Temperature detection methods, devices, electronic equipment, storage media and software products

Abstract

This disclosure provides a temperature detection method, apparatus, electronic device, storage medium, and program product, relating to the fields of infrared temperature measurement, intelligent temperature measurement, and intelligent robot technology. The temperature detection method includes: acquiring first pose information of a camera device detecting the temperature of a measured object during a first detection period, basic pose information of an infrared temperature measuring device during the first detection period, and second pose information of the camera device detecting the temperature of the measured object during a second detection period; determining the temperature measurement area of ​​the measured object in the reference image based on an image acquired by the camera device; converting the first position information of the temperature measurement area in the image coordinate system of the reference image into second position information in the world coordinate system based on the first pose information, basic pose information, and second pose information; and generating a detection command based on the second position information to instruct the infrared temperature measuring device to perform temperature detection on the measured object.

Description

Technical Field

[0001] This disclosure relates to the fields of infrared temperature measurement, intelligent temperature measurement, and intelligent robot technology, and more specifically to a temperature detection method, device, equipment, medium, and program product. Background Technology

[0002] Infrared thermometry is a non-contact temperature measurement method that uses the principle of infrared radiation to detect the temperature of an object's surface or interior. All objects above absolute zero emit infrared radiation energy, the intensity of which is related to the object's surface temperature. Infrared thermometers detect the infrared radiation energy emitted by an object's surface, and through a series of signal processing and algorithmic conversions, ultimately obtain the object's temperature value. This temperature measurement method has advantages such as being non-contact, fast, and safe, making it suitable for various applications.

[0003] While infrared human body temperature measurement technology provides a fast, non-contact method for measuring body temperature, it also has some limitations and drawbacks, such as the inability to accurately determine the temperature measurement area, which can lead to inaccurate temperature measurement results. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a temperature detection method, apparatus, device, medium, and program product.

[0005] According to a first aspect of this disclosure, a temperature detection method is provided, comprising:

[0006] Acquire the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period.

[0007] Based on the reference image obtained by the camera device from the image acquisition of the object under test, the temperature measurement area of ​​the object under test in the reference image is determined;

[0008] Based on the first pose information, the basic pose information, and the second pose information, the first position information of the temperature measurement area in the image coordinate system of the reference image is converted into the second position information of the temperature measurement area in the world coordinate system.

[0009] Based on the second location information, a detection command is generated to instruct the infrared temperature measuring device to perform temperature detection on the object being measured.

[0010] According to embodiments of this disclosure, converting the first position information of the temperature measurement area in the image coordinate system of the reference image into the second position information in the world coordinate system based on the first pose information, the basic pose information, and the second pose information includes:

[0011] Obtain the camera parameters of the imaging device;

[0012] The mapping relationship between the image coordinate system and the world coordinate system is constructed based on the first pose information, the basic pose information, the second pose information, and the camera parameters.

[0013] Based on the mapping relationship, the first position information of the temperature measurement area in the image coordinate system of the reference image is converted into the second position information of the temperature measurement area in the world coordinate system.

[0014] According to embodiments of this disclosure, constructing the mapping relationship between the image coordinate system and the world coordinate system based on the first pose information, the basic pose information, the second pose information, and camera parameters includes:

[0015] The translation vector t and rotation matrix R are determined based on the first pose information, the basic pose information, the second pose information, and the camera parameters.

[0016] Construct a coordinate transformation matrix T based on the translation vector t and the rotation matrix R, which serves as the mapping relationship.

[0017] According to embodiments of this disclosure, determining the temperature measurement area of ​​the object under test in the reference image obtained by the camera device from image acquisition of the object under test includes:

[0018] A fused image is obtained by fusing a reference image acquired by a camera device from the object under test with a thermal imaging image acquired from the object under test.

[0019] The temperature measurement area of ​​the object under test in the reference image is determined based on the fused image and the predetermined temperature measurement location.

[0020] According to embodiments of this disclosure, it further includes:

[0021] Based on the fused image, determine whether there are any obstructions in the temperature measurement area of ​​the object under test within the reference image;

[0022] If there are obstructions in the temperature measurement area, a first prompt message is generated.

[0023] According to embodiments of this disclosure, it further includes:

[0024] Determine whether the physiological state of the tested object is stable based on the fused images;

[0025] When the physiological state of the tested subject is unstable, a second prompt message is generated.

[0026] According to embodiments of this disclosure, it further includes:

[0027] Obtain the initial distance information between the infrared temperature measuring device and the object being measured;

[0028] Based on the first distance information, a movement command is generated to instruct the infrared temperature measuring device to move before performing temperature detection.

[0029] According to embodiments of this disclosure, generating a movement command based on first distance information to instruct the infrared temperature measuring device to move before performing temperature detection includes:

[0030] The second distance information is obtained based on the difference between the first distance information and the preset distance information;

[0031] Based on the second distance information, a movement command is generated to instruct the infrared temperature measuring device to move.

[0032] According to embodiments of this disclosure, it further includes:

[0033] Obtain the temperature detection results of the object being measured by the infrared thermometer;

[0034] A third prompt message is generated based on the detection results and the preset detection results.

[0035] A second aspect of this disclosure provides a temperature detection device, comprising:

[0036] The acquisition module is used to acquire the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period.

[0037] The judgment module is used to determine the temperature measurement area of ​​the object under test in the reference image obtained by the camera device from image acquisition of the object under test.

[0038] The conversion module is used to convert the first position information of the temperature measuring area in the image coordinate system of the reference image into the second position information of the temperature measuring area in the world coordinate system of the infrared temperature measuring device, based on the first pose information, the basic pose information, and the second pose information; and

[0039] The detection module is used to generate a detection command based on the second location information, which instructs the infrared temperature measuring device to perform temperature detection on the object being measured.

[0040] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0041] A fourth aspect of this disclosure also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0042] The fifth aspect of this disclosure also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0043] According to embodiments of this disclosure, by combining the visible light image acquired by the camera device, the temperature measurement area can be determined more accurately, facilitating the infrared temperature measurement device to more accurately emit the infrared temperature measurement beam to the temperature measurement area for temperature detection. Simultaneously, because the movement of the camera device during the search for the temperature measurement area will change its relative position with the infrared temperature measurement device, based on the first pose information of the camera device before searching for the temperature measurement area and the second pose information of the camera device after searching for and determining the temperature measurement area, along with the pose information of the infrared temperature measurement device, the determined temperature measurement area is transformed between coordinate systems, enabling the infrared temperature measurement device to perform position modulation. This ensures that the infrared temperature measurement beam can be accurately emitted to the determined temperature measurement area, avoiding temperature detection errors caused by inaccurate temperature measurement areas and improving the accuracy of temperature detection. Attached Figure Description

[0044] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0045] Figure 1 The illustration schematically depicts application scenarios of temperature detection methods, apparatus, devices, media, and program products according to embodiments of the present disclosure;

[0046] