Patent Application
20180225704
The present invention relates to an influence measurement device and an influence measurement method for measuring an influence of a person or an object (an influencer) exerting a great influence on other people on internet media or the like.
This application is based upon and claims the benefit of priority from the Japanese Patent Application No. 2015-169784 filed on Aug. 28, 2015, the contents of which are incorporated herein.
On consumer-generated media such as blogs, video sites, and social networking services, key persons whose messages have a great influence on other people in a field of internet marketing in particular is known in recent years as influencers. In addition, thing that is a video display device installed in an outdoor location or at a store and is a computerized sign, poster and the like which presents guidance information, an advertisement or the like to people near the device or passengers is known as digital signage. Further, a system that measures responses of viewers to information presented on digital signage or the like has been developed.
Various techniques relating to influencers and digital signage described above have been developed. PTL 1 discloses a technique of performing person tracking and providing interactive advertisements in an advertising station that provides advertising contents to potential customers. In the technique, a camera captures an image of a potential customer watching a display that provides an advertising content, and an interest level of the potential customer in the advertising content is determined based on a gaze direction and a body pose direction of the potential customer. PTL 2 discloses an influence calculation device and an influence calculation method for calculating an influence of posting information in social media and the like. PTL 3 discloses an advertisement distribution system capable of counting click through rates (CTR) of advertising information in a digital signage system. PTL 4 discloses an influencer extracting device and an influencer extracting method for extracting, as an influencer, a user who has provided posting information widespread on social media. PTL 5 discloses an attention level measurement device and an attention level measurement method capable of measuring levels of attention of people to media information such as advertising media based on an image captured with a camera installed near an advertisement media presentation device.
In the technique described above, the level of interest of the potential customer in advertising information displayed on an immobile entity such as a display and digital signage is determined, and no technique has been achieved that determines the level of interest of the potential customer in information provided by a moving entity such as a person and an advertisement vehicle.
The present invention has been made in order to solve the problem described above and an object of the present invention is to provide an influence measurement device and an influence measurement method for measuring an influence of an influencer on other people.
A first aspect of the present invention is an influence measurement device, the influence measurement device includes:
a measurement unit that measures an influence of a moving first subject on a second subject; and
an output unit that outputs the influence measured by the measurement unit.
A second aspect of the present invention is an influence measurement method, the influence measurement method includes:
measuring an influence of a moving first subject on a second subject; and,
outputting the measured influence.
According to the present invention, an influence of a moving first subject such as a person and an advertisement vehicle on a second subject such as a person can be measured.
Example embodiments of influence measurement device and influence measurement method according to the present invention will be described in detail with reference to the accompanying drawings. First, a network system 3 that implements functions of an influence measurement device 10 according to the present invention will be described.
In the network system 3 in
When the functions of the influence measurement device 10 are implemented by the network system 3, a discount coupon or points may be given to a first subject (for example, an influencer) based on the influence of the first subject on second subjects (for example, persons, animals, etc.). Hereinafter, the first subject is referred to as a “subject to be measured (or an entity to be measured)” of the influence measurement device 10 and the second subject is referred to as a “subject influenced (or a subject)”. With this, the entity to be measured (influencer) can buy a product at a low price depending on the influence on subjects. Further, a company such as a manufacturer or a dealer that provides products bought using such discount coupons or points can benefit because the product sales increase through advertising the products by the entity to be measured to subjects.
The influence measurement device 10 according to a first example embodiment of the present invention will be described.
The sensor 101 detects a physical quantity for extracting a subject that is influenced by an entity to be measured. For example, the sensor 101 is an image sensor which detects light and converts the light to image information.
The sensor information analysis unit 102 applies processing to detection information concerning a physical quantity detected by the sensor 101. For example, when the sensor 101 is the image sensor, the sensor information analysis unit 102 acquires image information from the sensor 101 and performs image analysis such as face recognition on the image information to extract a person.
