Method for identifying fever crowd, electronic equipment, storage medium and computer program product
The temperature data is obtained through the thermal imaging module of smart glasses, the target temperature difference is determined and the temperature calibration is performed, which solves the problem of inaccurate distance when measuring body temperature of smart glasses, and accurately recognizes the people with fever.
Patent Information
- Application Number
- CN202411553115.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-01
- Publication Date
- 2025-02-11
AI Technical Summary
When measuring body temperature of smart glasses, due to the large distance between the wearer and the person being measured, the body temperature data collected by the thermal imaging module is inaccurate and cannot effectively identify the fever population.
Thermal imaging picture and temperature data of multiple target areas are obtained through the thermal imaging module, the target temperature difference is determined, and the temperature calibration is performed with the target temperature difference and reference temperature, and the maximum value of the abnormal temperature is output to identify the heated population.
Through the temperature calibration of relative values, the problem of absolute value inaccuracy caused by distance is avoided, and the accurate identification of people with fever is achieved.
Smart Images
Figure CN119418119A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of smart wearable technology, and in particular to a method for identifying people with fever, an electronic device, a computer-readable storage medium, and a computer program product. Background Art
[0002] With the development of AR (Augmented Reality) technology, AR glasses have been widely used. At present, the biggest role of AR glasses is to achieve good information display effects by superimposing virtual display images in daily life applications such as voice translation, image recognition, and navigation. In view of the defect that the use of artificial temperature guns to detect high-fever people may cause the measurement person to be infected, the relevant plan proposes to use smart glasses with thermal imaging acquisition components to directly collect individual temperatures and prompt when abnormal temperatures are found.
[0003] However, the body temperature data collected directly by the thermal imaging acquisition component of the related solution may be inaccurate due to the large distance between the wearer of the smart glasses and the person being measured. In this case, it is impossible to effectively use smart glasses to identify people with fever. Summary of the invention
[0004] The purpose of the embodiments of the present application is to provide a method for identifying people with fever, and an electronic device, a storage medium, and a computer program product, which are used to avoid the problem of inaccurate absolute values caused by distance when the thermal imaging module collects temperature, and to perform temperature calibration with accurate relative values, thereby achieving effective identification of people with fever.
[0005] On the one hand, the present application provides a method for identifying people with fever, which is applied to smart glasses, wherein the smart glasses are equipped with a thermal imaging module, including:
[0006] Acquire a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module;
[0007] determining a target temperature difference based on the temperature data of the plurality of target areas;
[0008] Determine the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature;
[0009] The output shows the thermal imaging picture and the maximum abnormal temperature value.
[0010] In one embodiment, the smart glasses are equipped with a body temperature sensor module. Before acquiring the thermal imaging picture and the temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module, the method further includes:
[0011] The body temperature sensor module collects the wearer's body temperature data and determines whether the body temperature data exceeds the upper limit of normal body temperature;
[0012] If not, executing the step of acquiring the thermal imaging picture and the temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module;
[0013] If exceeded, the process ends.
[0014] In one embodiment, the method further comprises:
[0015] The wearer's body temperature data is used as the reference temperature.
[0016] In one embodiment, before determining the target temperature difference based on the temperature data of the plurality of target areas, the method includes:
[0017] Determine whether each target area in the thermal imaging image is an area where a person is located;
[0018] If all target areas are not areas where people are located, or only one target area is an area where people are located, return to the step of obtaining a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module;
[0019] If at least two target areas are areas where people are located, based on the temperature data of the areas where people are located, the step of determining the target temperature difference based on the temperature data of the multiple target areas is continued.
[0020] In one embodiment, determining the target temperature difference based on the temperature data of the plurality of target areas includes:
[0021] Determine whether the initial temperature difference between the highest temperature and the lowest temperature in the multiple temperature data is greater than a preset temperature difference threshold;
[0022] If the initial temperature difference is greater than the temperature difference threshold, filter out temperature data with the smallest specified ratio from the plurality of temperature data, and calculate a target average of the plurality of filtered temperature data;
[0023] The difference between the highest temperature in the plurality of temperature data and the target average is calculated as the target temperature difference.
[0024] In one embodiment, the step of determining the highest abnormal temperature value exceeding the upper limit of normal body temperature in a crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature includes:
[0025] The target temperature difference is added to the reference temperature to obtain the maximum abnormal temperature value.
