Spatial infection risk determination system, spatial infection risk information processing method and program

Abstract

To provide a spatial infection risk determination system, a spatial infection risk determination method and a program for preventing infection disease from spreading.SOLUTION: A spatial infection risk determination system 1 comprises a computer 10, an imaging device 20 and a display device 30. A person detection part 101 automatically identifies and detects a person in a video obtained from a video acquisition part 201. An information acquisition part 102 acquires information on properties and a state of a person, or environmental conditions of a space for setting a social distance. An infection risk determination part 103 determines an infection risk based upon the properties and state of the person, or the environmental conditions of the space acquired by the information acquisition part 102. A social distance range calculation part 104 calculates a social distance range based upon the infection risk determined by the infection risk determination part 103. A spatial risk determination part 105 makes a determination based upon the floor area of the space where an infection risk in one space is to be determined and a social distance range of a person present in the space.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a spatial infection risk determination system, a spatial infection risk determination method, and a program. [Background technology]

[0002] A means for easily notifying facility managers and prospective facility users of useful congestion information for ensuring the necessary social distancing to prevent the spread of infectious diseases has been disclosed (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6764214 Summary of the Invention [Problem to be solved by the invention]

[0004] The congestion information notification system described in Patent Document 1 discloses a technology for displaying a circular line indicating a predetermined range from a person superimposed on a processed image. However, the technology described in Patent Document 1 cannot determine the infection risk of a person who enters a space and contracts an infectious disease according to the state of the space. The present invention aims to provide a spatial infection risk determination system that determines the infection risk according to the state of the space. [Means for solving the problem]

[0005] According to one aspect of the present invention, the system of the present invention is a spatial infection risk assessment system that includes a detection means for detecting a person from an image of the space acquired by an imaging device, and a assessment means for assessing the infection risk within the space based on the floor area of ​​the space and the area of ​​a circle centered on the detected person and based on a distance for preventing the transmission of infectious diseases.

[0006] According to one aspect of the present invention, the method of the present invention is a method for determining the risk of infection in a space, which detects people in a space and determines the risk of infection in the space based on the floor area of ​​the space and the area of ​​a circle based on the distance for preventing the transmission of infectious diseases.

[0007] According to one aspect of the present invention, the program of the present invention executes a detection process to detect a person from an image taken within a space, and a determination process to determine the infection risk within the space based on the floor area of ​​the space and the area of ​​a circle based on the distance for preventing the transmission of infectious diseases. Effect of the Invention

[0008] According to the present invention, by setting the distance necessary to prevent the spread of an infectious disease based on the state of a certain space, it is possible to provide a spatial infection risk assessment system, a spatial infection risk assessment method, and a program that correspond to the state of the space. [Brief description of the drawings]

[0009] [Figure 1] A diagram for explaining an example of use of the spatial infection risk assessment system in this embodiment. [Diagram 2] 1 is an example of a configuration diagram of a spatial infection risk assessment system in this embodiment. [Diagram 3] FIG. 2 is a sequence diagram showing a processing flow of the present embodiment. [Figure 4] 4 is a flowchart showing a process flow of the present embodiment. [Diagram 5] 4 is an example of a processing screen according to the present embodiment. [Figure 6] 4 is a flowchart showing a process flow of the present embodiment. [Figure 7] 4 is an example of a processing screen according to the present embodiment. [Figure 8] 4 is a flowchart showing a process flow of the present embodiment. [Figure 9] 4 is an example of a processing screen according to the present embodiment. [Figure 10] 4 is an example of a processing screen according to the present embodiment. [Figure 11] 4 is a flowchart showing a process flow of the present embodiment. [Figure 12] 4 is a flowchart showing a process flow of the present embodiment. [Figure 13] 1 is an example of a configuration diagram of a spatial infection risk assessment system in this embodiment. [Figure 14] FIG. 2 is a sequence diagram showing a processing flow of the present embodiment. [Figure 15] 1 is an example of a hardware configuration of a spatial infection risk determination system in this embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] First, in order to facilitate understanding of embodiments of the present invention, a background of the present invention will be described. There are cases where facilities need to be operated while taking into consideration the prevention of the spread of infectious diseases. For example, in order to prevent the spread of infectious diseases, it is important to ensure the distance between people (social distance) required to prevent the spread of infectious diseases. Until now, social distance has often been determined as a fixed distance based on the distance that droplets emitted from a person's mouth during conversation or coughing can travel. However, for example, when comparing adults and children, it is assumed that adults can send droplets farther due to their body size, and therefore the risk of transmitting infectious diseases to others (infection risk) is higher. In addition, people with cold symptoms are assumed to have a higher infection risk because they sneeze and cough more frequently than people without cold symptoms. Furthermore, when comparing spatial environments, if the humidity and temperature are low, the virus becomes activated and the risk of infection increases. As shown above, the social distance required to prevent the spread of infection varies depending on various conditions within the space.

