Image display device, image display method, and program

Abstract

An image display device (10) comprises an image data acquisition unit (111), a specifying unit (112), an estimation unit (113), an image-of-interest detection unit (114), and an output unit (115). The image data acquisition unit (111) acquires a plurality of pieces of image data from a camera. The specifying unit (112) specifies an individual from the image data. The estimation unit (113) estimates the likelihood that the individual specified from the image data develops infectious disease symptoms. The image-of-interest detection unit (114) detects, on the basis of the estimation results, an image of interest which includes: the individual of interest who may develop the symptoms; and surrounding individuals who surround the individual of interest. The output unit (115) extracts and displays a series of image groups including the image of interest.

Description

Technical Field

[0001] The present invention relates to an image display device, an image display system, an image display method, and a non-transitory computer-readable medium.

Background Art

[0002] There is an increasing demand to grasp the infection risk of infectious diseases among a plurality of people existing in a predetermined area. As a means to realize such a demand, for example, it is considered effective to estimate the physical state of a person and visually recognize the contact state between people in the area where the person exists. For this purpose, there is a need for a technology to identify a person showing symptoms of an infectious disease and find the possibility that such a person has had close contact with surrounding people.

[0003] In relation to such a technology, for example, Patent Document 1 discloses a system for grasping changes in the physical state of a user. Such a technology searches for similar measurement data similar to the latest measurement data among the past measurement data of other users when the past measurement data of a specific user does not fall within a predetermined range, and estimates a disease or symptom that the user may suffer from in the near future.

[0004] Further, Patent Document 2 describes a nosocomial infection influence range browsing system. This system includes a round route device, a round log recording terminal, a log analysis unit, and a map display unit. The round route device is arranged in a medical facility, and the round log recording terminal records the round information of a person from the communication record with the round route device. The log analysis unit analyzes the round information based on a preset analysis rule to calculate the infection risk degree of a person. The map display unit displays the infection influence range in the medical facility based on the preset map information, the movement route of the person obtained from the round information, and the infection risk degree of the person.

[0005] Patent Document 3 discloses a home therapy patient rescue system having a monitoring center connected to medical devices used by home therapy patients through communication means and a database for storing personal information of home therapy patients. The monitoring center detects the state of medical devices used by home therapy patients at predetermined intervals, searches the database in the event of a disaster, and creates a list of rescue priorities in order of severity.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0007] However, even if the above-mentioned technologies are combined, it is difficult to track the movements of all persons showing symptoms of infectious diseases in crowded places.

[0008] The present disclosure has been made in view of such problems, and an object thereof is to provide an image display device or the like that suitably displays a situation with a high infection risk.

Means for Solving the Problems

[0009] An image display device according to an embodiment of the present disclosure includes an image data acquisition unit, an identification unit, an estimation unit, a target image detection unit, and an output unit. The image data acquisition unit acquires a plurality of image data from a camera. The identification unit identifies a person from the image data. The estimation unit estimates the likelihood of a person identified from the image data developing an infectious disease. The target image detection unit detects a target image including a target person having the likelihood of developing the disease and surrounding persons around the target person based on the estimation result. The output unit extracts and displays a series of image groups including the target image.

[0010] A method according to an embodiment of the present disclosure is executed by a computer as follows. The computer acquires a plurality of image data from a camera. The computer identifies a person from the image data. The computer estimates the likelihood of a person identified developing an infectious disease. The computer detects a target image including a target person having the likelihood of developing the disease and surrounding persons around the target person based on the estimation result. The computer extracts a series of image groups including the target image.

[0011] A program according to an embodiment of the present disclosure causes a computer to execute the following steps. The computer acquires a plurality of image data from a camera. The computer identifies a person from the image data. The computer estimates the likelihood of a person identified developing an infectious disease. The computer detects a target image including a target person having the likelihood of developing the disease and surrounding persons around the target person based on the estimation result. The computer extracts a series of image groups including the target image.

Advantages of the Invention

[0012] According to the present disclosure, it is possible to provide an image display device or the like that suitably displays a situation with a high infection risk.

Brief Description of the Drawings

[0013]

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Embodiments for Carrying Out the Invention

[0014] Hereinafter, the present invention will be described through embodiments of the invention, but the invention according to the claims is not limited to the following embodiments. Also, not all of the configurations described in the embodiments are necessarily essential as means for solving the problems. For clarity of explanation, the following description and drawings have been appropriately omitted and simplified. In each drawing, the same elements are denoted by the same reference numerals, and duplicate explanations are omitted as necessary.

[0015] <Embodiment 1> Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram of an image display device 10 according to Embodiment 1. The image display device 10 shown in FIG. 1 is connected to a camera installed indoors or outdoors, acquires image data captured by the camera, and displays an image or a group of images to be noted. The main components of the image display device 10 include an image data acquisition unit 111, a specifying unit 112, an estimating unit 113, a target image detection unit 114, and an output unit 115.

[0016] The image data acquisition unit 111 acquires a plurality of pieces of image data from the camera. The plurality of pieces of image data are image data captured at different times. For example, the camera captures 30 frames of images per second, and supplies the image data corresponding to these captured images to the image data acquisition unit 111. The number of cameras connected to the image data acquisition unit 111 may be one or more. Also, the camera connected to the image data acquisition unit 111 may be fixed to capture a predetermined angle of view, or may be a movable type that performs pan, tilt, or zoom. The image data acquisition unit 111 supplies the image data acquired from the camera to at least the specifying unit 112. Also, the image data acquisition unit 111 appropriately supplies the image data acquired from the camera to other components.