[0026] In one embodiment, the method further comprises:
[0027] If the initial temperature difference is not greater than the temperature difference threshold, filter out the temperature data within a specified numerical interval from the multiple temperature data, and calculate the target average of the remaining temperature data; wherein the specified numerical interval is from a specified left endpoint to the highest temperature of the multiple temperature data, and the specified left endpoint is determined by the highest temperature of the multiple temperature data and a preset interval length;
[0028] The difference between the highest temperature in the plurality of temperature data and the target average is calculated as the target temperature difference.
[0029] In one embodiment, the step of determining the highest abnormal temperature value exceeding the upper limit of normal body temperature in a crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature includes:
[0030] Adding the target temperature difference to the reference temperature, and determining whether the added result exceeds the upper limit of normal body temperature;
[0031] If the addition result exceeds the upper limit of normal body temperature, the addition result is used as the highest abnormal temperature value;
[0032] If the addition result does not exceed the upper limit of normal body temperature, return to the step of acquiring the thermal imaging picture and the temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module.
[0033] On the other hand, the present application provides an electronic device, the electronic device comprising:
[0034] processor;
[0035] a memory for storing processor-executable instructions;
[0036] Wherein, the processor is configured to execute the above-mentioned method for identifying people with fever.
[0037] Furthermore, the present application provides a computer-readable storage medium, which stores a computer program. The computer program can be executed by a processor to complete the above-mentioned method for identifying people with fever.
[0038] In addition, the present application provides a computer program product, including a computer program / instructions, which implement the above-mentioned method for identifying people with fever when executed by a processor.
[0039] In order to solve the problem of inaccurate body temperature data collected by the thermal imaging acquisition component due to the large distance between the wearer of smart glasses and the measured person in the related solutions, the present application scheme determines the target temperature difference through multiple temperature data in the thermal imaging picture, and can effectively extract the difference between the highest temperature of the people in the crowd in the picture and the average of the normal body temperature. This difference is not affected by the distance as a relative value and is relatively accurate. Furthermore, the actual highest temperature of the people indicated in the picture can be limitedly determined by the target difference and the reference temperature, and then the abnormal temperature maximum value exceeding the upper limit of the normal body temperature can be determined by the actual highest temperature, and the thermal imaging picture and the abnormal temperature maximum value are output and displayed. It can be seen that the recognition process of this scheme effectively avoids the problem of inaccurate absolute values caused by distance when the thermal imaging module collects temperature, and realizes the effective identification of people with fever with accurate relative values. BRIEF DESCRIPTION OF THE DRAWINGS
[0040] In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings required for use in the embodiments of the present application are briefly introduced below.
[0041] Figure 1 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application;
[0042] Figure 2 A schematic diagram of a flow chart of a method for identifying people with fever provided in an embodiment of the present application;
[0043] Figure 3 A schematic diagram of a screening process of thermal imaging images provided in an embodiment of the present application;
[0044] Figure 4 A schematic flow chart of a method for determining a target temperature difference provided in an embodiment of the present application;
[0045] Figure 5 A schematic flow chart of a method for determining a target temperature difference provided in another embodiment of the present application;
[0046] Figure 6 A schematic flow chart of a method for determining a maximum abnormal temperature value provided in an embodiment of the present application;
[0047] Figure 7 This is a block diagram of a device for identifying people with fever provided in one embodiment of the present application. DETAILED DESCRIPTION
[0048] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.
[0049] Similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.
[0050] like Figure 1 As shown, this embodiment provides an electronic device 1, including: at least one processor 11 and a memory 12, Figure 2 A processor 11 is taken as an example. The processor 11 and the memory 12 are connected via a bus 10. The memory 12 stores instructions that can be executed by the processor 11. The instructions are executed by the processor 11 so that the electronic device 1 can execute all or part of the process of the method in the following embodiment. In one embodiment, the electronic device 1 can be smart glasses for executing the method for identifying people with fever.
[0051] The memory 12 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.
[0052] The present application also provides a computer-readable storage medium, which stores a computer program. The computer program can be executed by the processor 11 to complete the method for identifying people with fever provided in the present application.
[0053] The present application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the method for identifying people with fever provided in the present application.
[0054] See also Figure 2 , is a flow chart of a method for identifying people with fever provided in an embodiment of the present application, such as Figure 2 As shown, the method may include the following steps 210 to 240.
[0055] Step 210: Acquire a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through a thermal imaging module.
[0056] This solution is applied to smart glasses with AR function. The smart glasses are equipped with a thermal imaging module, which can generate thermal imaging pictures of the scene within the field of view of the smart glasses and monitor the temperature data of multiple target areas in the thermal imaging pictures.
[0057] In this solution, the fever population refers to a population that includes at least one fever patient. In this solution, the target area refers to the area in the picture where the temperature is in the preset high temperature range and the temperature data is continuous. Here, the left endpoint of the preset high temperature range is determined by the lower limit of the abnormal body temperature of the human body (for example: directly taking the lower limit of the abnormal body temperature of 35°C as the left endpoint, or subtracting the lower limit of the abnormal body temperature from the preset constant to get the left endpoint), and the right endpoint is determined by the upper limit of the abnormal body temperature of the human body (for example: directly taking the upper limit of the abnormal body temperature of 41.4°C as the right endpoint, or adding the upper and lower limits of the abnormal body temperature to get the right endpoint).
[0058] When the wearer wears the smart glasses, the smart glasses can obtain thermal imaging pictures and temperature data of multiple target areas in the thermal imaging pictures through the thermal imaging module.
[0059] Step 220: Determine a target temperature difference based on the temperature data of multiple target areas.
[0060] The multiple target areas in the thermal imaging image can be regarded as areas where people are located, and the temperature data corresponding to the target areas are recorded as the temperature data of the people in the target areas.
[0061] The target temperature difference can be determined by the temperature data of multiple persons in the thermal imaging picture. Here, the target temperature difference represents the temperature difference between the average normal body temperature of multiple persons in the thermal imaging picture and the highest temperature of all persons.
[0062] Step 230: Determine the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature.
[0063] The reference temperature is a temperature that is a standard value of normal body temperature and can be configured based on experience. For example, the reference temperature is 36°C.
[0064] The upper limit of normal body temperature is the highest value of body temperature in a healthy state of a human body. For example, the upper limit of normal body temperature is 37.5°C.
[0065] After the target temperature difference is obtained, the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging picture can be determined according to the target temperature difference and the reference temperature. The highest abnormal temperature value exceeds the upper limit of normal body temperature and is the highest body temperature of the people in the crowd indicated by the thermal imaging picture.
[0066] Step 240: Output and display the thermal imaging image and the maximum abnormal temperature value.
[0067] If the highest abnormal temperature value can be determined, it means that there are patients with fever in the crowd indicated by the thermal imaging picture. At this time, the aforementioned thermal imaging picture and the highest abnormal temperature value can be output through the AR function of the smart glasses, so as to prompt the wearer to stay away from the crowd indicated by the thermal imaging picture to avoid infection.
[0068] Through the above measures, in order to solve the problem of inaccurate body temperature data collected by the thermal imaging acquisition component due to the large distance between the wearer of smart glasses and the measured person in the related scheme, this scheme can effectively extract the difference between the highest temperature of the people in the crowd in the picture and the average of the normal body temperature by determining the target temperature difference through multiple temperature data in the thermal imaging picture. This difference is not affected by the distance as a relative value and is relatively accurate. Furthermore, the actual highest temperature of the people indicated in the picture can be limitedly determined by the target difference and the reference temperature, and then the abnormal temperature maximum value exceeding the upper limit of the normal body temperature can be determined by the actual highest temperature, and the thermal imaging picture and the abnormal temperature maximum value are output and displayed. It can be seen that the recognition process of this scheme effectively avoids the problem of inaccurate absolute value caused by distance when the thermal imaging module collects temperature, and performs temperature calibration with accurate relative values, thereby realizing the effective identification of people with fever.
[0069] In one embodiment, the smart glasses are equipped with a body temperature sensor module, which can collect the wearer's own body temperature data.
[0070] Before executing step 210, the smart glasses can collect the wearer's body temperature data through the body temperature sensor module and determine whether the body temperature data exceeds the upper limit of normal body temperature. On the one hand, if the body temperature data does not exceed the upper limit of normal body temperature, it means that the wearer himself does not have a fever. At this time, step 210 can be executed to start the identification process of people with fever, so as to timely discover and stay away from people with fever through smart glasses to prevent the wearer from being infected by fever patients. On the other hand, if the body temperature data exceeds the upper limit of normal body temperature, it means that the wearer himself has a fever. At this time, it is not meaningful to identify fever patients. The process can be ended, thereby reducing power consumption and ensuring that the smart glasses can have a longer battery life.