[0011] For example, when judging the crowdedness of a certain facility, the degree of congestion may be determined by calculating the number of people per unit area of ​​the space. If the number is higher than a predetermined value, the facility operator may determine that the degree of congestion is high and may decide not to allow any more people into the space. However, in this case, the risk of infection, which changes depending on various conditions in the space as described above, is not taken into consideration when deciding whether or not to allow people to enter.

[0012] According to the embodiment of the present invention described below, it is possible to determine the infection risk in a space that changes depending on various conditions in the space. Note that, hereinafter, the infection risk in a space is referred to as spatial infection risk.

[0013] Hereinafter, exemplary embodiments of the present invention will be described with reference to the drawings. In the drawings, similar or corresponding elements are denoted by the same reference numerals, and descriptions thereof may be omitted or simplified.

[0014] [Feature Overview] An overview of the functions realized by the present invention will be described with reference to Fig. 1. Fig. 1 shows the configuration of a spatial infection risk determination system according to this embodiment. As shown in Fig. 1, the spatial infection risk determination system according to this embodiment includes a computer 10, an imaging device 20, and a display device 30.

[0015] The computer 10 sets a social distance based on the attributes and status of the person detected by the imaging device 20 or the environmental conditions of the space (room), and judges the spatial infection risk. The social distance is the distance between people required to prevent the spread of an infectious disease, and is the distance required to prevent the spread of an infectious disease.

[0016] The imaging device 20 is an image acquisition unit such as a surveillance camera that is installed at a predetermined monitoring position and captures people in the imaging space. The imaging device 20 may be a camera with a fixed orientation and installation location, a camera whose orientation can be changed such as a PTZ (Pan Tilt ZOOM) camera, or a movable camera mounted on a mobile object such as a drone. It may also be a camera mounted on a wearable terminal such as a smartphone or tablet. The imaging device 20 and the computer 10 are connected to each other so as to be able to communicate with each other via an arbitrary network. The computer 10 and the imaging device 20 may be a single device.

[0017] The display device 30 displays the calculated social distance range in a display mode according to the risk of infectious diseases. The social distance range is a range (area) that specifies the distance between people to prevent infection with infectious diseases. For example, the display device may be a signage placed outside the space, or a PC display. It may also be a display unit of a wearable device such as a smartphone or a tablet. The display device 30 and the computer 10 are connected to each other so as to be able to communicate with each other via any network. The computer 10, the imaging device 20, and the display device 30 may be integrated into one device.

[0018] In this manner, in this embodiment, when visualizing the social distance range required for infection prevention, the social distance of a person can be appropriately calculated by setting the social distance according to the infection risk. In addition, the spatial infection risk determination system determines the spatial infection risk from the above social distance range, so that the manager of the space can easily determine whether or not additional people can enter the space. [First embodiment]

[0019] The configuration of the spatial infection risk determination system 1 and the spatial infection risk determination method in this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the overall configuration of the spatial infection risk determination system 1 in this embodiment. The spatial infection risk determination system 1 includes a computer 10, an imaging device 20, and a display device 30. The computer 10 and the imaging device 20 can communicate with each other via a wired or wireless communication unit that each of them has. Similarly, the computer 10 and the display device 30 can communicate with each other via a wired or wireless communication unit that each of them has. The number of computers 10, imaging devices 20, and display devices 30 is at least one each, and it is also possible to connect and install multiple devices at the same time.

[0020] Next, the functional configuration of the computer 10, the imaging device 20, and the display device 30 will be described with reference to FIG. 2. The computer 10 is composed of a person detection unit 101, an information acquisition unit 102, an infection risk determination unit 103, a social distance range calculation unit 104, a spatial infection risk determination unit 105, and a display processing unit 106. The imaging device 20 is composed of an image acquisition unit 201, and the display device 30 is composed of a display unit 301. The person detection unit 101 serves as a detection means for detecting a person from an image of the space acquired by the imaging device 20. The information acquisition unit 102, the infection risk determination unit 103, the social distance range calculation unit 104, and the spatial infection risk determination unit 105 serve as a determination means for determining the infection risk in the space according to the floor area of ​​the space and the area of ​​a circle centered on the detected person and based on the distance for preventing infection of an infectious disease. The display processing unit 106 serves as a display means for displaying a circle around the person on the display device 30.

[0021] The person detection unit 101 automatically identifies and detects people from the video obtained from the video acquisition unit 201. This person identification is specifically performed by any one of various known methods or a combination of them. For example, objects other than the background are extracted from the captured image by background subtraction. This background subtraction is a known technology, and is a technology for extracting moving objects by taking the difference between the image data of the captured image captured by the video acquisition unit 201 and the background image of the captured target area acquired in advance. Another known technology example is machine learning image analysis. In machine learning video analysis, people in video images are automatically and efficiently identified by image recognition technology using deep learning.

[0022] The information acquisition unit 102 acquires information on the attributes and conditions of a person or the environmental conditions of a space for setting a social distance. The attributes of a person are specifically height and age, and the condition of a person is the physical condition of the person, such as whether or not the person has cold symptoms or an underlying disease. The environmental conditions are the temperature, humidity, amount of ultraviolet rays, or carbon dioxide concentration of the space for determining the spatial infection risk.

