unit 19 may perform the above-described processing by regarding the number of views, evaluation values, etc. during the advertising period under the desired conditions as equivalent to the number of views and evaluation values ​​stored in the medium information. For example, if a future year is specified as the advertising period, the proposal information generation unit 19 may perform the above-described processing by regarding the number of views, evaluation values, etc. corresponding to the most recent year stored in the medium information as the number of views, evaluation values, etc. corresponding to the advertising period. Alternatively, as in the fourth embodiment, the evaluation support device 1c may include a prediction unit 18, which predicts the number of views, evaluation values, etc. corresponding to the advertising period, and the proposal information generation unit 19 may generate an advertising plan using the prediction result by the prediction unit 18.

[0113] FIG. 18 is a diagram illustrating an example of a display screen for proposed information according to the present embodiment. In the example illustrated in FIG. 18, multiple advertising plans are included in the proposed information. In the example illustrated in FIG. 18, the advertising plan includes the advertising period, optimal time slot, advertising medium name, creative summary, expected number of viewers, advertising price, and cost per view. The items included in the advertising plan are not limited to the example illustrated in FIG. 18. When a recommended plan is determined, the recommended plan among the advertising plans illustrated in FIG. 18 may be marked or marked with text indicating that it is a recommended plan, or may be highlighted, for example, in a different color from the other plans. In the example illustrated in FIG. 18, a button 400 labeled "Details" is displayed at the right end of the row corresponding to each advertising plan. When the service user presses the button 400, the advertising plan in the row corresponding to the button 400 is selected, and detailed information about the advertising medium 3 corresponding to the selected advertising plan is displayed. Note that FIG. 18 is merely an example, and the display method, displayed items, and layout of the proposed information are not limited to this example. Furthermore, the button 400 for displaying detailed information does not necessarily have to be displayed.

[0114] Additionally, a map showing the installation locations of the proposed advertising media 3 may be displayed together with the proposed information. Fig. 19 is a diagram showing an example of a map showing the installation locations of the proposed advertising media 3 in this embodiment. In the example shown in Fig. 19, the installation locations of the advertising media 3 are indicated by triangles, and a black triangle indicates the installation location of the advertising medium 3 proposed in the proposal information. For example, detailed information about the selected advertising medium 3 may be displayed when the service user selects a triangle.

[0115] FIG. 20 is a diagram showing an example of a display screen for detailed information in this embodiment. Similar to the fourth embodiment, FIG. 20 shows an example in which the evaluation support device 1c includes a prediction unit 18, and similar to the fourth embodiment, a simulation image and various pieces of information related to the advertising medium 3 are displayed as detailed information. A creative sample in the simulation image (selected simulated image) corresponding to the selected advertising plan is generated similar to the fourth embodiment based on the attributes in the desired conditions. The display screen for detailed information may include only the number of views, evaluation values, etc., or may include only the simulation image. The display screen for detailed information is not limited to the example shown in FIG. 20.

[0116] The evaluation support device 1c of this embodiment is realized, for example, by the computer system illustrated in FIG. 7, similar to the evaluation support device 1 of embodiment 1. The proposal information generation unit 19 illustrated in FIG. 15 is realized by the control unit 101 illustrated in FIG. 7 executing a computer program stored in the storage unit 103 illustrated in FIG. 7. The storage unit 103 illustrated in FIG. 7 is also used to realize the proposal information generation unit 19. The evaluation support device 1c may be realized by multiple computer systems. Furthermore, for example, the evaluation support device 1c may be realized by a cloud computer system.

[0117] As described above, in this embodiment, the advertising plan to be proposed is determined based on the desired conditions specified by the service user, and the determined advertising plan is presented to the service user. This provides the same effects as in the first embodiment, and also makes it possible to propose advertising media 3 that meet the user's wishes.