[0071] In one embodiment, the smart glasses are equipped with a body temperature sensor module, and the body temperature data of the wearer collected by the body temperature sensor module can be used as the reference temperature for step 230. Since the body temperature of a person will fluctuate slightly with the ambient temperature, using the body temperature data of the wearer as the reference temperature can more accurately determine the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging image, compared with using a fixed reference temperature.
[0072] In one embodiment, there are not always people in the field of view of the wearer of the smart glasses, or the heat-generating objects in the field of view are not always people, so the data needs to be filtered. Figure 3 , is a schematic diagram of a screening process of thermal imaging images provided in an embodiment of the present application, such as Figure 3 As shown, before executing step 220, the currently acquired thermal imaging pictures can be screened through the following process from step 310 to step 330, so as to filter out thermal imaging pictures that do not need to execute the fever people identification process.
[0073] Step 310: Determine whether each target area in the thermal imaging image is an area where a person is located.
[0074] Smart glasses can use intelligent recognition algorithms to determine whether each target area in a thermal imaging picture is where a person is located. Here, the intelligent recognition algorithm can be an algorithm that can recognize people in the picture, such as a target detection algorithm, a classification algorithm, or an image segmentation algorithm. This recognition process can be implemented locally in the smart glasses or through a cloud server. This recognition process can be implemented directly based on the thermal imaging picture, or it can be implemented based on a photo taken at the same time as the thermal imaging picture.
[0075] Step 320: If all target areas are not areas where people are located, or if only one target area is an area where people are located, return to the step of obtaining a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module.
[0076] If all target areas are not areas where people are located, it means that there is no one in the thermal imaging picture. At this time, there is no need to process the thermal imaging picture, and the process can return to step 210 to re-collect new thermal imaging pictures and temperature data of multiple target areas in the thermal imaging pictures.
[0077] If there is only one target area where a person is located, and the other target areas are not areas where people are located, it means that there is only one person in the thermal imaging image, and the algorithm of the present application cannot effectively correct the temperature data of a single person. Therefore, the thermal imaging image is also not processed, and the process returns to step 210 to re-collect a new thermal imaging image and the temperature data of multiple target areas in the thermal imaging image.
[0078] In one embodiment, after determining not to process the current thermal imaging picture, the process may return to step 210 after a preset time delay to avoid the re-collected thermal imaging picture being similar to the current thermal imaging picture. Here, the preset time length may be configured based on experience, and illustratively, the preset time length may be one of 1.5 seconds, 1.8 seconds, 2 seconds, etc.
[0079] Step 330: If at least two target areas are areas where people are located, based on the temperature data of the areas where people are located, continue to perform the step of determining the target temperature difference based on the temperature data of multiple target areas.
[0080] If at least two of the multiple target areas in the thermal imaging image are areas where people are located, it means that there are people in the thermal imaging image, and step 220 can be continued. When executing step 220, the temperature data of the target areas that are not areas where people are located need to be filtered out and not processed.
[0081] Through the above measures, thermal imaging images that do not need to be processed can be filtered out, and temperature data that does not belong to people in the thermal imaging images can be filtered out, which is helpful for subsequent further identification processes.
[0082] In one embodiment, see Figure 4 , is a flow chart of a method for determining a target temperature difference provided in an embodiment of the present application, such as Figure 4 As shown, when executing step 220, the target temperature difference can be calculated through the following steps 410 to 430.
[0083] Step 410: Determine whether the initial temperature difference between the highest temperature and the lowest temperature in the plurality of temperature data is greater than a preset temperature difference threshold.
[0084] The temperature difference threshold is determined based on the upper limit of normal body temperature and the lower limit of normal body temperature, indicating the difference between the two. For example, the upper limit of normal body temperature is 37.5°C, the lower limit of normal body temperature is 36°C, and the temperature difference threshold is 1.5°C.
[0085] For multiple temperature data belonging to people in the thermal imaging picture, select the highest temperature and the lowest temperature, and calculate the difference between the two as the initial difference. Further, determine whether the initial difference is greater than the temperature difference threshold. On the one hand, if the initial difference is not greater than the temperature difference threshold, it means that it is necessary to further determine whether there is a patient with fever. The specific processing logic is described below. On the other hand, if the initial difference is greater than the temperature difference threshold, it means that there must be a patient with fever in the crowd in the thermal imaging picture, and step 420 can be continued at this time.