[0023] The infection risk determination unit 103 determines the infection risk based on the attributes and condition of the person acquired by the information acquisition unit 102, or the environmental conditions of the space. For example, the attributes of a person are the height and age of the person. Tall people are more likely to spread droplets farther than short people, so it is determined that they have a high infection risk, and short people are determined to have a low infection risk. The condition of a person refers to the presence or absence of cold symptoms (sneezing, coughing, fever) and underlying diseases. People with cold symptoms are determined to have a higher infection risk than people without cold symptoms, and people without infection symptoms are determined to have a low infection risk.

[0024] The environmental conditions of a space refer to the temperature, humidity, amount of ultraviolet light, and carbon dioxide concentration that can be observed from within the space. Generally, under environmental conditions where the temperature, humidity, and amount of ultraviolet light are low, viruses are easily activated and therefore the risk of infection is determined to be high. On the other hand, under environmental conditions where the temperature, humidity, and amount of ultraviolet light are high, the risk of infection is determined to be high. Also, spaces with high carbon dioxide concentrations are considered to have not been ventilated for a long time and are therefore determined to have a high risk of infection. Here, the risk of infection refers to the risk that a person who may be infected will infect a non-infected person, or the risk that a non-infected person will become seriously ill if infected.

[0025] The social distance range calculation unit 104 calculates a social distance range based on the infection risk determined by the infection risk determination unit 103. For example, the social distance range is a circle with a radius R centered on the person. Here, the radius R is a social distance, and is set by the social distance range calculation unit 104 based on the infection risk determined by the infection risk determination unit 103. The circle may be superimposed on the person's feet or around the waist. In addition, it is not limited to a circle, and may be a three-dimensional semicircular sphere that simulates the range of droplets from the mouth to the ground, assuming the range in which droplets fly. The radius R is set based on the level of the infection risk determined by the infection risk determination unit 103. In this embodiment, a method of setting the radius R according to the level of the infection risk has been described, but a fixed value may be set without considering the attributes and state of the person and the environmental conditions in the space.

[0026] The spatial infection risk determination unit 105 determines the infection risk in a space based on the floor area of ​​the space and the social distance range of people present in the space. For example, the spatial infection risk is expressed as the sum of the social distance range of all people present in the space relative to the floor area of ​​the space. The following formula 1 is an example of a formula for determining the spatial infection risk. A represents the spatial infection risk, R represents the radius of the social distance range, n represents the number of people present in the space, and S represents the floor area of ​​the space.

[0027]

number

[0028] When A exceeds 1, the space is determined to have a high spatial infection risk. In the above formula example, the overlap of social distance ranges for each person was not taken into consideration when determining the spatial infection risk, but the spatial infection risk may be determined by focusing on the overlap of social distance ranges. In other words, the spatial infection risk may be determined to be high when the overlap of social distance ranges for the area of ​​the space exceeds a predetermined value. Furthermore, when the spatial infection risk is high, an alert is issued to notify people outside the space and the manager of the space that the spatial infection risk is high.

[0029] The display processing unit 106 superimposes the social distance range calculated by the social distance range calculation unit 104 around the person shown in the image acquired by the image acquisition unit 201 and displays it on the display unit 301. As an example of this embodiment, people inside and outside the space visually recognize the infection risk by changing the size of the circle indicating the social distance range superimposed on the display device 30 according to the infection risk. In addition, the infection risk is made easier to recognize by changing the color of the social distance range or highlighting it with a thick line or the like. Furthermore, the blinking interval may be changed when the social distance range is displayed in a blinking manner. The above social distance range is a circle that is a predetermined distance range centered on the body of a person at a position higher than the person's feet, but it may be a three-dimensional semicircular sphere that imitates the range of droplets from the mouth to the ground, assuming the range of droplets flying.

[0030] FIG. 3 is a sequence diagram showing the flow of processing in this embodiment from when the image acquisition unit 201 acquires an image to when the spatial infection risk is judged and the image is displayed on the display unit 301. The image acquisition unit 201 acquires an image of the space in which the spatial infection risk is judged (S101). The person detection unit 101 detects a person from the acquired image (S102). The information acquisition unit 102 also acquires information on the attributes and status of a person for setting a social distance or on the environmental conditions of the space (S103), and the infection risk determination unit 103 uses the information to determine the level of infection risk (S104). The social distance range calculation unit 104 calculates a social distance range based on the judgment of the infection risk determination unit 103 (S105). The display processing unit 106 superimposes and displays the social distance range calculated by S105 around the person displayed on the display device 30 (S106). The spatial infection risk determination unit 105 calculates the ratio of the total social distance ranges of all people to the floor area in the space as the spatial infection risk (S107). The display processing unit 106 displays the determination result (S108).

[0031] If the spatial infection risk is 1 or more, the space is determined to have a high infection risk, and an alert is output to the manager of the space or to the display unit 301 outside the space. In addition, a signage is placed outside the space, and the display processing unit 106 displays the social distance range so that the presence or absence of a person superimposed and an alert can be visually confirmed, thereby alerting people who intend to enter the space. Alternatively, a method may be used in which alert information is posted on the website of the space, or a notification regarding the alert is sent to a wearable device such as a smartphone. As a result, when a person enters a certain space, the infection risk of the person contracting an infectious disease can be determined according to the state of the space, and the manager can easily determine whether or not additional people can be allowed into the space.

