CN111507200A - Body temperature detection method, body temperature detection device and dual-optical camera - Google Patents
Body temperature detection method, body temperature detection device and dual-optical camera Download PDFInfo
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- 230000036760 body temperature Effects 0.000 title claims abstract description 76
- 238000001514 detection method Methods 0.000 title claims abstract description 67
- 238000001931 thermography Methods 0.000 claims abstract description 77
- 238000000034 method Methods 0.000 claims description 29
- 238000009529 body temperature measurement Methods 0.000 claims description 10
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The present disclosure provides a body temperature detection method, a body temperature detection apparatus, a dual-optical camera, an electronic device, and a computer-readable storage medium, wherein the body temperature detection method includes: acquiring a visible light image and a thermal imaging image of a target human body; based on the visible light image, carrying out face detection to obtain first face position information of the visible light image; determining second face position information in the thermal imaging image based on the first face position information; obtaining third face position information through a face regression model based on the second face position information; and obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information. The face detection is carried out through the visible light image, relatively accurate face position information is obtained, then the face position in the thermal imaging image is obtained, face regression is carried out on the face position part in the thermal imaging image, the temperature is determined based on the regression result, the calculation cost is reduced, and meanwhile, the accuracy rate is greatly improved.
Description
Technical Field
The present disclosure relates generally to the field of image processing, and more particularly to a body temperature detection method, a body temperature detection apparatus, a dual-optical camera, an electronic device, and a computer-readable storage medium.
Background
Currently, the body temperature of a person needs to be detected or monitored in many scenarios. The temperature measurement mode is generally divided into two modes, one mode is that a large amount of manual work is needed for screening through handheld contact type temperature measurement equipment such as a temperature gun, the efficiency is seriously influenced under the condition of large pedestrian flow and large density, and the risk of group infection is increased. The other type of the intelligent temperature measuring camera acquires the body temperature information of the pedestrian through the infrared camera, so that the body temperature of the pedestrian is automatically detected, but the temperature measuring error of the current temperature measuring camera is large, and the body temperature data of the person cannot be accurately acquired.
Disclosure of Invention
In order to solve the above problems in the prior art, a first aspect of the present disclosure provides a body temperature detecting method, wherein the method includes: acquiring a visible light image and a thermal imaging image of a target human body; based on the visible light image, carrying out face detection to obtain first face position information of the visible light image; determining second face position information in the thermal imaging image based on the first face position information; obtaining third face position information through a face regression model based on the second face position information; and obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
In one example, prior to determining second face location information in the thermographic image based on the first face location information, the method further comprises: the visible light image is aligned with the thermographic image.
In one example, aligning a visible light image with a thermographic image comprises: respectively determining a first characteristic point of the visible light image and a second characteristic point of the thermal imaging image through characteristic point detection; the thermographic image is aligned with the visible-light image by translation and/or scaling based on the first and second feature points.
In one example, determining second face position information in the thermal imaging image based on the first face position information comprises: obtaining expanded position information through size expansion based on the first face position information; and determining second face position information based on the expansion position information.
In one example, obtaining the third face position information through the face regression model based on the second face position information includes: obtaining the confidence of the position information of the third face; the method further comprises the following steps: and if the confidence coefficient is greater than the confidence coefficient threshold value, obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
In one example, obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information includes: determining a temperature measurement area of the target figure based on the third face position information; and determining the body temperature of the target person according to the temperature information of the thermal imaging image based on the temperature measuring area.
In one example, acquiring a visible light image and a thermographic image comprises: acquiring a visible light image through a visible light lens of the double-light camera; the thermographic image is acquired by the infrared lens of the dual-optical camera.
A second aspect of the present disclosure provides a body temperature detection device, the device comprising: the acquisition module is used for acquiring a visible light image and a thermal imaging image of a target human body; the detection module is used for carrying out face detection based on the visible light image and acquiring first face position information of the visible light image; the mapping module is used for determining second face position information in the thermal imaging image based on the first face position information; the regression module is used for obtaining third face position information through a face regression model based on the second face position information; and the temperature determining module is used for obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
A third aspect of the present disclosure provides a dual-light camera including: the visible light lens is used for acquiring a visible light image; the infrared lens is used for acquiring a thermal imaging image; the two-light camera is also used for body temperature detection by the body temperature detection method as in the first aspect.