The entity-to-be-measured identification unit 103 identifies the entity to be measured that is likely to be influencing persons or the like. For example, an association between identification information (ID) of the influence measurement device 10 and identification information (ID) of the entity to be measured is stored in the storage unit 107 in advance. The entity-to-be-measured identification unit 103 acquires the ID of the influence measurement device 10 and reads out the association between the influence measurement device 10 and the entity to be measured from the storage unit 107. The entity-to-be-measured identification unit 103 identifies the sensor 101 provided in the influence measurement device 10 identified by the ID written in the association and identifies an entity equipped with the sensor 101 as the entity to be measured that is likely to be the influencing subjects.
The environment determination unit 104 determines whether the entity to be measured identified by the entity-to-be-measured identification unit 103 is in an environment in which a subject influenced by the entity to be measured exists, i.e. whether the subject which is likely to be influenced by the entity to be measured identified by the entity-to-be-measured identification unit 103 exists. For example, when the sensor information analysis unit 102 has extracted a person from the detection information, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject that is likely to be influenced by the entity to be measured exists. On the other hand, when the sensor information analysis unit 102 does not extract a person, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is likely to be influenced by the entity to be measured exists, i.e. determines that such subject does not exist. When the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists, it can be said that the entity to be measured is likely to influence the subject in the real world. On the other hand, when the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject exists, the subject that is likely to be influenced in the real world by the entity to be measured does not exist and therefore it can be said that the entity to be measured does not need to perform an activity that influence the subject.
The response determination unit 105 determines whether a response from the subject that is influenced by the entity to be measured is received. For example, the response determination unit 105 determines a direction of the face of each person extracted by the sensor information analysis unit 102 using image analysis technique. Specifically, images of a model person's face are captured from various angles (directions), and each of the angles is associated with the face including positional relationships between parts of the face such as the eyes and the mouth at that angle and stored in the storage unit 107 in advance. The response determination unit 105 compares each person's face extracted by the sensor information analysis unit 102 with the faces stored in the storage unit 107 in advance and identifies a face that has the positional relationship between face parts that matches that of the face among the faces stored in the storage unit 107. The response determination unit 105 determines that the angle associated with the identified face is the direction of the face. When the direction of the identified face is toward the sensor 101, the response determination unit 105 determines that the response from the subject is received. The response determination unit 105 determines that the greater the number of persons extracted by the sensor information analysis unit 102 and turning their faces to the sensor 101, the more responses are returned from the subjects. Further, when the direction of the identified face is not turned to the sensor 101, the response determination unit 105 determines that no response from the subject is received.
The influence calculation unit 106 calculates an influence score indicating the influence (i.e. one example of information indicating influence of a moving entity to be measured on subjects) based on the responses from subjects identified by the response determination unit 105. For example, when the number of responses from subjects determined by the response determination unit 105 is 100, the influence calculation unit 106 outputs the influence score of “100” by calculation. When the number of responses from subjects determined by the response determination unit 105 is 123, the influence calculation unit 106 outputs the influence score of “123” by calculation.
The storage unit 107 stores various kinds of information required for processing performed by the influence measurement device 10. For example, the storage unit 107 stores an association between the ID of the influence measurement device 10 and the ID of the entity to be measured.
Next, Processing performed by the influence measurement device 10 according to the first example embodiment will be described with reference to
The entity-to-be-measured identification unit 103 reads out, from the storage unit 107, an association between the influence measurement device 10 and the advertisement vehicle 1 which uses the influence measurement device 10 to determine the influence of the entity to be measured on subjects. Based on the association read out from the storage unit 107, the entity-to-be-measured identification unit 103 identifies the advertisement vehicle 1 equipped with the sensor 101 as the entity to be measured that is likely to be the influencing subjects (step S1).
The advertisement vehicle 1 runs along any route including stopping locations. When the advertisement vehicle 1 starts running along the route, the camera 20 starts to capture images of subjects in front of the advertisement. The sensor 101 detects light and converts the light to image information.
The sensor information analysis unit 102 acquires the image information from the sensor 101 at regular intervals. The sensor information analysis unit 102 performs image analysis such as face recognition on the image information to identify the subject (person) (step S2). The sensor information analysis unit 102 sends a result of the person extraction to the environment determination unit 104 and the response determination unit 105.
The environment determination unit 104 receives the result of the person extraction from the sensor information analysis unit 102. Based on the result of the person extraction, the environment determination unit 104 determines whether the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists (step S3). Specifically, when the sensor information analysis unit 102 extracts a person, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists. On the other hand, when the sensor information analysis unit 102 does not extracts a person, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject exists.