[0017] The specifying unit 112 receives the image data from the image data acquisition unit 111 and specifies a person from the received image data. More specifically, for example, the specifying unit 112 extracts the feature amount of the received image data and detects the feature amount of the person. The specifying unit 112 supplies data (specifying data) related to the specified person to the estimating unit 113.

[0018] The estimation unit 113 receives specific data from the specifying unit 112, and estimates the likelihood of the specified person developing an infectious disease using the received specific data. More specifically, for example, the estimation unit 113 receives the state of a person's body movements as feature data, and detects that the specified person exhibits symptom movements indicating the onset of an infectious disease. Symptom movements related to the occurrence of an infectious disease are, for example, actions such as coughing, sneezing, touching the hip, and touching the chest. The estimation unit 113 estimates whether there is a possibility that the specified person will develop an infectious disease. In this case, the estimation unit 113 may estimate that there is a possibility of developing an infectious disease when the specified person performs a preset action. Alternatively, the estimation unit 113 may estimate whether the likelihood of developing an infectious disease is equal to or greater than a preset threshold from a plurality of actions of the specified person. The estimation unit 113 supplies the result of the above estimation to the attention image detection unit 114.

[0019] The attention image detection unit 114 uses the estimation result received from the estimation unit 113 to detect an image including a person of interest who may have developed an infectious disease from the plurality of image data acquired by the image data acquisition unit 111. Here, the "person of interest" refers to a person estimated by the estimation unit 113 to have a possibility of developing an infectious disease. The attention image detection unit 114 also detects an attention image including the person of interest and surrounding people from the plurality of image data acquired by the image data acquisition unit 111.

[0020] Here, the "surrounding people" refers to, for example, people who are present at a position closer than a preset value to the person of interest. However, the definition of the surrounding people is not limited to the above content. For example, the surrounding people may be people who are closer than a preset value to the person of interest and have been present for a preset period or longer. That is, the surrounding people are people who are present near the person of interest who may develop an infectious disease and who may be infected with the infectious disease from the person of interest. The attention image detection unit 114 determines a situation in which there is a possibility of the infectious disease being transmitted from the person of interest to the surrounding people as a situation with a high infection risk, and detects the captured image as an attention image. When the attention image detection unit 114 detects an attention image, it supplies data related to the attention image to the output unit 115.

[0021] The output unit 115 receives data regarding the target image from the target image detection unit 114, and extracts a series of image groups including the target image from the received data. The output unit 115 extracts, for example, an image group for a preset period including the target image. The preset period is, for example, 5 seconds, 10 seconds, or 30 seconds before and after the target image. In the present disclosure, the "image group" refers to images captured continuously. Therefore, the "image group" may be referred to as a "video". The output unit 115 outputs the extracted image group to a predetermined display device for connection.

[0022] As described above, the configuration of the image display device 10 has been described. With such a configuration, the image display device 10 can detect a person suspected of having developed an infectious disease from the image data acquired from the camera, and extract and display an image group in which there is a possibility that the infectious disease has been transmitted to the people around such a person.

[0023] Next, with reference to FIG. 2, an image display method executed by the image display device 10 will be described. FIG. 2 is a flowchart showing the image display method according to the first embodiment. The flowchart shown in FIG. 2 is started, for example, when the image display device 10 is activated.

[0024] First, the image data acquisition unit 111 acquires a plurality of image data from the camera (step S11). The image data acquisition unit 111 supplies the acquired plurality of image data to at least the specifying unit 112.

[0025] Next, the specifying unit 112 receives the image data from the image data acquisition unit 111, and specifies a person from the received image data (step S12). When the specifying unit 112 specifies a person, it supplies the specifying data to the estimating unit 113.

[0026] Next, the estimating unit 113 uses the specifying data received from the specifying unit 112 to estimate the possibility of the specified person developing an infectious disease (step S13). The estimating unit 113 supplies the result of the estimation to the target image detection unit 114.

[0027] Next, the target image detection unit 114 detects a target image including a target person having a possibility of onset and surrounding persons around the target person from the estimation result received from the estimation unit 113 (step S14). The target image detection unit 114 supplies the detected target image to the output unit 115.

[0028] Next, the output unit 115 extracts a series of image groups including the target image from the target image received from the target image detection unit 114, and outputs the extracted series of image groups to a predetermined display device (step S15).

[0029] The image display device according to the first embodiment has been described above. Note that the image display device 10 has a processor and a storage device as a configuration not shown in the drawings. The storage device included in the image display device 10 includes a storage device including a non-volatile memory such as a flash memory or an SSD (Solid State Drive). In this case, the storage device included in the image display device 10 stores a computer program (hereinafter also simply referred to as a program) for executing the above-described image display method. Further, the processor causes the buffer memory such as a DRAM (Dynamic Random Access Memory) to read the computer program from the storage device, and executes the program.

[0030] Each component of the image display device 10 may be realized by dedicated hardware. Also, some or all of the components may be realized by general-purpose or dedicated circuitry, a processor, etc., or a combination thereof. These may be constituted by a single chip, or may be constituted by a plurality of chips connected via a bus. Some or all of the components of each device may be realized by a combination of the circuitry, etc. described above and a program. Also, as the processor, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an FPGA (field-programmable gate array), etc. can be used. Note that the description regarding the configuration described here can also be applied to other devices or systems described below in the present disclosure.

[0031] Also, when some or all of the components of the image display device 10 are realized by a plurality of information processing devices, circuitry, etc., the plurality of information processing devices, circuitry, etc. may be centrally arranged or may be distributed. For example, the information processing devices, circuitry, etc. may be realized in a form in which each is connected via a communication network, such as a client-server system or a cloud computing system. Also, the function of the image display device 10 may be provided in the form of SaaS (Software as a Service).