A fourth aspect of the present disclosure provides an electronic device, comprising: a memory to store instructions; and a processor for invoking the instructions stored by the memory to perform the body temperature detection method of the first aspect.
A fifth aspect of the present disclosure provides a computer-readable storage medium having stored therein instructions which, when executed by a processor, perform the body temperature detection method as in the first aspect.
According to the body temperature detection method, the body temperature detection device, the dual-optical camera, the electronic equipment and the computer readable storage medium, face detection is carried out through the visible light image, relatively accurate face position information is obtained, then the face position in the thermal imaging image is obtained, face regression is carried out on the face position part in the thermal imaging image, the temperature is determined based on the regression result, and the accuracy rate is greatly improved while the calculation cost is reduced.
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The above and other objects, features and advantages of the embodiments of the present disclosure will become readily apparent from the following detailed description read in conjunction with the accompanying drawings. Several embodiments of the present disclosure are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which:
FIG. 1 shows a schematic flow diagram of a method of body temperature detection according to an embodiment of the present disclosure;
FIG. 2 shows a schematic flow chart of a method of body temperature detection according to another embodiment of the present disclosure;
FIG. 3 shows a schematic flow chart of a method of body temperature detection according to another embodiment of the present disclosure;
FIG. 4 shows a schematic flow chart of a method of body temperature detection according to another embodiment of the present disclosure;
FIG. 5 shows a schematic flow chart of a method of body temperature detection according to another embodiment of the present disclosure;
fig. 6 shows a schematic diagram of a body temperature detection device according to an embodiment of the present disclosure.
Fig. 7 shows a schematic view of a body temperature detection device according to another embodiment of the present disclosure.
Fig. 8 is a schematic diagram of an electronic device provided in an embodiment of the present disclosure.
In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts.
Detailed Description
The principles and spirit of the present disclosure will be described with reference to a number of exemplary embodiments. It is understood that these embodiments are given solely for the purpose of enabling those skilled in the art to better understand and to practice the present disclosure, and are not intended to limit the scope of the present disclosure in any way.
It should be noted that, although the expressions "first", "second", etc. are used herein to describe different modules, steps, data, etc. of the embodiments of the present disclosure, the expressions "first", "second", etc. are merely used to distinguish between different modules, steps, data, etc. and do not indicate a particular order or degree of importance. Indeed, the terms "first," "second," and the like are fully interchangeable.
In some related technologies, alignment of a visible light image and a temperature image needs to be completed through temperature measurement of a dual-optical camera, but due to differences of the placement positions of the cameras and parameters of the cameras, the two images cannot be aligned simultaneously, so that offset is generated during face position mapping, and extracted temperature data is inaccurate; or the two images are aligned by a manual alignment method, the two images must be aligned manually each time the two images are used, the efficiency is low, and the accuracy of manual alignment is not high.
In other related technologies, a base infrared camera is used for collecting a thermal imaging image, and face detection is directly performed on the thermal imaging image, but due to the fact that pixels of the thermal imaging image are low, face information in the thermal imaging image is not enough than visible light, and therefore face detection is prone to false detection and missing detection.
In order to solve the above problem, an embodiment of the present disclosure provides a body temperature detecting method 10, which may be used in a dual-optical camera having a visible light lens and an infrared lens, or in a terminal device such as a mobile phone or a computer, or in a cloud server, as shown in fig. 1, and includes: step S11-step S15. The above steps are described in detail below:
in step S11, a visible light image and a thermal image of the target human body are acquired.
In order to conveniently and accurately detect the body temperature of a target human body, a visible light image and a thermal imaging image of the target human body need to be acquired, the visible light image is mainly used for detecting the human body and determining the position of the human body due to high pixels and clear textures, and the thermal imaging image has temperature information and is mainly used for determining the temperature.