When the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exits (the result of the determination in step S3 is “NO”), the environment determination unit 104 returns the flow to step S2. On the other hand, when the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists (the result of the determination in step S3 is “YES”), the environment determination unit 104 sends a subject presence signal indicating that the entity to be measured is in the environment in which the subject exists to the response determination unit 105.
The response determination unit 105 receives the subject presence signal from the environment determination unit 104. Upon reception of the subject presence signal, the response determination unit 105 determines, based on the person extraction result received from the sensor information analysis unit 102, whether the response from the subject (person) is received (step S4). Specifically, the response determination unit 105 uses an image analysis technique to identify the face direction of each person extracted by the sensor information analysis unit 102. When the identified face direction is toward the sensor 101, the response determination unit 105 determines that the response from the person is received. The response determination unit 105 determines that the greater the number of persons indicated by the person extraction result, turning their faces to the sensor 101, the more responses from the persons. Further, when the identified face direction is not toward the sensor 101, the response determination unit 105 determines that no response from the person is received.
When the response determination unit 105 determines that no response from the subject (person) is received (the result of the determination in step S4 is “NO”), the response determination unit 105 returns the flow to step S2. On the other hand, when the response determination unit 105 determines that the response from the subject (person) is received (the result of the determination in step S4 is “YES”), the response determination unit 105 sends the result of the determination as to the response from the subject to the influence calculation unit 106. The influence calculation unit 106 receives the response determination result from the response determination unit 105. The influence calculation unit 106 calculates the influence score based on the response determination result (step S5). Specifically, the influence calculation unit 106 outputs the number of subject responses indicated by the response determination result as the influence score by calculation. For example, when the number of responses indicated by the response determination result is 100, the influence calculation unit 106 outputs the influence score of “100” by calculation. When the number of responses indicated by the response determination result is 123, the influence calculation unit 106 outputs the influence score of “123” by calculation. The influence calculation unit 106 outputs the influence score to a monitor device such as a display and causes the monitor device to display the influence score (step S6).
Note that an output unit to which the influence calculation unit 106 outputs the influence score is not limited to a monitor device but may be a speaker. In that case, the influence calculation unit 106 outputs the influence score through the speaker as audible sound. In addition, the influence calculation unit 106 may record the influence score on another output unit (for example the storage unit 107). Further, a functional unit other than the influence calculation unit 106 may, for example, cause the influence score recorded on the storage unit 107 to be displayed on a monitor device such as a display. Further, a functional unit other than the influence calculation unit 106 may, for example, cause the influence score recorded on the storage unit 107 to be output through a speaker as audible sound.
As described above, the entity-to-be-measured identification unit 103 in the influence measurement device 10 identifies the entity to be measured that is likely to be the influencing subject such as a person. The environment determination unit 104 determines whether the entity to be measured identified by the entity-to-be-measured identification unit 103 is in the environment in which the subject that is influenced by the entity to be measured exists. The response determination unit 105 determines whether the response from the subject is received influenced by the entity to be measured identified by the entity-to-be-measured identification unit 103. Based on the response from the subject determined by the response determination unit 105, the influence calculation unit 106 calculates the influence score indicating the influence on the subjects. The influence calculation unit 106 outputs the influence score to a predetermined output unit. In this way, the influences of various entities to be measured, including moving entities such as persons and advertisement vehicles, on the subjects that exist in surroundings can be measured by the influence measurement device 10.
If functions of the influence measurement device 10 are implemented in a distributed manner in the network system 3 illustrated in
Further, the entity to be measured is not limited to the advertisement vehicle 1 illustrated in
An influence measurement device 10 according to a second example embodiment will be described.
The sensor 101 detects a physical quantity for extracting a subject that is influenced by the entity to be measured. The sensor 101 is, for example, an image sensor that detects light and converts the light to image information.
The sensor information analysis unit 102 performs processing on the detection information indicating the physical quantity detected by the sensor 101. For example, when the sensor 101 is the image sensor, the sensor information analysis unit 102 acquires the image information from the sensor 101 and performs the image analysis such as face recognition on the image information to extract a person.