[0032] [Second embodiment] Next, another example applicable to the above-mentioned first embodiment will be described with reference to Figures 4 and 5. In the first embodiment, a method was described in which the infection risk determination unit 103 determines the infection risk based on the attributes and state of a person acquired by the information acquisition unit 102, or the environmental conditions of a space. In the second embodiment, a method of determining the infection risk based on height, which is one of the attributes of a person, will be described in more detail.

[0033] Generally, when a person sneezes, the shortest distance (flight distance) from the person's feet to the position where the droplets reach the floor is different when the person sneezes while standing and when the person sneezes while sitting. In other words, it takes a longer time for droplets from a tall person to fall to the floor, and it is thought that the droplets will fly farther than those of a short person, even if the initial velocity of the droplets from the mouth is the same. Therefore, tall people are more likely to infect people around them than short people, and a wider social distance is required than for short people.

[0034] 4 is a flowchart showing the flow of processing in this embodiment. The person detection unit 101 detects a person present in a space (S201). Next, the information acquisition unit 102 estimates the height of the person detected by the person detection unit 101 (S202).

[0035] The height estimation method is performed by any of various known methods or a combination of them. For example, when the imaging device 20 is a surveillance camera installed at an arbitrary position on the road or in a facility, an arbitrary object (post, vending machine, traffic light, etc.) installed in the shooting area is always present in the captured image. The actual height of the object may be measured in advance and input to the information acquisition unit 102. The information acquisition unit 102 estimates the height of each person based on the relative positional relationship between each person detected in the captured image and the object, the height of the object in the image, and the actual height of the object. In addition, the external appearance feature amount and height of each of multiple people may be registered in a database in advance.

[0036] The information acquisition unit 102 recognizes the detected person by comparing the appearance feature of the person detected in the captured image with the appearance feature registered in the database, and acquires the height of the recognized person from the database. After acquiring the height of each person, the infection risk determination unit 103 determines the level of infection risk (S203). For example, a person who is 120 cm or shorter in height is determined to have a low infection risk, and a person who is taller than 120 cm is determined to have a high risk of infection.

[0037] The social distance range calculation unit 104 calculates the social distance range based on this infection risk determination (S204). For example, if the falling speed of droplets is 30 cm / sec, it takes 4 seconds for droplets to reach the floor for a person who is 120 cm tall, and 6 seconds for a person who is 180 cm tall. If the flight distance of droplets from the feet of a person who is 180 cm tall is 6 m, the initial speed of the droplets from the mouth is 1 m / sec, and if this is applied to a person who is 120 cm tall, the flight distance of the droplets is calculated to be 4 m.

[0038] In the flowchart of FIG. 4, the risk of infection is divided into two categories, high and low, but the risk of infection is not limited to this and may be medium. For example, if a person with a height of 150 cm is considered to have a medium risk of infection, the above calculation is applied to a person with a height of 150 cm, and the social distance range is calculated to be 5 m. In other words, the social distance range is set to 4 m for heights of 120 cm or less, 5 m for heights of 120 cm to 150 cm, and 6 m for heights of 150 cm or more. The above social distance may be freely input by the administrator into the system as a fixed value, or the value may be set in the program in advance. Furthermore, the risk of infection may be determined in multiple stages without being limited to the above.

[0039] FIG. 5 is an example of a processing screen in this embodiment. An estimated height is displayed above the head of a person present in the space. A circle indicating a social distance range based on the risk of infection is superimposed around the person. In this embodiment, an example of a display in which the height is superimposed is shown, but the height does not have to be displayed. In addition, the circle indicating the social distance range is a circle of a predetermined distance range centered on the body of the person at a position higher than the person's feet, but it may be a three-dimensional semicircular sphere (D1) that simulates the range of droplets from the mouth to the ground, assuming the range of droplets flying. With the above method, it is possible to set an appropriate social distance range by considering the height rather than simply setting the same social distance for all people in the space.

[0040] [Third embodiment] Next, another example applicable to the above-mentioned first embodiment will be described with reference to Figures 6 and 7. In the first embodiment, a method was described in which the infection risk determination unit 103 determines the infection risk based on the attributes and state of a person acquired by the information acquisition unit 102, or the environmental conditions of a space. In the third embodiment, a more detailed description will be given of a method in which the infection risk is determined based on age, which is one of the attributes of the person.

[0041] In general, when elderly people contract an infectious disease, they are at higher risk of becoming seriously ill compared to younger people. For example, with COVID-19, if the severity rate for people in their 30s is set at 1, the severity rate is said to be about 25 times higher for people in their 60s, about 50 times higher for people in their 70s, about 70 times higher for people in their 80s, and about 80 times higher for people in their 90s or older. Here, severe illness refers to treatment in an intensive care unit, the use of a ventilator, or the use of extracorporeal membrane oxygenation.