In one embodiment, a visible light image is acquired by a visible light lens of a dual-light camera; the thermographic image is acquired by the infrared lens of the dual-optical camera. In this embodiment, two different lenses through two optical cameras acquire visible light image and thermal imaging image respectively, because two lenses of two optical cameras are close to the setting, consequently the image position and the angle of shooing are close relatively, are convenient for align, and body temperature detection method 10 can directly be applied to two optical cameras, thereby convenient acquisition image, and when body temperature detection method 10 is applied to terminal equipment or high in the clouds server, can carry out the temperature measurement through receiving the image that comes from two optical cameras collection.
In other embodiments, images can be acquired by a visible light camera with a visible light lens and an infrared camera with an infrared lens, which are independently arranged, and then transmitted to the terminal device or the cloud server, and the temperature is detected by the body temperature detection method 10.
And step S12, performing face detection based on the visible light image, and acquiring first face position information of the visible light image.
The visible light image has clear texture and high pixel resolution, and whether the human face exists in the visible light image or not and the position of the human face can be relatively accurately detected through human face detection. In some embodiments, the face detection may be performed by a trained neural network, such as a Convolutional Neural Network (CNN), inputting the visible light image, or inputting a portion of the coarsely positioned visible light image, and outputting the first face position information. The first face position information may be a position and a size of a face frame in the visible light image, and may be expressed by [ x, y, w, h ], where x and y are coordinates in a horizontal direction and a vertical direction, respectively, and generally are coordinates of an upper left corner point of the face frame, and w and h are widths and heights of the face frame, respectively. Meanwhile, the confidence of the face frame, that is, the possibility that the face frame contains a face, may be expressed by [ x, y, w, h, s ], where s is the confidence of the face frame.
In step S13, second face position information in the thermal imaging image is determined based on the first face position information.
After the first face position information is determined on the visible light image through face detection, the first face position information is mapped to the thermal imaging image according to the coordinates and the image proportion on the basis of the position of the first face position information on the visible light image, and therefore second face position information of the thermal imaging image is determined. Since the visible light image and the thermal imaging image are images captured of one scene, particularly in the case of capturing through two adjacently disposed lenses of a dual-optical camera, the position information is close in the captured images of the two images. Thus, the first face position information may be mapped substantially into the thermographic image based on the position of the first face position information in the visible light image, and based on factors such as the pixel ratios of the two images.
In one embodiment, as shown in fig. 2, before step S13, the body temperature detecting method 10 further includes step S16 of aligning the visible light image with the thermal imaging image. In this embodiment, before the second face position information is determined on the thermal imaging image, the two images are roughly aligned, so that the problems of image content offset and different pixel resolutions of the visible light image and the thermal imaging image are solved, and the second face position information can be determined more accurately, that is, the position of the face in the thermal imaging image is determined based on the face detected in the visible light image.
In one embodiment, as shown in fig. 3, step S16 may include: step S161, respectively determining a first characteristic point of the visible light image and a second characteristic point of the thermal imaging image through characteristic point detection; and step S162, aligning the thermal imaging image with the visible light image through translation and/or zooming based on the first characteristic point and the second characteristic point. In this embodiment, feature points in the visible light image and the thermal imaging image may be respectively detected through a network model, where the feature points may be a first feature point and a second feature point in the two images determined in a Scale-invariant feature transform (SIFT) manner, a Speeded-Up Robust Features (SURF) manner, or another manner, and the first feature point and the second feature point may be multiple. And matching the first characteristic points and the second characteristic points of the two images in a characteristic point matching mode to obtain corresponding calculation matrixes. Generally, the thermal imaging image and the thermal imaging image are acquired without significant difference in rotation, so that the matrix can be restricted to only perform translation and scaling operations without rotation, and the thermal imaging image and the visible light image can be aligned by performing translation, scaling or both translation and scaling on one or both of the thermal imaging image and the visible light image. By the mode, the alignment operation can be performed through the model, the efficiency is high, the accuracy is high, and meanwhile the second face position information can be determined in the thermal imaging image more accurately through the aligned image.