The entity-to-be-measured identification unit 103 identifies the entity to be measured that is likely to be the influencing the subjects such as persons. For example, the association between the ID of the influence measurement device 10 and the ID of the entity to be measured are stored in the storage unit 107 in advance and the entity-to-be-measured identification unit 103 reads out the association from the storage unit 107 to identify the entity to be measured that is likely to be the influencing subjects (the entity to be measured in which the sensor 101 is provided).
The environment determination unit 104 determines whether the entity to be measured is in an environment in which the subject that is influenced by the entity to be measured exists. For example, when the sensor information analysis unit 102 extracts a person from the detection information from the sensor 101, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists. When the sensor information analysis unit 102 does not extract a person from the detection information, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject exists.
The response determination unit 105 determines whether the response from the subject (person) is received that is influenced by the entity to be measured. For example, the response determination unit 105 determines the direction of the face of each person extracted from the detection information by the sensor information analysis unit 102 using the image analysis technique. When the direction of the face of the person is toward the sensor 101, the response determination unit 105 determines that the response from the person is received. The response determination unit 105 determines that the greater the number of persons extracted by the sensor information analysis unit 102 and turning their faces to the sensor 101, the more responses are returned from the subjects. Further, when the face of the person is not turned to the sensor 101, the response determination unit 105 determines that no response from the person is received.
The influence calculation unit 106 calculates the influence score indicating the influence of the entity to be measured on a person based on responses from persons determined by the response determination unit 105. For example, when the number of responses from persons determined by the response determination unit 105 is 100, the influence calculation unit 106 outputs the influence score of “100” by calculation. When the number of responses from persons determined by the response determination unit 105 is 123, the influence calculation unit 106 outputs the influence score of “123” by calculation.
The storage unit 107 stores various kinds of information required for processing performed by the influence measurement device 10. For example, the storage unit 107 stores the association between the ID of the influence measurement device 10 and the ID of the entity to be measured.
The first communication unit 108 performs wireless communication with the second communication unit 109. For example, the first communication unit 108 sends a result of person extraction from the sensor information analysis unit 102 to the second communication unit 109. The second communication unit 109 receives the person extraction result from the first communication unit 108.
A procedure of processing performed by the influence measurement device 10 according to the second example embodiment will be described next. It is assumed that the second influence measurement device 10b is provided in the advertisement vehicle 1 which is the entity to be measured and the first influence measurement device 10a is provided in a flying object 2 that automatically follows the advertisement vehicle 1, as illustrated in
The procedure of processing performed by the influence measurement device 10 according to the second example embodiment is similar to the procedure of processing performed by the influence measurement device 10 according to the first example embodiment illustrated in
In the second example embodiment, when the advertisement vehicle 1 starts running along the predetermined route, the camera 20 starts to capture images. The flying object 2 follows the advertisement vehicle 1. For example, each of the advertisement vehicle 1 and the flying object 2 includes GPS capability. The flying object 2 acquires position information of each of the flying object 2 and the advertisement vehicle 1 using the GPS capability. The flying object 2 is controlled by a control unit included in the flying object 2 itself so as to follow and fly behind and above the advertisement vehicle 1 a predetermined distance relative to the position of the advertisement vehicle 1 for each time period, indicated by the position information of the advertisement vehicle 1.
The person extraction result of the sensor information analysis unit 102 in step S2 of
As described above, in the influence measurement device 10 according to the second example embodiment, the entity-to-be-measured identification unit 103 identifies the entity to be measured that is likely to be the influencing subjects such as persons. The environment determination unit 104 determines whether the entity to be measured identified by the entity-to-be-measured identification unit 103 is in the environment in which the subject that is influenced by the entity to be measured exits. The response determination unit 105 determines whether the response from the subject that is influenced by the entity to be measured which is identified by the entity-to-be-measured identification unit 103 is received. Based on the responses from the persons determined by the response determination unit 105, the influence calculation unit 106 calculates the influence score indicating the influence of the entity to be measured on the persons. The influence calculation unit 106 outputs the influence score to the output unit (such as a display or a speaker). In this way, the influence measurement device 10 can measure the influences of various entities to be measured, including moving entities such as the persons and the advertisement vehicles, on the subjects that exist in surroundings.