[0086] Step 420: If the initial temperature difference is greater than the temperature difference threshold, filter out the temperature data with the smallest specified ratio from the multiple temperature data, and calculate the target average of the filtered temperature data.
[0087] The specified ratio can be configured based on experience. For example, the specified ratio can be any one of 50%, 45%, 40%, etc.
[0088] When the initial temperature difference is greater than the temperature difference threshold, multiple temperature data are arranged in order of size, and the temperature data with the smallest specified ratio is selected from small to large, and then the average of the selected temperature data is calculated as the target average. Here, the target average can represent the average of normal body temperatures of people in the thermal imaging image.
[0089] Step 430: Calculate the difference between the highest temperature in the plurality of temperature data and the target average as the target temperature difference.
[0090] After obtaining the target average, the difference between the highest temperature among the multiple temperature data and the target average can be calculated as the target difference.
[0091] Through the above measures, the target difference value can be determined when the initial temperature difference is greater than the temperature difference threshold.
[0092] In one embodiment, when the initial temperature difference is greater than the temperature difference threshold, since it has been determined that there must be a patient with fever in the crowd in the thermal imaging image, the sum of the target temperature difference and the reference temperature must exceed the upper limit of normal body temperature, and the sum can be used as the maximum abnormal temperature value.
[0093] In one embodiment, see Figure 5 , is a flow chart of a method for determining a target temperature difference provided by another embodiment of the present application, such as Figure 5 As shown, when executing step 220, the target temperature difference can be calculated through the following steps 510 to 520.
[0094] Step 510: If the initial temperature difference is not greater than the temperature difference threshold, filter out the temperature data within the specified numerical range from the multiple temperature data, and calculate the target average of the remaining temperature data; wherein the specified numerical range is from the specified left endpoint to the highest temperature of the multiple temperature data, and the specified left endpoint is determined by the highest temperature of the multiple temperature data and the preset interval length.
[0095] Here, the interval length is configured as needed. Exemplarily, the interval length can be any value such as 0.5, 0.6, 0.7, etc. The specified left endpoint can be obtained by subtracting the interval length from the highest temperature of the plurality of temperature data, and then the specified numerical interval can be determined based on the specified left endpoint and the highest temperature.
[0096] When the initial temperature difference is not greater than the temperature difference threshold, the temperature data within the specified data interval can be filtered out from the multiple temperature data, thereby filtering out the temperature data that is closer to the highest temperature. Further, the average is calculated for the remaining temperature data as the target average. Here, the target average can represent the average of normal body temperatures of people in the thermal imaging image.
[0097] Step 520: Calculate the difference between the highest temperature in the plurality of temperature data and the target average as the target temperature difference.
[0098] After obtaining the target average, the difference between the highest temperature among the multiple temperature data and the target average can be calculated as the target difference.
[0099] Through the above measures, the target temperature difference can be determined when the initial temperature difference is not greater than the temperature difference threshold.
[0100] In one embodiment, when the initial temperature difference is not greater than the temperature difference threshold, since it has not yet been determined that there is a patient with fever in the crowd in the thermal imaging image, it can be further determined whether there is a patient with fever. Figure 6 , is a flow chart of a method for determining a maximum abnormal temperature value provided in an embodiment of the present application, such as Figure 6 As shown, when executing step 230, the maximum abnormal temperature value can be determined through the following steps 610 to 630.
[0101] Step 610: Add the target temperature difference to the reference temperature, and determine whether the added result exceeds the upper limit of normal body temperature.
[0102] After obtaining the target temperature difference, the target temperature difference can be added to the reference temperature, and the addition result is the actual maximum body temperature in the thermal imaging image. Further, it can be determined whether the addition result exceeds the upper limit of normal body temperature.
[0103] Step 620: If the addition result exceeds the upper limit of normal body temperature, the addition result is used as the maximum abnormal temperature value.
[0104] Step 630: If the addition result does not exceed the upper limit of normal body temperature, return to the step of acquiring the thermal imaging picture and the temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module.
[0105] On the one hand, if the added result exceeds the upper limit of normal body temperature, it means that there are patients with fever in the population indicated by the thermal imaging image, and the added result can be used as the highest abnormal temperature value.
[0106] On the other hand, if the addition result does not exceed the upper limit of normal body temperature, it means that there is no fever patient in the crowd indicated by the thermal imaging picture, and the process can return to step 210 to restart a new round of fever crowd identification process. In one embodiment, the process can return to step 210 after a preset delay to avoid the re-collected thermal imaging picture being similar to the current thermal imaging picture.