In one embodiment, as shown in fig. 4, step S13 may include: step S131, based on the first face position information, obtaining expanded position information through size expansion; step S132, based on the enlarged position information, determines second face position information. In this embodiment, after the first face position information is obtained by performing face detection on the visible light image, a size expansion (resize) operation may be performed to expand the obtained face frame, that is, the obtained face frame may be expressed as converting [ x, y, w, h ] into [ x ', y', w ', h' ], and the face frame may be expanded to the periphery by taking the center of the face frame as the center, for example, by 10% or 20% or other sizes. And mapping the image to a thermal imaging image according to the mode based on the expanded position information obtained after expansion to obtain second face position information, wherein the mapping can be carried out after the alignment, so that the mapping is more convenient and accurate. The range is expanded through size expansion, so that when a certain deviation exists between the thermal imaging image and the visible light image, the second face position information determined in the thermal imaging image can be ensured as much as possible, namely, the face detected in the visible light image is contained in the face frame determined in the thermal imaging image, and the accuracy and the reliability are improved.
And step S14, obtaining third face position information through a face regression model based on the second face position information.
And in the thermal imaging image, roughly determining the face position according to the second face position information, and performing face regression on the face position determined by the second face position information, namely the image in the face frame determined in the thermal imaging image through a face regression model, so as to obtain third face position information. The third face position information can be a more accurate face frame, and the positions of four sides of the face frame cling to the contour extension of the face, so that the face position is accurately positioned. The human face regression model can conveniently and quickly locate the human face, and because the second human face position information is determined through the visible light image, the second human face position information does not need to be located in the full image range of the thermal imaging image, only the foreground is considered, and the influence brought by the background is ignored, so that the calculation cost is reduced, and the accuracy is also improved. In some embodiments, a face detection model may be used instead of the face regression model, which may increase a lot of cost and may not be accurate in the case of low resolution and poor texture quality of the thermal imaging image.
And step S15, obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the position information of the third face.
The third face position information obtained by face regression in the thermal imaging image can accurately position the face, and the body temperature of the target person is determined by combining the temperature information in the thermal imaging image.
In one embodiment, step S15 may include: determining a temperature measurement area of the target figure based on the third face position information; and determining the body temperature of the target person according to the temperature information of the thermal imaging image based on the temperature measuring area. In this embodiment, a temperature measurement area may be further determined according to the determined third face position information, for example, a face forehead area for temperature measurement is obtained through coordinates, and then, in combination with temperature information of the area, an accurate body temperature of a human body may be determined through a mean value, a peak value, or other manners.
According to the embodiment of the invention, the human face approximate position can be efficiently and accurately obtained by detecting the human face in the visible light image, and the human face position in the thermal imaging image is determined based on the human face approximate position, so that the background can be ignored, the accurate human face position can be obtained only by aiming at the foreground with the human face image through the human face regression model, and the accurate human body temperature can be obtained by combining the temperature information. The body temperature detection method 10 can accurately and efficiently acquire the body temperature of a human body.
The body temperature detection method 10 disclosed by the present disclosure may further combine with threshold judgment, for example, when the obtained body temperature of the target person is higher than the threshold, for example, if the obtained body temperature is higher than 37.5 ℃, prompt and other operations are performed, so as to conveniently and quickly perform troubleshooting on the fever staff.
In an embodiment, as shown in fig. 5, step S14 may further include: and obtaining the confidence of the position information of the third face. And when the face regression model carries out face regression to obtain third face position information, the confidence coefficient of the third face position information can be obtained, and the probability value containing the face is determined in a face frame determined according to the third face position information. The body temperature detection method 10 may further include: step S17, determining whether the confidence level is greater than the confidence level threshold, if so, performing step S15, that is, obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the position information of the third face, and if not, performing step S15, that is, not performing temperature detection. When the confidence coefficient is higher than the confidence coefficient threshold value, the human face can be judged to be present, so that the human body temperature can be further determined based on the third human face position information and the temperature information obtained through regression. And under the condition that the confidence coefficient does not exceed the confidence coefficient threshold, namely the position corresponding to the third face position information does not comprise the face, at the moment, the data obtained by temperature detection is inaccurate, and the subsequent misoperation, false alarm and other consequences can be caused, so that the temperature detection is not carried out.