[0118] In the above example, the reception unit 17 and the proposal information generation unit 19 are added to the evaluation support device 1 of embodiment 1, but this is not limiting. The operation of this embodiment may be performed by adding the proposal information generation unit 19 to the evaluation support device 1b described in embodiment 4 as described above. The operation of this embodiment may be performed by adding the reception unit 17 and the proposal information generation unit 19 to the evaluation support device 1a described in embodiment 2 or the evaluation support device 1 described in embodiment 3. Alternatively, the operation of this embodiment may be performed by adding the reception unit 17 and the prediction unit 18 described in embodiment 4 and the proposal information generation unit 19 described in this embodiment to the evaluation support device 1a described in embodiment 2 or the evaluation support device 1 described in embodiment 3.

[0119] The configurations shown in the above embodiments are merely examples, and may be combined with other known technologies, or different embodiments may be combined with each other. It is also possible to omit or modify parts of the configurations as long as they do not deviate from the gist of the invention.

[0120] Various aspects of the present disclosure are summarized below as appendices.

[0121] (Supplementary Note 1) An evaluation support device comprising: a people flow information acquisition unit that acquires people flow information indicating the flow of people around an advertising medium; a range acquisition unit that acquires a viewable range that is a range within which the advertising medium is viewable and is defined as three-dimensional data; and a view number calculation unit that calculates a view number, which is the number of people who view the advertising medium, using the viewable range and the people flow information. (Supplementary Note 2) The evaluation support device according to Supplementary Note 1, wherein the viewable range is determined based on at least one of three-dimensional map data and three-dimensional measurement data. (Supplementary Note 3) The evaluation support device according to Supplementary Note 1 or 2, wherein the viewable range is determined taking obstacles into consideration. (Supplementary Note 4) The evaluation support device according to any one of Supplements 1 to 3, wherein the people flow information is sensor information acquired by one or more sensors that can detect people present in the viewable range. (Supplementary Note 5) The evaluation support device according to Supplementary Note 4, wherein the view count calculation unit comprises: a gaze estimation unit that identifies people present in the viewable range using the viewable range and the sensor information and estimates the gazes of the identified people; and a counting unit that counts the number of gazes directed at the advertising medium among the gazes estimated by the gaze estimation unit and calculates the view count based on the counting result. (Supplementary Note 6) The evaluation support device according to Supplementary Note 5, wherein the counting unit calculates the view count by multiplying the counting result by a predetermined visibility rate. (Supplementary Note 7) The evaluation support device according to Supplementary Note 6, wherein the visibility rate is calculated based on location information of terminal devices carried by passersby who passed around the advertising medium and response information input by the passersby, the response information including information indicating whether the advertising medium was viewed.(Supplementary Note 8) The evaluation support device according to Supplementary Note 7, wherein the view count calculation unit uses the location information and the viewable range to identify people who passed through the viewable range among the passersby corresponding to the response information, calculates the number of view opportunity holders who were facing the advertising medium using the location information of the identified people, calculates a number of view responses which is the number of response information indicating that the advertising medium was viewed among the response information corresponding to the view opportunity holders, and calculates the view rate based on the number of view opportunity holders and the number of view responses. (Supplementary Note 9) The evaluation support device according to Supplementary Note 1, wherein the people flow information includes information indicating the number of passersby for each movement route. (Supplementary Note 10) The evaluation support device according to any one of Supplements 1 to 9, wherein the viewable range is determined based on at least one of brightness, viewing angle, and curvature information indicating a shape of screen curvature of the advertising medium. (Supplementary Note 11) The evaluation support device according to any one of Supplements 1 to 10, further comprising: a presentation unit that presents the number of views. (Supplementary Note 12) The evaluation support device according to Supplementary Note 11, further comprising: a number of passersby that is the number of passersby who passed through the viewable range; information on people flow for each attribute; and a viewer rating calculated based on the number of views. (Supplementary Note 13) The evaluation support device according to Supplementary Note 12, further comprising: a prediction unit that predicts prediction target information that is at least one of the number of views, the number of passersby, the information on people flow for each attribute, and the viewer rating, wherein the presentation unit presents a prediction result by the prediction unit. (Supplementary Note 14) The evaluation support device according to Supplementary Note 13, further comprising: a prediction unit that predicts prediction target information that is at least one of the number of views, the number of passersby, the information on people flow for each attribute, and the viewer rating, wherein the presentation unit presents a prediction result by the prediction unit.(Supplementary Note 15) The evaluation support device according to Supplementary Note 13, comprising: a reception unit that receives input of desired conditions related to advertising, and a proposal information generation unit that generates one or more advertising plans including information on the advertising media that suit the desired conditions based on the desired conditions, and generates proposal information including the generated one or more advertising plans, wherein the presentation unit displays the proposal information. (Supplementary Note 16) The evaluation support device according to Supplementary Note 15, wherein the reception unit receives a selection of the advertising plan from the advertising plans included in the proposal information, and the presentation unit presents at least one of the number of passersby, information on people flow by attribute, and the audience rating corresponding to the selected advertising plan. and a display unit configured to display the selected advertising medium based on the display target information, the ... (Appendix 19) An evaluation support method in an evaluation support device, comprising: a step of acquiring people flow information indicating the flow of people around an advertising medium; a step of acquiring a viewable range, which is the range within which the advertising medium is visible and is defined as three-dimensional data; and a step of calculating a view count, which is the number of people who viewed the advertising medium, using the viewable range and the people flow information.(Appendix 20) A program that causes a computer system to execute the steps of: acquiring people flow information indicating the flow of people around an advertising medium; acquiring a viewable range that is the range within which the advertising medium is visible and is defined as three-dimensional data; and calculating a view count, which is the number of people who viewed the advertising medium, using the viewable range and the people flow information.