[0107] Figure 7 is a block diagram of a device for identifying people with fever according to an embodiment of the present invention. Figure 7 As shown, the device may include:
[0108] An acquisition module 710, configured to acquire a thermal imaging picture and temperature data of a plurality of target areas in the thermal imaging picture through the thermal imaging module;
[0109] A first determination module 720, configured to determine a target temperature difference based on the temperature data of the plurality of target areas;
[0110] The second determination module 730 is used to determine the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging picture based on the target temperature difference and the reference temperature;
[0111] The output module 740 is used to output and display the thermal imaging picture and the maximum abnormal temperature value.
[0112] The implementation process of the functions and effects of each module in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method for identifying people with fever, and will not be repeated here.
[0113] In several embodiments provided in the present application, the disclosed devices and methods may also be implemented in other ways. The device embodiments described above are merely schematic, for example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram may represent a module, a program segment or a part of a code, and a module, a program segment or a part of a code contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of boxes in the block diagram and / or the flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.
[0114] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
[0115] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.
Claims
1. A method for identifying people with fever, applied to smart glasses, characterized in that: The smart glasses are equipped with a thermal imaging module, including: Acquire a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module; determining a target temperature difference based on the temperature data of the plurality of target areas; Determine the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature; The output shows the thermal imaging picture and the maximum abnormal temperature value.
2. The method according to claim 1, characterized in that The smart glasses are equipped with a body temperature sensor module. Before obtaining a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module, the method further includes: The body temperature sensor module collects the wearer's body temperature data and determines whether the body temperature data exceeds the upper limit of normal body temperature; If not, executing the step of acquiring the thermal imaging picture and the temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module; If exceeded, the process ends.
3. The method according to claim 2, characterized in that The method further comprises: The wearer's body temperature data is used as the reference temperature.
4. The method according to claim 1, characterized in that Before determining the target temperature difference based on the temperature data of the plurality of target areas, the method includes: Determine whether each target area in the thermal imaging image is an area where a person is located; If all target areas are not areas where people are located, or only one target area is an area where people are located, return to the step of obtaining a thermal imaging picture and temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module; If at least two target areas are areas where people are located, based on the temperature data of the areas where people are located, the step of determining the target temperature difference based on the temperature data of the multiple target areas is continued.
5. The method according to claim 1 or 4, characterized in that: The step of determining a target temperature difference based on the temperature data of the plurality of target areas comprises: Determine whether the initial temperature difference between the highest temperature and the lowest temperature in the multiple temperature data is greater than a preset temperature difference threshold; If the initial temperature difference is greater than the temperature difference threshold, filter out temperature data with the smallest specified ratio from the plurality of temperature data, and calculate a target average of the plurality of filtered temperature data; The difference between the highest temperature in the plurality of temperature data and the target average is calculated as the target temperature difference.
6. The method according to claim 5, characterized in that The step of determining the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature includes: The target temperature difference is added to the reference temperature to obtain the maximum abnormal temperature value.
7. The method according to claim 5, characterized in that The method further comprises: If the initial temperature difference is not greater than the temperature difference threshold, filter out the temperature data within a specified numerical interval from the multiple temperature data, and calculate the target average of the remaining temperature data; wherein the specified numerical interval is from a specified left endpoint to the highest temperature of the multiple temperature data, and the specified left endpoint is determined by the highest temperature of the multiple temperature data and a preset interval length; The difference between the highest temperature in the plurality of temperature data and the target average is calculated as the target temperature difference.
8. The method according to claim 7, characterized in that The step of determining the highest abnormal temperature value exceeding the upper limit of normal body temperature in the crowd indicated by the thermal imaging image based on the target temperature difference and the reference temperature includes: Adding the target temperature difference to the reference temperature, and determining whether the added result exceeds the upper limit of normal body temperature; If the addition result exceeds the upper limit of normal body temperature, the addition result is used as the highest abnormal temperature value; If the addition result does not exceed the upper limit of normal body temperature, return to the step of acquiring the thermal imaging picture and the temperature data of multiple target areas in the thermal imaging picture through the thermal imaging module.
9. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to execute the method for identifying people with fever as described in any one of claims 1-8.
10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program can be executed by a processor to complete the method for identifying people with fever as described in any one of claims 1-8.
11. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the method for identifying people with fever as described in any one of claims 1 to 8 is implemented.