[0032] The above is the description of Embodiment 1. The image display device 10 according to Embodiment 1 can detect a person of interest showing symptoms of an infectious disease in a place where a plurality of people come and go, and further display an image including a situation where there is a possibility that the infectious disease will be transmitted to the people existing around the person of interest. Therefore, according to Embodiment 1, it is possible to provide an image display device or the like that preferably displays a situation with a high infection risk.

[0033] <Embodiment 2> Next, Embodiment 2 will be described. FIG. 3 is a block diagram of the image display device 20 according to Embodiment 2. The image display device 20 shown in FIG. 3 differs from that in Embodiment 1 in that it has a thermal image data acquisition unit 116 and a storage unit 120.

[0034] The thermal image data acquisition unit 116 acquires thermal image data from an infrared camera (or a thermal camera). In the following description, for the sake of easily distinguishing from the infrared camera, the camera connected to the image data acquisition unit 111 is also referred to as a "visible light camera". Also, the image data generated by the visible light camera is also referred to as "visible light image data". The infrared camera is installed corresponding to the visible light camera connected to the image data acquisition unit 111.

[0035] The visible light camera and the infrared camera are installed at a predetermined location within a predetermined facility, around the facility, or outdoors. The visible light camera captures a scene including a person, generates visible light image data related to the captured scene image, and supplies the generated visible light image data to the image data acquisition unit 111. The infrared camera captures a scene including a person, generates thermal image data related to the captured scene image, and supplies the generated thermal image data to the thermal image data acquisition unit 116.

[0036] At least a part of the shooting ranges of the visible light camera and the infrared camera overlap with each other. In other words, the infrared camera has a shooting range corresponding to at least a part of the visible light image captured by the visible light camera. Also, it is preferable that the visible light camera and the infrared camera are fixed so that their relative positions do not change. With such a configuration, the imaging device can associate the image of a person included in the visible light image data generated by the visible light camera with the image of a person included in the thermal image data generated by the infrared camera.

[0037] Note that the visible light camera and the infrared camera may each be one or a plurality. For example, the visible light camera or the infrared camera may be movable such that their relative positions change. In this case, even if the visible light camera or the infrared camera temporarily pans, tilts, or zooms, for example, in response to a user operation or the like, changing the angle of view, it is preferable that it then automatically returns to a predetermined position.

[0038] The thermal image data acquisition unit 116 acquires thermal image data from the above-described infrared camera and supplies the acquired thermal image data to the estimation unit 113.

[0039] The estimation unit 113 in the present embodiment measures the body surface temperature of a person included in the thermal image data. For example, first, the estimation unit 113 extracts an image of a person from the visible light image data. At this time, the estimation unit 113 may extract only a specific part such as a face image inside the person's body. Next, the estimation unit 113 extracts thermal image data corresponding to the identified person's image. Further, the estimation unit 113 measures the body surface temperature of the identified person from the extracted thermal image data. The estimation unit 113 may measure the body surface temperature from the part showing the highest temperature among the extracted thermal image data. Also, the estimation unit 113 may calculate a statistical value of the temperature of the extracted thermal image data and use the calculated statistical value as the body surface temperature of the person.

[0040] The estimation unit 113 estimates the likelihood of a person developing a disease using the body surface temperature of the person measured from the thermal image data. More specifically, for example, the estimation unit 113 measures the body surface temperature of the identified person and estimates that there is a likelihood of developing an infectious disease when the measured value is equal to or higher than a preset threshold (for example, 37.5 degrees Celsius). Also, the estimation unit 113 may estimate the likelihood of developing an infectious disease in consideration of the measured body surface temperature described above and the symptom actions described below.

[0041] When the estimation unit 113 receives visible light image data, it detects the motion state of a person from the image data of the person included in the received visible light image data. Then, the estimation unit 113 reads the symptom motion database 121 stored in the storage unit 120. Further, the estimation unit 113 compares the detected motion state of the person with the symptom motion patterns included in the symptom motion database 121 to check whether the motion state of the person matches the symptom motions related to the onset of an infectious disease. Thereby, the estimation unit 113 estimates the likelihood of the person getting sick.

[0042] That is, when the motion state of a person matches the symptom motions related to the onset of an infectious disease, the estimation unit 113 estimates that such a person has the possibility of developing an infectious disease. More specifically, for example, the estimation unit 113 detects an action in which a person identified from the image data coughs or sneezes. On the other hand, the symptom motion database 121 stores the motion patterns in which a person coughs or sneezes. The estimation unit 113 compares the detected motion with the symptom motion pattern, and when they match, estimates the possibility that the person related to the detected motion has developed an infectious disease. In the above description, the fact that the collation results match indicates a substantial match, and the determination of the match can be appropriately set by those skilled in the art.

[0043] The attention image detection unit 114 in the present embodiment detects that the attention person and the surrounding persons are performing attention motions. Here, the "attention motion" is an action including at least one of the mouth movement of a person, wearing a mask, coughing, sneezing, and contact actions, and refers to a predetermined action determined to have a high risk of infection of an infectious disease. For example, when a person is performing an action of moving their mouth violently, it is assumed that the person is talking. When the attention image detection unit 114 detects that the attention person and the surrounding persons are performing such attention motions in an image including the attention person and the surrounding persons, it detects an attention image.