Based on the same inventive concept, the present disclosure further provides a body temperature detecting device 100, as shown in fig. 6, the body temperature detecting device 100 includes: an obtaining module 110, configured to obtain a visible light image and a thermal imaging image of a target human body; the detection module 120 is configured to perform face detection based on the visible light image, and acquire first face position information of the visible light image; a mapping module 130, configured to determine second face position information in the thermal imaging image based on the first face position information; the regression module 140 is configured to obtain third face position information through a face regression model based on the second face position information; and the temperature determining module 150 is configured to obtain the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
In one example, as shown in fig. 7, the body temperature detection device 100 further includes: an alignment module 160 for aligning the visible light image with the thermal imaging image before the mapping module 130 performs the determining of the second face position information in the thermal imaging image based on the first face position information.
In one example, the alignment module 160 is further configured to: respectively determining a first characteristic point of the visible light image and a second characteristic point of the thermal imaging image through characteristic point detection; the thermographic image is aligned with the visible-light image by translation and/or scaling based on the first and second feature points.
In one example, the mapping module 130 is further configured to: obtaining expanded position information through size expansion based on the first face position information; and determining second face position information based on the expansion position information.
In one example, the regression module 140 is further configured to: obtaining the confidence of the position information of the third face; if the confidence is greater than the confidence threshold, the temperature determination module 150 obtains the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
In one example, the determine temperature module 150 is further configured to: determining a temperature measurement area of the target figure based on the third face position information; and determining the body temperature of the target person according to the temperature information of the thermal imaging image based on the temperature measuring area.
In one example, the obtaining module 110 is configured to: acquiring a visible light image through a visible light lens of the double-light camera; the thermographic image is acquired by the infrared lens of the dual-optical camera.
With regard to the body temperature detecting device 100 in the above-mentioned embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Based on the same inventive concept, the present disclosure also provides a dual-optical camera, including: the visible light lens is used for acquiring a visible light image; the infrared lens is used for acquiring a thermal imaging image; the two-optical camera is also used for body temperature detection by the body temperature detection method 10 of any of the foregoing embodiments. Thereby being capable of conveniently, accurately and efficiently detecting the body temperature of the personnel.
As shown in fig. 8, one embodiment of the present disclosure provides an electronic device 200. The electronic device 200 includes a memory 201, a processor 202, and an Input/Output (I/O) interface 203. The memory 201 is used for storing instructions. And the processor 202 is used for calling the instructions stored in the memory 201 to execute the body temperature detection method of the embodiment of the disclosure. The processor 202 is connected to the memory 201 and the I/O interface 203, respectively, for example, via a bus system and/or other connection mechanism (not shown). The memory 201 may be used to store programs and data, including the programs of the body temperature detection method according to the embodiments of the present disclosure, and the processor 202 executes various functional applications and data processing of the electronic device 200 by executing the programs stored in the memory 201.
The processor 202 in the embodiment of the present disclosure may be implemented in at least one hardware form of a Digital Signal Processor (DSP), a Field-Programmable Gate Array (FPGA), a Programmable logic Array (Programmable L organic Array, P L a), and the processor 202 may be one or a combination of several of a Central Processing Unit (CPU) or other forms of Processing units with data Processing capability and/or instruction execution capability.
In the embodiment of the present disclosure, the I/O interface 203 may be used to receive input instructions (e.g., numeric or character information, and generate key signal inputs related to user settings and function control of the electronic apparatus 200, etc.), and may also output various information (e.g., images or sounds, etc.) to the outside. The I/O interface 203 in the disclosed embodiments may include one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a mouse, a joystick, a trackball, a microphone, a speaker, a touch panel, and the like.