[0042] 6 is a flowchart showing the flow of processing in this embodiment. The person detection unit 101 detects a person present in a space (S301). Next, the information acquisition unit 102 estimates the age of the person detected by the person detection unit 101 (S302).

[0043] This age estimation method is performed using any one of various known methods or a combination of them. For example, a technology has been disclosed that estimates an age by learning feature quantities related to a person's facial shape, wrinkles, blemishes, sagging skin, color, hair, etc.

[0044] After the information acquisition unit 102 estimates the age, the infection risk determination unit 103 determines, for example, that a person estimated to be 65 years old or older is of high age and has a high infection risk. Also, it determines that a person estimated to be younger than 65 is of low age and has a low infection risk. The social distance range calculation unit 104 sets the social distance to 5 m when the infection risk is determined to be high, and sets the social distance to 3 m when the infection risk is determined to be low.

[0045] In addition, in the flowchart of FIG. 6, the infection risk is divided into two categories, high and low, but the present invention is not limited thereto and may include a medium infection risk. For example, a person estimated to be 65 years old or older is determined to be at high infection risk, a person estimated to be 40 years old or older to less than 65 years old is determined to be at medium infection risk, and a person estimated to be less than 40 years old is determined to be at low infection risk. In this case, the social distance range calculation unit 104 may set the social distance to 5 m when the infection risk is determined to be high, to 4 m when the infection risk is determined to be medium, and to 3 m when the infection risk is determined to be low. The above social distance may be freely input by the administrator into the system as a fixed value, or may be set in the program in advance. The infection risk is not limited to the above and may be determined in multiple stages.

[0046] FIG. 7 is an example of a processing screen in this embodiment. The estimated age is displayed above the head of the person present in the space. In addition, a circle indicating the social distance range based on the infection risk is superimposed around the person. In this embodiment, an example of a display with the age superimposed is shown, but the age does not have to be displayed. With the above method, it is possible to set an appropriate social distance range by taking age into consideration, rather than simply setting the same social distance for all people in the space.

[0047] [Fourth embodiment] Next, another example applicable to the above-mentioned first embodiment will be described with reference to Figs. 8 to 10. In the first embodiment, a method was described in which the infection risk determination unit 103 determines the infection risk based on the attributes and conditions of a person acquired by the information acquisition unit 102, or the environmental conditions of a space. In the fourth embodiment, a method is described in more detail in which the infection risk is determined based on the presence or absence of a disease, such as cold symptoms, which is one of the above-mentioned conditions of the person.

[0048] The general guideline for the distance that droplets can travel is 1m for conversation, 3m for coughing, and 5m for sneezing. In addition, there is data that suggests that influenza patients release 100,000 viruses with each cough, and 2 million viruses with each sneeze. In other words, if a person has cold symptoms, there is a high risk of infecting those around them.

[0049] 8 is a flowchart showing the flow of processing in this embodiment. The person detection unit 101 detects a person present in a space (S401). Next, the information acquisition unit 102 acquires whether or not the person detected by the person detection unit 101 has cold symptoms (S402).

[0050] The presence or absence of cold symptoms is acquired by any of various known methods or a combination of them. For example, a joint estimation technique (skeleton estimation technique) such as Open Pose that utilizes machine learning is used. Coughing and sneezing are detected from the overall shape of the joints of the person detected by the person detection unit 101 and reflex actions using the joint estimation technique.

[0051] After the information acquisition unit 102 acquires the presence or absence of cold symptoms, the infection risk determination unit 103 determines the infection risk to be high if cold symptoms are present, and determines the infection risk to be low if cold symptoms are absent (S403). The social distance range calculation unit 104 sets a predetermined value, such as a social distance of 5 m if the infection risk is determined to be high, or 2 m if the infection risk is determined to be low (S404).

[0052] In addition, in the flowchart of FIG. 8, the infection risk is divided into two categories, high and low, but the present invention is not limited to this and may include a medium infection risk. For example, if a sneeze is detected, the infection risk is determined to be high, if a cough is detected, the infection risk is determined to be medium, and if there are no cold symptoms, the infection risk is determined to be low. In this case, the social distance range calculation unit 104 may set the social distance to 5 m when the infection risk is determined to be high, to 3 m when the infection risk is determined to be medium, and to 2 m when the infection risk is determined to be low. The above social distance may be freely input by the administrator into the system as a fixed value, or may be set in advance in the program.

[0053] In addition, a single sneeze or cough may not be associated with infection. Therefore, if cold symptoms are detected and no further cold symptoms are detected for a certain period of time, the infection risk may be lowered by one level or determined to be low.

[0054] FIG. 9 is an example of a processing screen in this embodiment. The information acquisition unit 102 detects joint points estimated to be the joints of a person based on the characteristics of each part of the person recognized in the image using a joint estimation technique, and further extracts bone segments connecting the detected joint points. Note that the detected joint points and bone segments are joint points and bone segments estimated by the joint estimation technique, and may not match the actual joints and bones of the person. It can also be said that the information acquisition unit 102 detects a skeletal structure including joint points and bone segments from the person's feet to the head. The information acquisition unit 102 recognizes people in multiple images (frames) in a time series, and detects the joint points and bone segments of all people recognized in each image. With the above technique, the information acquisition unit 102 detects coughing and sneezing from the overall shape of the person's joints and reflexive actions, such as when a person places a hand on their mouth.