[0044] The attention image detection unit 114 may detect an attention image while further considering the degree of congestion in the area containing people in the image related to the image data. In this case, when the degree of congestion is relatively high, the attention image detection unit 114 determines that the risk of infectious disease infection is relatively high. The attention image detection unit 114 may calculate a predetermined population density from the relationship between the space and the number of people in the image data as the degree of congestion. Further, the attention image detection unit 114 may perform crowd detection in the image data as the degree of congestion. A crowd refers to a state in which a plurality of people appear overlapping in a predetermined space. In this case, the attention image detection unit 114 can detect a crowd, identify the congestion state of the detected crowd, and calculate the degree of congestion.

[0045] In addition, when the attention person and the surrounding persons continue to exist at the same viewing angle, the attention image detection unit 114 may be set to detect one attention image from the period during which the attention person and the surrounding persons exist. Thereby, the attention image detection unit 114 can suppress the redundant detection of the attention image.

[0046] The storage unit 120 is a storage device including a non-volatile memory such as an EPROM (Erasable Programmable Read Only Memory) or a flash memory. The storage unit 120 stores a symptom behavior database 121. The symptom behavior database 121 is a database for estimating the likelihood of developing an infectious disease and includes the symptom behavior patterns of people who have developed an infectious disease. As described above, the storage unit 120 appropriately supplies the symptom behavior database 121 to the estimation unit 113. The symptom behavior database 121 may include a plurality of symptom behavior patterns. Also, the data included in the symptom behavior database 121 may be updated as appropriate.

[0047] Next, with reference to FIG. 4, the configuration of the system including the image display device 20 will be described. FIG. 4 is a block diagram of the image display system 1 according to the second embodiment. The image display system 1 is installed for the purpose of grasping the infection risk of people in the facility 900. The main components of the image display system 1 include an image display device 20, an image display device, a visible light camera 300, and a thermal camera 400.

[0048] The visible light camera 300 and the thermal camera 400 are fixed at predetermined positions in the facility 900 and photograph people in the facility 900. The visible light camera 300 and the thermal camera 400 are communicably connected to the image display device 20 via a network N1 which is a communication network. As shown in the figure, for example, the visible light camera 300 photographs the person P1 and the person P2 with the angle of view indicated by the dotted line, generates visible light image data, and supplies it to the image display device 20. Also, the thermal camera 400 photographs the person P1 and the person P2 with the angle of view indicated by the two-dot chain line, generates thermal image data, and supplies it to the image display device 20.

[0049] The image display device 20 shown in FIG. 4 is connected to the visible light camera 300 via the network N1 and receives visible light image data. Also, the image display device 20 is connected to the thermal camera 400 via the network N1 and receives thermal image data. Further, the image display device 20 is communicably connected to the display 200 and outputs image data related to a series of image groups via the output unit 115. In the example shown in the figure, one visible light camera 300 and one thermal camera 400 are shown, but the number of these cameras may be plural. By a plurality of cameras photographing different locations and supplying the image data photographed by each to the image display device 20, the image display system 1 can grasp the infection risk over a wide range of the facility 900.

[0050] The display 200 is a display device including, for example, a liquid crystal display or an organic electroluminescence. The display 200 is communicably connected to the image display device 20, receives image data from the image display device 20, and displays the received image data. In the example shown in FIG. 4, the image display device 20 and the display 200 are connected without passing through the network N1, but they may be connected via the network N1. By visually recognizing the image group displayed on the display 200 by the user of the image display system 1, the user can grasp the contact situation between the person of interest who is highly likely to be an infected person and the surrounding people.

[0051] Next, with reference to FIG. 5, the image group extracted by the image display device 20 will be described. FIG. 5 is a diagram showing an example of the image group extracted by the image display device according to the second embodiment. In FIG. 5, the arrow extending horizontally from left to right indicates the passage of time. Also in FIG. 5, above the arrow, the band shape extending parallel to the arrow indicates the shooting period V20. The shooting period V20 schematically shows the period during which a plurality of images, that is, a moving image, captured by the visible light camera 300 are continuously generated.

[0052] The first period Q1 and the second period Q2 extending in the left - right direction are shown within the shooting period V20. The first period Q1 indicates the period during which the person P1 is included in the images captured by the visible light camera 300. The second period Q2 indicates the period during which the person P2 is included in the images captured by the visible light camera 300. Specifically, the first period Q1 indicates the period between the time T1 and the time T7. The second period Q2 indicates the period between the time T2 after the time T1 and the time T6 before the time T7.

[0053] In the central part of the belt-shaped V20, an extraction period V21 indicated in boldface is superimposed. The extraction period V21 is a period during which the person P1 and the person P2 are approaching each other, and indicates the period during which a series of image groups extracted by the output unit 115 were taken. More specifically, the extraction period V21 indicates the period from the time T3 after the time T3 to the time T5 before the time T6. In the central part of the extraction period V21, a highlighted time V22 indicated by hatching is shown. The highlighted time V22 is the time T4, which is after the time T3 and before the time T5.

[0054] In FIG. 5, the time T4 is the time when the highlighted image detected by the highlighted image detection unit 114 was taken. That is, at the time T4, the person P1 and the person P2 were, for example, in the closest state, and it was determined that the risk of infection was high. Therefore, the highlighted image detection unit 114 detected the image taken at the time T4 as the highlighted image. Further, the output unit 115 extracts a preset period (that is, from the time T3 to the time T5) before and after the time when the highlighted image was taken as a series of image groups.

[0055] The image groups extracted by the image display device 20 have been described above. Note that the method for extracting the above-described image groups is merely an example, and the image groups extracted by the output unit 115 are not limited to the above-described method. For example, the output unit 115 may extract the period during which the person P2 is included in the angle of view, that is, from the time T2 to the time T6. Further, the output unit 115 may extract the period during which the person P1 is included in the angle of view, that is, from the time T1 to the time T7. Note that when the output unit 115 extracts a series of image groups, the frame rate and image quality of the image data may be changed.

[0056] The above has described Embodiment 2. The image display device 20 and the image display system 1 according to Embodiment 2 can detect a person of interest showing symptoms of an infectious disease in a place where a plurality of people come and go, and further display an image including a situation where there is a possibility that the infectious disease will be transmitted to the people existing around the person of interest. Therefore, according to Embodiment 2, it is possible to provide an image display device, an image display system, etc. that preferably display a situation with a high infection risk.

[0057] <Embodiment 3> Next, Embodiment 3 will be described. FIG. 6 is a block diagram of an image display device 30 according to Embodiment 3. The image display device 30 shown in FIG. 6 is different from the above-described embodiment in that the storage unit 120 stores an authentication database. Also, the processing performed by the specifying unit 112 in the image display device 30 shown in FIG. 6 is different from that in the above-described embodiment.

[0058] The authentication database 122 includes person authentication data and person attribute data. The authentication data is data used for authentication performed by the specifying unit 112. The authentication data is data for identifying a person-specific feature, for example, feature data of a face image. The authentication data may be iris data or ear shape data.

[0059] The attribute data is data associated with the person subject to authentication and is used when determining the risk of contracting an infectious disease. For example, the attribute data may include antibody certification data possessed by the person subject to authentication. The antibody certification data is data indicating whether or not the person has antibodies against an infectious disease. Also, the attribute data may be the past history related to the infectious disease of the person subject to authentication or other information related to the resistance to the infectious disease of the person subject to authentication.

[0060] In this embodiment, the specifying unit 112 performs, in addition to specifying a person, authentication of the person using authentication data. When specifying a person, the specifying unit 112 uses the authentication data included in the authentication database 122. The specifying unit 112 supplies the result of the authentication to the estimating unit 113. The estimating unit 113 estimates the infection possibility of the person subject to authentication from the data received from the specifying unit 112.

[0061] Specifically, for example, when the body surface temperature of the person subject to authentication is equal to or higher than the threshold value, or when such a person performs an operation that matches the symptom operation pattern, if this person has antibody certification, the estimating unit 113 determines whether or not the person shows symptoms taking this into account. That is, when the body surface temperature of a person with antibody certification is equal to or higher than the threshold value, or when a person with antibody certification performs an operation that matches the symptom operation pattern, the estimating unit 113 may not determine that such a person may show symptoms of an infectious disease.

[0062] Also, the attention image detection unit 114 in this embodiment detects an attention image based on the attribute data. For example, the attention image detection unit 114 detects an attention image taking into account the antibody certification data of the person subject to authentication. More specifically, when a peripheral person existing near the person of interest has antibody certification, the attention image detection unit 114 does not determine that the infection possibility of this peripheral person is high. Therefore, even if a person with this antibody certification exists near the person of interest, the attention image detection unit 114 may not detect this as an attention image.

[0063] The above describes Embodiment 3. The image display device 30 according to Embodiment 3 can detect a person of interest showing symptoms of an infectious disease at a place where a plurality of people come and go, and further display an image including a situation where there is a possibility that an infectious disease is transmitted to a person existing around the person of interest. Also, when detecting the person of interest and extracting the attention image, the image display device 30 performs processing taking into account the attribute data of the person subject to authentication. Therefore, according to Embodiment 3, it is possible to provide an image display device or the like that suitably displays a situation with a high infection risk taking into account the individual circumstances of a person.

[0064] <Embodiment 4> Next, Embodiment 4 will be described. The image display device 40 according to Embodiment 4 is different from the above-described embodiments in that the storage unit 120 stores the index database 123 and the attention image detection unit 114 uses the index database 123. FIG. 7 is a block diagram of the image display device 40 according to Embodiment 4.

[0065] The attention image detection unit 114 in the present embodiment detects an attention image in consideration of an infection risk index related to the shooting location of the acquired image data. For example, when there are an image in which a person of interest and surrounding people come into contact at a location with a relatively high infection index and an image with the same contact at a location with a relatively low infection index, the attention image detection unit 114 may detect the former as the attention image and may not detect the latter.

[0066] The storage unit 120 in the present embodiment stores the index database 123. The index database 123 is a database including an infection risk index related to the shooting location of the acquired image data. The index database 123 is linked to a camera that shoots a predetermined shooting location and is a preset value.

[0067] For example, the infection risk index associated with outdoor image data is set lower than the infection risk index associated with indoor image data. Also, even for indoor image data, the infection risk index associated with image data of a relatively narrow space is set higher than the infection risk index associated with image data of a relatively wide space. In addition, the infection risk index can be set higher for a place where the air flow is relatively poor than for a place where the air flow is relatively good, depending on, for example, the ventilation situation of the room or the shape of the room. Note that different infection risk indexes may be set for different shooting areas in the image data shot by one camera.

[0068] Also, the infection risk index may be updated as appropriate. For example, when the person of interest stays in the same place for a period longer than a preset period, the person-of-interest image detection unit 114 may temporarily set the infection risk index of the place where the person of interest stayed to be high. In this case, the person-of-interest image detection unit 114 may detect the area of interest where the person of interest has stayed for a period longer than the preset period, and detect an image in which surrounding people are present in the area of interest as the image of interest.

[0069] As described above, Embodiment 4 has been explained. When extracting the image of interest, the image display device 40 performs processing taking into account the infection risk index related to the shooting location. Therefore, according to Embodiment 4, it is possible to provide an image display device or the like that preferably displays a situation with a high infection risk in consideration of the circumstances of the shooting location.

[0070] <Embodiment 5> Next, Embodiment 5 will be described. The image display device according to Embodiment 5 is different from the above-described embodiments in that it has an audio data acquisition unit and that audio data is used when detecting a person of interest or an image of interest. FIG. 8 is a block diagram of an image display device 50 according to Embodiment 5.

[0071] The image display device 50 has an audio data acquisition unit 117. The audio data acquisition unit 117 acquires audio data generated by a microphone installed in the shooting area of the image data. The audio data acquisition unit 117 supplies the acquired audio data to the estimation unit 113 and the person-of-interest image detection unit 114.

[0072] The estimation unit 113 in the present embodiment estimates the possibility of onset from the voice uttered by the identified person. For example, the estimation unit 113 extracts the voice that is estimated to be uttered by the identified person from the audio data received from the audio data acquisition unit 117. At this time, the estimation unit 113 may analyze the visible light image data or the thermal image data in addition to the audio data. When the identified person is coughing or sneezing, etc., the estimation unit 113 associates this with the symptom action pattern.

[0073] In addition, the target image detection unit 114 in the present embodiment receives voice data from the voice data acquisition unit 117, and detects voices emitted by the target person and surrounding persons from the received voice data. Then, it detects that the target person is coughing or sneezing near the surrounding persons, or that the target person is talking to the surrounding persons, or that the target person is shouting, etc. At this time, the target image detection unit 114 may detect the above-mentioned voices after analyzing the body postures of the target person and surrounding persons in the visible light image data or thermal image data. By such a method, the target image detection unit 114 detects a target image from the image data.

[0074] As described above, Embodiment 5 has been explained. The image display device 50 uses voice data when determining a target person or detecting a target image. Thereby, the accuracy of the image display device 50 for displaying a desired image is improved. Therefore, according to Embodiment 5, it is possible to provide an image display device or the like that accurately displays a situation with a high infection risk.

[0075] <Embodiment 6> Next, Embodiment 6 will be described. Embodiment 6 is different from the above-described embodiments in that it has a degree of attention setting unit. FIG. 9 is a block diagram of an image display device 60 according to Embodiment 6. The image display device 60 has a degree of attention setting unit 118.

[0076] The attention level setting unit 118 sets an attention level for the attention image. The attention level serves as an indicator when displaying a series of image groups and can also be referred to as a display priority. The attention level is indicated by a numerical value within a predetermined range, for example. The predetermined range may be a multi-level range such as 0, 1, and 2, for example. For example, the higher the attention level of an image group, the higher the likelihood that an infectious disease is spreading to surrounding people. The attention level setting unit 118 analyzes the contact state between the attention person and the surrounding people and sets the attention level according to the analysis result. Specifically, for example, the attention level setting unit 118 sets the attention level (first attention level) of an image in which the attention person and the surrounding people are facing each other and having a conversation at a very close distance higher than the attention level (second attention level) of an image in which the attention person and the surrounding people are not having a conversation.

[0077] In addition to the above example, for example, when there are a large number of people and the situation is crowded, and the attention person and the surrounding people are facing each other, the attention level setting unit 118 sets a higher attention level than when it is not crowded. Alternatively, when the attention person and the surrounding people are facing each other, if the attention person and the surrounding people are not wearing masks, the attention level setting unit 118 sets a higher attention level than when they are wearing masks. Alternatively, when the attention person and the surrounding people are facing each other, if the infection risk index of the place where they are facing each other is high, the attention level setting unit 118 sets a higher attention level than in a similar situation in a place with a low infection risk index.

[0078] In this case, the output unit 115 sets and outputs a higher display priority for image groups with a higher attention level. That is, the output unit 115 preferentially outputs the image group set to the first attention level with a relatively high attention level over the image group set to the second attention level with a relatively low attention level.

[0079] Next, the processing performed by the image display device 60 will be described with reference to FIG. 10. FIG. 10 is a flowchart showing an image display method according to the sixth embodiment. The flowchart shown in FIG. 10 differs from the flowchart shown in FIG. 2 in that steps S21 and S22 are added between step S14 and step S15.

[0080] In step S14, the attention image detection unit 114 detects an attention image including a person of interest having a likelihood of onset and surrounding persons around the person of interest from the estimation result received from the estimation unit 113 (step S14). The attention image detection unit 114 supplies the detected attention image to the output unit 115 and the attention level setting unit 118.

[0081] Next, the attention level setting unit 118 sets an attention level for the attention image received from the attention image detection unit 114 (step S21). The attention level setting unit 118 supplies the attention level set for the attention image to the output unit 115.

[0082] Next, the output unit 115 sets the display order of the attention images according to the set attention level (step S22).

[0083] Next, the output unit 115 extracts a series of image groups including the attention image from the attention image received from the attention image detection unit 114, and outputs the extracted series of image groups to the display device according to the above-described display order (step S15).

[0084] The processing performed by the image display device 60 has been described above. When the image display device 60 detects a plurality of attention images and extracts a plurality of image groups accordingly, it outputs them in descending order of attention level. By setting the attention level in this way, the image display device 60 can quickly show the user a situation with a high infection risk. Note that the output unit 115 outputs a plurality of image groups according to the display order set according to the attention level, but the output process may be sequentially performed according to the user's operation.

[0085] Next, with reference to FIG. 11, an example of an image displayed by the image display device 60 will be described. FIG. 11 is a diagram showing an example of an image displayed by the image display device 60 according to Embodiment 6.

[0086] Figure 11 shows an image 201 displayed by a display device. In the upper part of the image 201, a map of the facility interior is shown. In the map of the facility interior, the installation positions of cameras 301, 302, and 303 are respectively shown, and areas A, B, and C are shown as the shooting ranges of the respective cameras. In area A, an icon marked with ID#1011 is shown. This indicates that an image group with ID#1011 has been extracted in area A. Similarly, in area B, an icon marked with ID#1012 is shown. This indicates that an image group with ID#1012 has been extracted in area B. In area C, an icon marked with ID#1013 is shown. This indicates that an image group with ID#1013 has been extracted in area C. A user who views the image 201 can play each video by selecting the icon shown in the map of the facility interior.

[0087] In the lower part of the image 201, a video list is shown. The video list shows video ID#1011, #1012, and #1013. Each video shows the corresponding shooting date sequence, shooting area, and degree of attention respectively. In Figure 11, the video ID#1012 corresponding to the degree of attention "1" has the highest degree of attention. Also, the video ID#1011 corresponding to the degree of attention "2" has the second highest degree of attention. Also, the video ID#1013 corresponding to the degree of attention "3" has the third highest degree of attention. A user who views the image 201 can play the videos in the order of the degree of attention. Also, the user can play the selected video regardless of the degree of attention.

[0088] The above is the description of Embodiment 6. The image display device 60 can preferably output a desired image group by setting the degree of attention. Therefore, according to Embodiment 6, it is possible to provide an image display device or the like that efficiently displays a situation with a high infection risk.

[0089] Incidentally, the above-described program can be stored using various types of non-transitory computer-readable media and supplied to a computer. The non-transitory computer-readable media include various types of tangible recording media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, and semiconductor memories (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)). Also, the program may be supplied to a computer by various types of temporary computer-readable media. Examples of temporary computer-readable media include electrical signals, optical signals, and electromagnetic waves. The temporary computer-readable media can supply the program to a computer via wired communication paths such as electric wires and optical fibers, or wireless communication paths.

[0090] Note that the present invention is not limited to the above-described embodiments, and can be appropriately modified without departing from the gist thereof.

[0091] Some or all of the above embodiments can be described as follows in the appended claims, but are not limited thereto. (Appended Claim 1) Image data acquisition means for acquiring a plurality of image data from a camera; Identification means for identifying a person from the image data; Estimation means for estimating the likelihood of a person identified from the image data developing an infectious disease; Attention image detection means for detecting an attention image including a person of interest having the likelihood of developing the disease and surrounding persons around the person of interest based on the result of the estimation; Output means for extracting and outputting a series of image groups including the attention image. An image display device. (Appended Claim 2) Further comprising thermal image data acquisition means for acquiring thermal image data from an infrared camera. The estimation means estimates the onset possibility based on the body surface temperature of the person measured from the thermal image data corresponding to the image data. The image display device according to Supplementary Note 1. (Supplementary Note 3) It further includes symptom action storage means for storing the symptom actions in the case of developing an infectious disease. The estimation means detects the actions of the identified person and estimates the onset possibility by collating whether the detected actions match the symptom actions. The image display device according to Supplementary Note 1 or 2. (Supplementary Note 4) The symptom action storage means stores the cough or sneeze action of the person as the symptom action. The estimation means detects the cough or sneeze action of the person. The image display device according to Supplementary Note 3. (Supplementary Note 5) The target image detection means detects an image in which the target person and the surrounding persons exist at a distance less than a threshold value for a predetermined period or more as the target image. The image display device according to any one of Supplementary Notes 1 to 4. (Supplementary Note 6) The target image detection means detects a target action including at least one of the mouth movements, mask wearing, cough, sneeze, and contact actions of the target person and the surrounding persons, and detects the target image based on the target action. The image display device according to any one of Supplementary Notes 1 to 5. (Supplementary Note 7) The target image detection means further takes into account the congestion degree of the area including the person in the image related to the image data to detect the target image. The image display device according to any one of Supplementary Notes 1 to 6. (Supplementary Note 8) It further includes authentication data storage means for storing the authentication data and attribute data of the person. The identification means also performs authentication of the person based on the authentication data. The target image detection means detects the target image based on the attribute data. The image display device according to any one of Appendices 1 to 7. (Appendix 9) The authentication data storage means includes antibody certification data that the person has in the attribute data. The target image detection means detects the target image in consideration of the antibody certification data of the person related to the authentication. The image display device according to Appendix 8. (Appendix 10) It further includes index storage means for storing an infection risk index related to the shooting location of the acquired image data. The target image detection means detects the target image in consideration of the infection risk index related to the shooting location of the acquired image data. The image display device according to any one of Appendices 1 to 9. (Appendix 11) The target image detection means detects a target area where the target person has stayed for a period equal to or longer than a preset period, and detects an image in which the surrounding persons exist in the target area as the target image. The image display device according to any one of Appendices 1 to 10. (Appendix 12) It further includes voice data acquisition means for acquiring voice data in the shooting area of the image data. The estimation means estimates the onset possibility based on the voice uttered by the person. The image display device according to any one of Appendices 1 to 11. (Appendix 13) The target image detection means detects the target image based on the voices uttered by the target person and the surrounding persons. The image display device according to any one of Appendices 1 to 12. (Appendix 14) It further includes attention degree setting means for setting an attention degree based on the contact state between the target person and the surrounding persons with respect to the target image. The output means outputs a series of image groups based on the attention degree. The image display device according to any one of Supplementary Notes 1 to 13. (Supplementary Note 15) The apparatus further comprises a degree-of-attention setting means for estimating the infection risk of the surrounding people with respect to the target image and setting the degree of attention based on the infection risk. The output means outputs a series of image groups based on the degree of attention. The image display device according to any one of Supplementary Notes 1 to 13. (Supplementary Note 16) The degree-of-attention setting means sets a higher priority for the image group to be displayed as the degree of attention is higher. The output means preferentially outputs the image group set to the first degree of attention with a relatively high degree of attention over the image group set to the second degree of attention with a relatively low degree of attention. The image display device according to Supplementary Note 14 or 15. (Supplementary Note 17) The image display device according to any one of Supplementary Notes 1 to 16, and at least one of a camera that supplies the image data to the image data acquisition means or a display device that receives and displays the image group from the output means. An image display system. (Supplementary Note 18) A computer acquires a plurality of image data from a camera, identifies a person from the image data, estimates the possibility of developing an infectious disease in the identified person, detects a target image including the target person having the possibility of developing the disease and surrounding people around the target person based on the result of the estimation, extracts and outputs a series of image groups including the target image. An image display method. (Supplementary Note 19) To a computer a process of acquiring a plurality of image data from a camera, a process of identifying a person from the image data, a process of estimating the possibility of developing an infectious disease in the identified person, Based on the result of the above-mentioned estimation, a process of detecting a target image including a person of interest having the possibility of onset and a person around the person of interest, and a process of extracting and outputting a series of image groups including the target image are executed. A non-transitory computer-readable medium storing a program for causing a computer to execute the program.

[0092] This application claims priority based on Japanese Patent Application No. 2020-206504 filed on December 14, 2020, and incorporates the entire disclosure thereof herein.

Explanation of Signs

[0093] 1 Image display system 10 Image display device 20 Image display device 30 Image display device 40 Image display device 50 Image display device 60 Image display device 111 Image data acquisition unit 112 Identification unit 113 Estimation unit 114 Target image detection unit 115 Output unit 116 Thermal image data acquisition unit 117 Audio data acquisition unit 118 Attention degree setting unit 120 Storage unit 121 Symptom action database 122 Authentication database 123 Index database 200 Display 300 Visible light camera 400 Thermal camera 900 Facility N1 Network P1 Person P2 Person

Claims

1. Image data acquisition means for acquiring a plurality of image data from a camera, Identification means for identifying a person from the image data, Estimation means for estimating the likelihood of onset of an infectious disease of the person identified from the image data, Attention image detection means for detecting an attention image including a person of interest having the likelihood of onset and surrounding persons around the person of interest based on the result of the estimation, Symptom action storage means for storing symptom actions related to the occurrence of an infectious disease, and comprising, The estimation means, Estimates the likelihood of occurrence of an infectious disease of the identified person by collating whether the action of the identified person matches the symptom action related to the occurrence of the infectious disease, Further comprising authentication data storage means for storing the authentication data of the person and the attribute data of the person, The identification means also performs authentication of the person based on the authentication data, The attention image detection means detects the attention image based on the attribute data of the person corresponding to the surrounding persons among the authenticated persons, An image display device.

2. Further comprising thermal image data acquisition means for acquiring thermal image data from an infrared camera, The estimation means estimates the likelihood of onset based on the body surface temperature of the person measured from the thermal image data corresponding to the image data, The image display device according to claim 1.

3. The symptom action storage means stores the cough or sneeze action of the person as the symptom action, The estimation means detects the cough or sneeze action of the person, The image display device according to claim 1.

4. The attention image detection means detects, as the attention image, an image in which the person of interest and the surrounding persons exist at a distance less than a threshold value for a predetermined period or more, The image display device according to any one of claims 1 to 3.

5. The attention image detection means detects an attention action including at least one of the mouth movements, mask wearing, cough, sneeze, and contact actions of the person of interest and the surrounding persons, and detects the attention image based on the attention action, The image display device according to any one of claims 1 to 4.

6. The attention image detection means further takes into account the congestion degree of the area including the person in the image related to the image data to detect the attention image, The image display device according to any one of claims 1 to 5.

7. The authentication data storage means includes antibody certification data possessed by the person in the attribute data, The target image detection means detects the target image in consideration of the antibody certification data of the person corresponding to the peripheral person among the authenticated persons. The image display device according to claim 1.

8. A computer acquires a plurality of image data from a camera, identifies a person from the image data, estimates the possibility of the identified person developing an infectious disease, detects a target image including a target person having the possibility of developing the disease and peripheral persons around the target person based on the result of the estimation, and further estimates the possibility of the identified person developing an infectious disease by collating whether the action of the identified person matches the symptomatic action related to the occurrence of the infectious disease, and further uses the authentication data and attribute data of the person stored in advance to perform the authentication of the person based on the authentication data, detects the target image based on the attribute data of the person corresponding to the peripheral person among the authenticated persons. An image display method.

9. On a computer perform a process of acquiring a plurality of image data from a camera, perform a process of identifying a person from the image data, perform a process of estimating the possibility of the identified person developing an infectious disease, execute an image display method comprising a process of detecting a target image including a target person having the possibility of developing the disease and peripheral persons around the target person based on the result of the estimation, and further execute an image display method comprising a process of estimating the possibility of the identified person developing an infectious disease by collating whether the action of the identified person matches the symptomatic action related to the occurrence of the infectious disease, and further use the authentication data and attribute data of the person stored in advance to perform the authentication of the person based on the authentication data, execute an image display method comprising a process of detecting the target image based on the attribute data of the person corresponding to the peripheral person among the authenticated persons. A program for causing a computer to execute.

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