An influence measurement device 10 according to a third example embodiment of the present invention will be described.
The sensor 101 detects the physical quantity for extracting the subject that is influenced by the entity to be measured. The sensor 101 is, for example, the image sensor that detects light and converts the light to image information.
The sensor information analysis unit 102 performs processing on the information indicating the physical quantity detected by the sensor 101. For example, when the sensor 101 is the image sensor, the sensor information analysis unit 102 acquires the image information from the sensor 101 and performs the image analysis such as the face recognition on the image information to extract a person.
The environment determination unit 104 determines whether the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists. For example, when the sensor information analysis unit 102 extracts a person from the detection information from the sensor 101, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists. When the sensor information analysis unit 102 does not extract the person from the detection information, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject exists.
The response determination unit 105 determines whether the response from the subject which is influenced by the entity to be measured is received. For example, the response determination unit 105 determines the direction of the face of each person extracted from the detection information by the sensor information analysis unit 102 using the image analysis technique. The response determination unit 105 draws imaginary straight lines extending in the directions of the faces of a plurality of persons and determines a point at which a greater number of straight lines than a predetermined number intersect each other. When an object exists at the position at which a greater number of straight lines than the predetermine number intersect each other, the response determination unit 105 determines that responses from subjects is received. In this case, the response determination unit 105 determines that the greater the number of intersecting lines, the greater the number of responses from subjects. Further, when no object exists at the point at which a greater number of straight lines than the predetermined number (predetermined threshold) intersect each other, the response determination unit 105 determines that no response from subjects is received. This is determination processing that considers the fact that when the subject is a person and the person pays attention to the entity to be measured, the person turns the face to the entity to be measured.
The influence calculation unit 106 calculates the influence score indicating the influence of the entity to be measured on the subjects based on the response of the subjects determined by the response determination unit 105. For example, when the number of straight lines intersecting each other at a particular point determined by the response determination unit 105 is 100, the influence calculation unit 106 outputs the influence score of “100” by calculation. When the number of straight lines intersecting each other at a particular point determined by the response determination unit 105 is 123, the influence calculation unit 106 outputs the influence score of “123” by calculation.
Based on the responses from the subjects, the entity-to-be-measured identification unit 103 identifies the entity to be measured that is the influencing subjects. For example, the entity-to-be-measured identification unit 103 identifies the object that corresponds to the influence score calculated by the influence calculation unit 106 that is greater than a predetermined threshold as the entity to be measured that is the influencing subjects.
The storage unit 107 stores various kinds of information required for processing performed by the influence measurement device 10. For example, the storage unit 107 stores the threshold used by the response determination unit 105 for determination processing and the threshold used by the entity-to-be-measured identification unit 103 for identification processing.
The first communication unit 108 communicates with the second communication unit 109. For example, the first communication unit 108 sends the result of person extraction from the detection information by the sensor information analysis unit 102 to the second communication unit 109. The second communication unit 109 receives the result of person extraction by the sensor information analysis unit 102 through the first communication unit 108. Further, when the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists, the first communication unit 108 sends the subject-presence signal to the second communication unit 109. The second communication unit 109 receives the subject-presence signal through the first communication unit 108.
A procedure of processing performed by the influence measurement device 10 according to the third example embodiment will be described next.
First, the camera 20 starts capturing images. The sensor 101 converts light detected in a range in which images of a plurality of persons can be captured with the camera 20 provided in the shopping mall to image information.
The sensor information analysis unit 102 acquires the image information from the sensor 101 at regular intervals. The sensor information analysis unit 102 performs the image analysis such as the face recognition on the image information to extract persons (step S1). The sensor information analysis unit 102 sends the person extraction result to the second communication unit 109 through the first communication unit 108. Further, the sensor information analysis unit 102 sends the person extraction result to the environment determination unit 104.
The response determination unit 105 receives the person extraction result through the second communication unit 109. The environment determination unit 104 receives the person extraction result from the sensor information analysis unit 102. Based on the person extraction result, the environment determination unit 104 determines whether the entity to be measured is in the environment in which the subject that is likely to be influenced by the entity to be measured exists (step S2). Specifically, when the sensor information analysis unit 102 extracts a person from the detection information from the sensor 101, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists. On the other hand, when the sensor information analysis unit 102 does not extract a person from the detection information, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject exists.