[0055] In this embodiment, sneezing and coughing are shown as examples of cold symptoms to be detected, but fever may also be detected. An infrared camera is further installed as the imaging device 20, and the person detection unit 101 detects people present in the space. Next, the information acquisition unit 102 detects the body temperature of the people present in the space using the infrared camera. If the body temperature detected by the information acquisition unit 102 is 37.5°C or higher, the infection risk determination unit 103 determines that the infection risk is high, and if the body temperature is less than 37.5°C, the infection risk is low. The social distance range calculation unit 104 sets a predetermined value, such as a social distance of 5m when the infection risk is determined to be high, and a social distance of 2m when the infection risk is determined to be low.

[0056] In addition, a predetermined condition may be set by combining the presence or absence of cold symptoms with fever detection to determine the level of infection risk. The above social distance may be set by allowing the administrator to freely input a fixed value into the system, or the value may be set in advance in the program.

[0057] 10 is an example of a processing screen in this embodiment. A circle indicating a social distance range based on the risk of infection is superimposed around the person. The display processing unit 106 may display the circle indicating the social distance range of a person at risk of infection in an easy-to-understand manner for the administrator by highlighting it by changing the color of the circle or by displaying the line of the circle in a thicker color. With the above method, it is possible to set an appropriate social distance range by taking cold symptoms into consideration, rather than simply setting the same social distance for all people in a space.

[0058] [Fifth embodiment] Next, another example applicable to the above-mentioned first embodiment will be described with reference to Fig. 11. In the first embodiment, a method was described in which the infection risk determination unit 103 determines the infection risk based on the attributes or state of a person acquired by the information acquisition unit 102 or the environmental conditions of a space. In the fifth embodiment, a method of determining the infection risk based on the environmental conditions of a space will be described in more detail.

[0059] Common cold and influenza infections are inactivated in environments with high room temperature, high humidity, and high levels of ultraviolet light, but conversely, are easily activated in environments with low temperature, low humidity, and low levels of ultraviolet light.

[0060] 11 is a flowchart showing the process flow of this embodiment. The human detection unit 101 detects a person present in a space (S501). Next, the information acquisition unit 102 acquires the room temperature, humidity, and amount of ultraviolet light from a thermometer, a hygrometer, and an ultraviolet light meter installed in the room (S502). In this embodiment, the thermometer, the hygrometer, and the ultraviolet light meter are connected to the computer 10 by wire or wirelessly.

[0061] After the information acquisition unit 102 acquires the room temperature, humidity, and amount of ultraviolet rays, the infection risk determination unit 103 determines the infection risk based on the room temperature, humidity, and amount of ultraviolet rays. For example, if the room temperature is high (S503), humidity is high (S505), and amount of ultraviolet rays is high (S509), the infection risk is determined to be the lowest (S516). If the room temperature is high (S503), humidity is high (S505), and amount of ultraviolet rays is low (S509), the infection risk is determined to be low (S515). If the room temperature is high (S503), humidity is low (S505), and amount of ultraviolet rays is high (S508), the infection risk is determined to be slightly low (S514). If the room temperature is high (S503), humidity is low (S505), and amount of ultraviolet rays is low (S508), the infection risk is determined to be normal (S513). Similarly, if the room temperature is low (S503), the humidity is low (S504), and the amount of ultraviolet rays is low (S506), the risk of infection is determined to be highest (S510). If the room temperature is low (S503), the humidity is low (S504), and the amount of ultraviolet rays is high (S506), the risk of infection is determined to be high (S511). If the room temperature is low (S503), the humidity is high (S504), and the amount of ultraviolet rays is low (S507), the risk of infection is determined to be slightly high (S512). If the room temperature is low (S503), the humidity is high (S504), and the amount of ultraviolet rays is high (S507), the risk of infection is determined to be normal (S513).

[0062] The social distance range calculation unit 104 sets the social distance to 4.5 m when the risk of infection is determined to be the highest, 4 m when the risk of infection is determined to be high, and 3.5 m when the risk of infection is determined to be somewhat high. Also, when the risk of infection is determined to be normal, the social distance is set to 3 m. Similarly, when the risk of infection is determined to be somewhat low, the social distance is set to 2.5 m, when the risk of infection is determined to be low, and when the risk of infection is determined to be the lowest, the social distance is set to 1.5 m, or other predetermined values ​​(S517). The above social distances may be freely input by the administrator into the system as fixed values, or values ​​may be set in advance in the program.

[0063] In addition, in the flowchart of Fig. 11, the infection risk is divided into seven stages for judgment, but the number of stages may be reduced without being limited to this. For example, the number of stages may be five by regarding a slightly low infection risk as the same as a low infection risk, and a slightly high infection risk as the same as a high infection risk, and the number of judgment stages is not limited to the above.