[0122] 1, 1a, 1b, 1c Evaluation support device, 2 Sensor, 3 Advertising medium, 4 Building, 5 Planting, 6 People flow information providing device, 7 Terminal device, 11 Range acquisition unit, 12, 12a View count calculation unit, 13 Evaluation unit, 14 Information storage unit, 15 People flow information acquisition unit, 16 Presentation unit, 17 Reception unit, 18 Prediction unit, 19 Proposal information generation unit, 100, 100a, 100b, 100c Evaluation support system, 121 Gaze estimation unit, 122 Counting unit.

Claims

1. An evaluation support device comprising: a people flow information acquisition unit that acquires people flow information indicating the flow of people around an advertising medium; a range acquisition unit that acquires a viewable range that is the range within which the advertising medium is visible and is defined as three-dimensional data; and a view number calculation unit that uses the viewable range and the people flow information to calculate the view number, which is the number of people who viewed the advertising medium.

2. The evaluation support device according to claim 1, wherein the visible range is determined based on at least one of three-dimensional map data and three-dimensional measurement data.

3. The evaluation support device according to claim 1 or 2, characterized in that the visible range is determined taking into consideration obstacles.

4. An evaluation support device described in any one of claims 1 to 3, characterized in that the people flow information is sensor information obtained by one or more sensors capable of detecting people present within the visible range.

5. The evaluation support device described in claim 4, characterized in that the view count calculation unit comprises: a gaze estimation unit that identifies people present in the viewable range using the viewable range and the sensor information and estimates the gaze of the identified people; and a counting unit that counts the number of gazes directed at the advertising medium among the gazes estimated by the gaze estimation unit and calculates the view count based on the counting result.

6. The evaluation support device according to claim 5, wherein the counting unit calculates the number of views by multiplying the counting result by a predetermined visibility rate.

7. The evaluation support device described in claim 6, characterized in that the visibility rate is calculated based on location information of a terminal device carried by a passerby who passed near the advertising medium and response information entered by the passerby, including information indicating whether or not the advertising medium was viewed.

8. The evaluation support device described in claim 7, characterized in that the view count calculation unit uses the location information and the viewable range to identify people who passed through the viewable range among the passersby corresponding to the response information, calculates the number of view opportunity holders who were looking at the advertising medium using the location information of the identified people, calculates the number of view responses which is the number of response information among the response information corresponding to the view opportunity holders that indicates that they viewed the advertising medium, and calculates the view rate based on the number of view opportunity holders and the number of view responses.

9. The evaluation support device according to claim 1, wherein the people flow information includes information indicating the number of passersby for each travel route.

10. An evaluation support device as described in any one of claims 1 to 9, characterized in that the visible range is determined based on at least one of the brightness, viewing angle, and curvature information indicating the shape of the screen curvature of the advertising medium.

11. The evaluation support device according to any one of claims 1 to 10, further comprising: a presentation unit that presents the number of views.

12. The evaluation support device described in claim 11, characterized in that the presentation unit further presents at least one of the number of pedestrians, which is the number of pedestrians who passed through the visible range, information on people flow by attribute, and an audience rating calculated based on the number of views.

13. The evaluation support device described in claim 12, further comprising a prediction unit that predicts the target information to be predicted, which is at least one of the number of viewers, the number of passersby, information on the flow of people for each attribute, and the audience rating, and wherein the presentation unit presents the prediction results by the prediction unit.

14. The evaluation support device described in claim 13, characterized in that the prediction unit generates an advertising sample image that simulates an advertisement to be displayed on the advertising medium based on specified conditions, and generates a simulated image by superimposing the advertising sample image and an image showing the prediction result on an image including the advertising medium, and the presentation unit presents the simulated image.

15. An evaluation support device as described in claim 13, characterized in that it comprises: a reception unit that receives input of desired conditions related to advertising; and a proposal information generation unit that generates one or more advertising plans including information about the advertising media that suit the desired conditions based on the desired conditions, and generates proposal information including the one or more generated advertising plans, wherein the presentation unit displays the proposal information.

16. The evaluation support device described in claim 15, characterized in that the reception unit receives a selection of an advertising plan from among the advertising plans included in the proposal information, and the presentation unit presents at least one of the number of passersby corresponding to the selected advertising plan, information regarding people flow by attribute, and the audience rating.

17. The evaluation support device described in claim 16, characterized in that when the reception unit receives the selection of the advertising plan, the prediction unit predicts the prediction target information corresponding to the selected advertising plan, generates an advertising sample image simulating the advertisement based on the desired conditions, and generates a selected mock image corresponding to the selected advertising plan by superimposing the generated advertising sample image and an image showing the prediction result corresponding to the selected advertising plan on an image of the advertising medium corresponding to the selected advertising plan, and the presentation unit presents the selected mock image.

18. An evaluation support system comprising: an advertising medium; and an evaluation support device that supports evaluation of the advertising medium, wherein the evaluation support device comprises: a people flow information acquisition unit that acquires people flow information indicating the flow of people around the advertising medium; a range acquisition unit that acquires a viewable range that is the range within which the advertising medium is viewable and is defined as three-dimensional data; and a view number calculation unit that uses the viewable range and the people flow information to calculate a view number, which is the number of people who view the advertising medium.

19. An evaluation support method in an evaluation support device, comprising the steps of: acquiring people flow information indicating the flow of people around advertising media; acquiring a viewable range, which is the range within which the advertising media is visible and is defined as three-dimensional data; and using the viewable range and the people flow information, calculating the number of views, which is the number of people who viewed the advertising media.

20. A program that causes a computer system to execute the following steps: acquiring people flow information indicating the flow of people around an advertising medium; acquiring a viewable range that is the range within which the advertising medium is visible and is defined as three-dimensional data; and calculating the number of views, which is the number of people who viewed the advertising medium, using the viewable range and the people flow information.

Images