It is to be understood that although operations are depicted in the drawings in a particular order, this is not to be understood as requiring that such operations be performed in the particular order shown or in serial order, or that all illustrated operations be performed, to achieve desirable results. In certain environments, multitasking and parallel processing may be advantageous.
The methods and apparatus related to embodiments of the present disclosure can be accomplished with standard programming techniques with rule-based logic or other logic to accomplish the various method steps. It should also be noted that the words "means" and "module," as used herein and in the claims, is intended to encompass implementations using one or more lines of software code, and/or hardware implementations, and/or equipment for receiving inputs.
Any of the steps, operations, or procedures described herein may be performed or implemented using one or more hardware or software modules, alone or in combination with other devices. In one embodiment, the software modules are implemented using a computer program product comprising a computer readable medium containing computer program code, which is executable by a computer processor for performing any or all of the described steps, operations, or procedures.
The foregoing description of the implementations of the disclosure has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of the disclosure. The embodiments were chosen and described in order to explain the principles of the disclosure and its practical application to enable one skilled in the art to utilize the disclosure in various embodiments and with various modifications as are suited to the particular use contemplated.
Claims (11)
1. A method of body temperature detection, wherein the method comprises:
acquiring a visible light image and a thermal imaging image of a target human body;
performing face detection based on the visible light image to acquire first face position information of the visible light image;
determining second face position information in the thermal imaging image based on the first face position information;
obtaining third face position information through a face regression model based on the second face position information;
and obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
2. The method of claim 1, wherein prior to said determining second face location information in the thermographic image based on the first face location information, the method further comprises:
aligning the visible light image with the thermographic image.
3. The method of claim 2, wherein said aligning the visible light image with the thermographic image comprises:
respectively determining a first characteristic point of the visible light image and a second characteristic point of the thermal imaging image through characteristic point detection;
aligning the thermographic image with the visible-light image by translation and/or zooming based on the first and second feature points.
4. The method of any of claims 1-3, wherein the determining second face location information in the thermographic image based on the first face location information comprises:
obtaining enlarged position information through size expansion based on the first face position information;
and determining the second face position information based on the expansion position information.
5. The method of claim 1, wherein,
based on the second face position information, obtaining third face position information through a face regression model, wherein the third face position information comprises: obtaining the confidence of the third face position information;
the method further comprises the following steps:
and if the confidence coefficient is greater than a confidence coefficient threshold value, obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
6. The method of claim 1, wherein,
the obtaining of the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information includes:
determining a temperature measurement area of the target figure based on the third face position information;
and determining the body temperature of the target person according to the temperature information of the thermal imaging image based on the temperature measuring area.
7. The method of claim 1, wherein said acquiring visible light images and thermographic images comprises:
acquiring the visible light image through a visible light lens of a dual-light camera;
acquiring the thermal imaging image through an infrared lens of the dual-optical camera.
8. A body temperature sensing device, wherein the device comprises:
the acquisition module is used for acquiring a visible light image and a thermal imaging image of a target human body;
the detection module is used for carrying out face detection based on the visible light image and acquiring first face position information of the visible light image;
a mapping module for determining second face location information in the thermal imaging image based on the first face location information;
the regression module is used for obtaining third face position information through a face regression model based on the second face position information;
and the temperature determining module is used for obtaining the body temperature of the target person according to the temperature information of the thermal imaging image based on the third face position information.
9. A dual-light camera, wherein the dual-light camera comprises:
the visible light lens is used for acquiring a visible light image;
the infrared lens is used for acquiring a thermal imaging image;
the dual-optical camera is also used for body temperature detection by the body temperature detection method according to any one of claims 1 to 7.
10. An electronic device, wherein the electronic device comprises:
a memory to store instructions; and
a processor for invoking the memory-stored instructions to perform a body temperature detection method according to any one of claims 1-7.
11. A computer readable storage medium having stored therein instructions which, when executed by a processor, perform the method of body temperature detection according to any one of claims 1-7.
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