[0064] 11, the order of judgment is room temperature, humidity, and amount of ultraviolet light, but the order may be amount of ultraviolet light, humidity, room temperature, and is not limited to the above. In this embodiment, three conditions (room temperature, humidity, and amount of ultraviolet light) are used as elements of the environmental conditions, but judgment may be made using only one or two of these elements.

[0065] There is also a method of using the amount of carbon dioxide as another factor. If a person emits a large amount of carbon dioxide into a space, the space is considered to be unventilated. If the amount of carbon dioxide exceeds a predetermined value, the risk of infection is determined to be high, and if it does not exceed the predetermined value, the risk of infection is determined to be low. A social distance range is set based on the judgment result. In this embodiment, the social distance is not set for each individual, but the social distance of all people present in the space is the same constant value. With the above method, an appropriate social distance range can be set by taking into account the environmental conditions in the space rather than setting the same social distance for all people in the space.

[0066] [Sixth embodiment] Next, another example applicable to the first embodiment will be described. For example, in the event of an emergency such as a disaster, a shelter may be used. There are limited places to evacuate to in an emergency, and it may be difficult to use a shelter while taking into account the risk of infection. In this example, a method for determining the spatial infection risk of a shelter used in an emergency will be described in detail.

[0067] In this embodiment, in addition to the imaging device 20 that captures images of the interior of the space, an imaging device 21 (not shown) is also installed at the entrance of the evacuation shelter. In addition, a face matching unit 107 (not shown) and a personal information registration unit 108 (not shown) are provided as additional functions of the computer 10 used in the first embodiment. The imaging device 21 captures a face image of a person before entering the evacuation shelter. The imaging device 20 and the computer 10 can communicate with each other via a wired or wireless communication unit. The face image captured by the imaging device 21 is transmitted to the personal information registration unit 108 of the computer 10. The personal information registration unit 108 inputs and registers personal information such as the name of the person entering the evacuation shelter, the presence or absence of underlying diseases, the presence or absence of cold symptoms, the address, and the telephone number in addition to the face image. Here, the underlying disease refers to chronic heart disease, respiratory disease, kidney disease, diabetes being treated with insulin, neurological disease or neuromuscular disease associated with immune abnormality, chromosomal abnormality, etc. There is a concern that a person with such an underlying disease may become seriously ill if he or she contracts an infectious disease such as COVID-19.

[0068] 12 is a flowchart showing the flow of processing in this embodiment. The imaging device 21 installed at the entrance of the evacuation shelter acquires a face image of a person entering the evacuation shelter and transmits the face image to the personal information registration unit 108 (S601). The personal information registration unit 108, which has received the face image, acquires and registers the personal information of the person entering the evacuation shelter and information on the presence or absence of underlying diseases and cold symptoms using an input unit such as a keyboard or mouse of the computer 10 (S602). The person detection unit 101 detects a person present in the space, and the face matching unit 107 matches the face information of the detected person with the face image registered in the personal information registration unit 108 (S603).

[0069] The infection risk determination unit 103 refers to the personal information registration unit 108, and if the matched person has an underlying disease or cold symptoms, it determines that the infection risk is high, and if the matched person does not have an underlying disease or cold symptoms, it determines that the infection risk is low (S604). The social distance range calculation unit 104 sets a predetermined value, such as a social distance of 5 m when the infection risk is determined to be high, and a social distance of 2 m when the infection risk is determined to be low (S605). The above social distance may be freely input by the administrator into the system as a fixed value, or a value may be set in the program in advance. The spatial infection risk described in the first embodiment is determined based on the social distance set for each individual.

[0070] As a result, it becomes easy to determine whether or not to allow additional people to enter the evacuation shelter while taking into account the spatial infection risk. In addition, by displaying the spatial infection risk on signage or the like, a person who has once registered personal information can determine whether or not to allow entry on his / her own without relying on an administrator. As a secondary effect, since face information is registered in this embodiment, if a family member or the like has a photo of a person who is in the evacuation shelter, it is also possible to confirm whether the person is in the evacuation shelter by using face recognition technology. Alternatively, a search may be performed using the name registered in the personal information registration unit 108. Furthermore, if information on various evacuation shelters, rather than just one, can be integrated, it becomes possible to grasp who is evacuating to which evacuation shelter.

[0071] [Seventh embodiment] The minimum configuration of the spatial infection risk determination system 4 in the present invention will be described with reference to Fig. 13. Fig. 13 is a diagram showing an example of the overall configuration of the spatial infection risk determination system 4 in this embodiment. The spatial infection risk determination system 4 includes a detection unit 401 and a determination unit 402.

[0072] The detection unit 401 detects people in a space for which the spatial infection risk is to be determined, using the imaging device 20. The determination unit 402 determines the spatial infection risk based on the floor area of ​​the space and the area of ​​a circle based on the distance for preventing infection of all people present in the space.

[0073] Next, the process flow of the minimum configuration of the spatial infection risk determination system 4 will be described with reference to Fig. 14. The detection unit 401 detects people in a space for which the spatial infection risk is to be determined using the imaging device 20 (S701). The determination unit 402 determines the spatial infection risk according to the floor area of ​​the space and the area of ​​a circle based on the distance for preventing infection of all people in the space (S702).

[0074] As a result, the space manager can use computer 10 to make a evidence-based judgment on the risk of infection in the space.

[0075] [Hardware configuration example] Next, an example of a hardware configuration for realizing the computer 10, the imaging device 20, the display device 30, and the spatial infection risk determination system (1, 4) in each of the above-mentioned embodiments will be described. Each functional unit of the computer 10, the imaging device 20, the display device 30, and the spatial infection risk determination system (1, 2) is realized by any combination of hardware and software, centering on at least one CPU (Central Processing Unit) of any computer, at least one memory, a program loaded into the memory, at least one storage unit such as a hard disk that stores the program, and a network connection interface. Those skilled in the art will understand that there are various modifications of this realization method and device. In addition to the program stored before the shipment of the device, the storage unit can also store a program downloaded from a storage medium such as an optical disk, a magneto-optical disk, or a semiconductor flash memory, or a server on the Internet.

[0076] The processor (1A) is an arithmetic processing device such as a CPU, a GPU (Graphics Processing Unit), or a microprocessor, and executes various programs and controls each part. That is, the processor (1A) reads out a program from the ROM (2A) and writes it into the RAM (2A). The program is executed using ROM (3A) as a work area. In the above embodiment, the program is stored in ROM (2A).

[0077] The ROM (2A) stores an execution program for causing the processor (1A) to execute a detection process for detecting people in a space and a determination process for determining an infection risk in the space based on the floor area of ​​the space and the area of ​​a circle based on the distance for preventing infection of an infectious disease, as well as data related to social distance ranges. The RAM (3A) temporarily stores programs or data as a working area.

[0078] The communication module (4A) realizes a function for the computer 10 to communicate with the imaging device 20 and the display device 30. In addition, when multiple computers 10 are installed, the communication module (4A) realizes a function for the computers to communicate with each other.

[0079] The display (5A) functions as a display unit, and receives user requests via a touch panel or mouse, etc., and displays responses from the spatial infection risk assessment system (1, 4). It also has the function of displaying an image with a superimposed social distance range and the spatial infection risk results.

[0080] The I / O (6A) includes interfaces for acquiring information from input devices, external devices, external storage units, external sensors, cameras, etc., and interfaces for outputting information to output devices, external devices, external storage units, etc. Examples of input devices include a touch panel, keyboard, mouse, microphone, camera, etc. Examples of output devices include a display, speaker, printer, lamp, etc. Examples of external sensors include a thermometer, hygrometer, ultraviolet ray amount measuring device, infrared sensor, carbon dioxide concentration meter, etc.

[0081] The configurations of the above-described embodiments may be combined or some of the components may be replaced. Furthermore, the configuration of the present invention is not limited to the above-described embodiments, and various modifications may be made without departing from the scope of the present invention. [Explanation of symbols]

[0082] 1 Spatial infection risk assessment system 10. Computers 20 Imaging device 30 Display device 101 Human detection unit 102 Information acquisition department 103 Infection Risk Assessment Department 104 Social Distance Range Calculation Unit 105 Spatial Infection Risk Assessment Department 106 Display processing unit 107 Face matching unit 108 Personal Information Registration Department 201 Video Acquisition Unit 301 Display section 4 Spatial infection risk assessment system 401 Detection unit 402 Judgment section D1 Semisphere 1A Processor 2A ROM 3A RAM 4A Communication Module 5A Display 6A I / O 7A Bus

Claims

1. A detection means for detecting a person from an image captured by an imaging device; A determination means for determining an infection risk in the space based on a floor area of ​​the space and an area of ​​a circle centered on the detected person and based on a distance for preventing infection of an infectious disease; Equipped with Spatial infection risk assessment system.

2. Further comprising a display means for displaying the circle around the person on a display device. The spatial infection risk determination system according to claim 1.

3. The circle based on the distance is a circle centered on the person, and the radius of the circle is a predetermined fixed value. A spatial infection risk determination system as described in claim 1 or 2.

4. The radius of the circle is set based on the height of the person. A spatial infection risk determination system as described in claim 1 or 2.

5. The radius of the circle is set based on at least one of the temperature, humidity, and amount of ultraviolet light in the space. A spatial infection risk determination system as described in claim 1 or 2.

6. The radius of the circle is set based on the presence or absence of a disease of the person. A spatial infection risk determination system as described in claim 1 or 2.

7. The radius of the circle is set based on the age of the person. A spatial infection risk determination system as described in claim 1 or 2.

8. The radius of the circle is set based on whether or not the person has a fever. A spatial infection risk determination system as described in claim 1 or 2.

9. A procedure for detecting a person in a space; and A procedure for determining an infection risk in the space according to a floor area of ​​the space and an area of ​​a circle based on a distance for preventing infection of an infectious disease; A spatial infection risk information processing method using a computer.

10. Computer processor A detection process for detecting a person in the space; A determination process for determining an infection risk in the space based on a floor area of ​​the space and an area of ​​a circle based on a distance for preventing infection of an infectious disease; A program for executing.

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