When the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exits (the result of the determination in step S2 is “NO”), the environment determination unit 104 returns the flow to step S1. On the other hand, when the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject exists (the result of the determination in step S2 is “YES”), the environment determination unit 104 sends the subject presence signal indicating that the entity to be measured is in the environment in which the subject exists to the second communication unit 109 through the first communication unit 108. The response determination unit 105 receives the subject presence signal from the environmental determination unit 104 through the second communication unit 109. When the response determination unit 105 receives the subject presence signal, the response determination unit 105 determines, based on the person extraction result received from the sensor information analysis unit 102, whether the response from the subject is received (step S3). Specifically, the response determination unit 105 determines the direction of the face of each person extracted by the sensor information analysis unit 102 using the image analysis technique. The response determination unit 105 draws the imaginary straight line extending in the direction of the face of each person and identifies the position at which a greater number of straight lines than a predetermined number (a predetermined threshold) intersect each other. The response determination unit 105 then determines that the greater the number of interchanging straight lines, the greater the number of responses from persons. Further, when the number of interchanging lines is less than the predetermined number (the predetermined threshold) or when no object exists at the position at which straight lines intersect each other, the response determination unit 105 determines that no response from persons is received.
As an example, a case where persons A, B, C, D and E exist in a coverage of the camera 20 as illustrated in
When the response determination unit 105 determines that no response from subjects which are influenced by the entity to be measured is received (the result of the determination in step S3 is “NO”), the response determination unit 105 returns the flow to step S1. On the other hand, when the response determination unit 105 determines that the responses from subjects is received (the result of the determination in step 3 is “YES”), the response determination unit 105 sends the result of the determination as to the responses from the subjects to the influence calculation unit 106. The influence calculation unit 106 receives the response determination result from the response determination unit 105. Based on the response determination result, the influence calculation unit 106 calculates the influence score (step S4). Specifically, when the number of straight lines that intersect a particular position determined by the response determination unit 105 is 100, the influence calculation unit 106 outputs the influence score of “100” by calculation. When the number of straight lines that intersect the particular position determined by the response determination unit 105 is 123, the influence calculation unit 106 outputs the influence score of “123” by calculation. In
The entity-to-be-measured identification unit 103 identifies the entity to be measured that is the influencing subject based on the response from the subject. For example, the entity-to-be-measured identification unit 103 identifies the object that corresponds to the influence score calculated by the influence calculation unit 106 that is greater than or equal to the predetermined threshold as the entity to be measured that is the influencing subjects (step S5). The influence calculation unit 106 outputs the influence score to a monitor device such as a display to cause the monitor device to display the influence score (step S6).
As described above, in the influence measurement device 10 according to the third example embodiment, the environment determination unit 104 determines whether the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured. The response determination unit 105 determines whether the response from the subject is received influenced by the entity to be measured. Based on responses from subjects determined by the response determination unit 105, the influence calculation unit 106 calculates the influence score indicating the influence of the entity to be measured on subjects. Based on the influence score calculated by the influence calculation unit 106, the entity-to-be-measured identification unit 103 identifies the entity to be measured that is the influencing subject. The influence calculation unit 106 outputs the influence score to the output unit (for example, a monitor device). In this way, the influence measurement device 10 according to the third example embodiment is capable of measuring influences of various entities to be measured, including moving entities such as persons and advertisement vehicles, on subjects in surroundings.
Note that, in the third example embodiment, the method by which the environment determination unit 104 determines whether the entity to be measured is in the environment in which the subject that is likely to be influenced by the entity to be measured exists is not limited to the determination method described above. For example, the environment determination unit 104 may determine whether the entity to be measured is in the environment in which the subject influenced by the entity to be measured exists based on at least one of the position of the entity to be measured and a time of day. Specifically, the entity to be measured is equipped with a device, such as a GPS device, that is capable of identifying positions. The environment determination unit 104 acquires position information from the device capable of identifying positions. For example, when the entity to be measured is moving in a place where there are many people (i.e. subjects) at any time of day or night, such as Shinjuku or Shibuya in Tokyo, Japan, the environment determination unit 104 determines that the entity to be measured is in the environment in which subjects that are influenced by the entity to be measured exist. On the other hand, when the entity to be measured is moving in the place where there is no person, such as woods or an extensive forest, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists. Note that when the entity to be measured cannot be identified in advance, a device capable of identifying positions may be provided at the sensor 101 of the influence measurement device 10.
Specific examples to which the environment determination unit 104 is applied will be described next. For example, the storage unit 107 stores relationship between each time of day and the number of subjects in a shopping mall in advance. The environment determination unit 104 reads out the relationship between each time of day and the number of subjects in the shopping mall from the storage unit 107. Specifically, the environment determination unit 104 reads out a time from a timer at the timing of determination. The environment determination unit 104 reads out the relationship of the time read out from the timer with the number of subjects from the storage unit 107. In the relationship read out from the storage unit 107, the environment determination unit 104 reads the number of subjects associated with the time read out from the timer. When the number of subjects read out from the storage unit 107 is not zero, the environment determination unit 104 determines that the entity to be measured is in an environment in which a subject that is influenced by the entity to be measured exists. On the other hand, when the number of subjects read from the storage unit 107 is zero, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists.
In another specific example, the entity to be measured is equipped with a device capable of identifying positions such as a GPS device. The storage unit 107 stores relationship between each time of day and the number of subjects at each position in advance. The environment determination unit 104 reads out the relationship between each time of day and the number of subjects at each position from the storage unit 107. Specifically, the environment determination unit 104 acquires position information from the device capable of identifying positions. The environment determination unit 104 reads out a time from a timer at the timing of determination. The environment determination unit 104 reads the relationship that matches the position information from the storage unit 107. The environment determination unit 104 refers to the relationship read out from the storage unit 107 based on the time read out from the timer and the position information to identify the number of subjects that correspond to the time and the position. When the number of subjects that is written in the relationship read out from the storage unit 107 is not zero, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists. On the other hand, when the number of subjects is zero, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists. Note that when the entity to be measured cannot be identified in advance, the device capable of identifying positions may be provided at the sensor 101 of the influence measurement device 10.
In another specific example, the environment determination unit 104 may determine whether the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists, based on a sound state in the surroundings of the entity to be measured. The entity to be measured is equipped with a device that captures sound in the surroundings, such as a microphone. The environment determination unit 104 acquires sound volume information from the device that captures sound in the surroundings of the entity to be measured and, when the sound volume is greater than or equal to a predetermined threshold, determines that the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists. On the other hand, when the sound volume is smaller than the predetermined threshold, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists. Note that when the entity to be measured cannot be identified in advance, the device that captures sound in the surroundings of the entity to be measured may be provided at the sensor 101 of the influence measurement device 10.
In another specific example, the environment determination unit 104 may determine whether the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists based on a communication state in the surroundings of the entity to be measured. In this example, each of the entity to be measured and subjects is equipped with a device capable of short-range communication. A procedure is determined in advance in which when the entity to be measured and the subject start communication, the short-range communication device of the subject sends a communication start notification signal indicating the start of communication to the environment determination unit 104. When the environment determination unit 104 receives the communication start notification signal, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists. On the other hand, when the environment determination unit 104 does not receive the communication start notification signal, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists. Note that when the entity to be measured cannot be identified in advance, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists when there is a short-range communication device that is concurrently communicating with a greater number of short-range communication devices than a predetermined threshold. On the other hand, when there is no short-range communication device that is concurrently communicating with a greater number of short-range communication devices than the predetermined threshold, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists.
In another specific example, the environment determination unit 104 may determine whether the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists based on whether a device that is capable of distributing information concerning the entity to be measured exists in the vicinity of the entity to be measured. For example, a device capable of distributing information concerning the entity to be measured distributes a “button image” to be pressed when one is favorably impressed by the entity to be measured to subjects by short-range communication. The subjects are equipped with a device capable of short-range communication. A procedure is determined in advance in which when the short-range communication device of the subject receives the “button image”, the short-range communication device sends a reception notification signal notifying the reception of the “button image” to the environment determination unit 104. When the environment determination unit 104 receives the reception notification signal, the environment determination unit 104 determines that the entity to be measured is in the environment in which the subject that is influenced by the entity to be measured exists. On the other hand, when the environment determination unit 104 does not receive the reception notification signal, the environment determination unit 104 determines that the entity to be measured is not in the environment in which the subject that is influenced by the entity to be measured exists.
In the example described above, the method for the response determination unit 105 to determine whether the response from the subject which is influenced by the entity to be measured is received is not limited to the determination method described above. For example, the response determination unit 105 may determine whether the response from the subject is received based on a communication state in the surroundings of the entity to be measured. Alternatively, the response determination unit 105 may determine whether the response from the subject is received based on a sound state in the surroundings of the entity to be measured. Specifically, the entity to be measured is equipped with a device, such as a microphone, that captures sound in the surroundings. The response determination unit 105 acquires a sound volume from the device that captures sound in the surroundings of the entity to be measured and, when the sound volume is greater than or equal to a predetermined threshold, determines that the response from the subject which is influenced by the entity to be measured is received. On the other hand, when the sound volume is smaller than the predetermined threshold, the response determination unit 105 determines that no response from the subject is received. Note that when the entity to be measured cannot be identified in advance, a device that captures sound in the surroundings of the entity to be measured may be provided at the sensor 101 of the influence measurement device 10.
Further, the response determination unit 105 may determine whether the response from the subject is received based on the communication state in the surroundings of the entity to be measured. In this case, each of the entity to be measured and the subjects is equipped with the device that is capable of short-range communication. A procedure is determined in advance in which when the entity to be measured and the subject start communication, the short-range communication device of the subject sends the communication start notification signal notifying the start of communication to the response determination unit 105. When the response determination unit 105 receives the communication start notification signal, the response determination unit 105 determines that the response from the subject which is influenced by the entity to be measured is received. On the other hand, when the response determination unit 105 does not receive the communication start notification signal, the response determination unit 105 determines that no response from the subject is received. Note that in the case where the entity to be measured cannot be identified in advance, the response determination unit 105 determines that the response from the subject is received when there is a short-range communication device that is concurrently communicating with a greater number of short-range communication devices than a predetermined threshold. On the other hand, when there is no short-range communication device that is concurrently communicating with a greater number of short-range communication devices than the predetermined threshold, the response determination unit 105 determines that no response from the subject is received.
Note that as in the response determination unit 105 in the third example embodiment, the response determination units 105 according to the first example embodiment and the second example embodiment may determine whether the response from the subject is received based on the subject turning the face to the entity to be measured when the subject pays attention to the entity to be measured.
A minimum configuration of an influence measurement device 10 according to the present invention will be described next.
Note that the storage unit 107 in the examples described above may be provided anywhere within a range in which desired information can be sent and received. Further, a plurality of storage units 107 may be provided and data may be stored in the storage units 107 in a distributed manner within a range in which desired information can be sent and received.
Note that the order of performance of steps in the procedures of the processing in the examples described above may be changed as appropriate as long as the functions of the influence measurement device 10 according to the present invention can be achieved.
The influence measurement device 10 according to the present invention includes a computer system therein. Any of the procedures of processing described above is stored in a computer-readable storage medium in the form of a program. Any of the processing procedures described above is performed by a computer reading the program from the storage medium and executing the program. Here, the computer-readable storage medium is a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory or the like. The computer program may be delivered to a computer through a communication line and the computer may execute the program.
The program described above may be a program that implements some of the functions of the influence measurement device 10. Further, the program may be a program that can implement the functions of the influence measurement device 10 in combination with a program already recorded on a computer system, i.e. a so-called differential program (a differential file).
Lastly, the present invention is not limited to the examples and the specific examples described above and encompasses design changes and modifications within the scope of the present invention defined by the attached claims.
The present invention related to the influence measurement device and the influence measurement method is applied to measure the influence of advertising media (such as persons or advertisement vehicles) on subjects (such as persons), and then may be applied to measure the influence of an information source other than advertising media on the subjects.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2015-169784 | Aug 2015 | JP | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2016/074635 | 8/24/2016 | WO | 00 |
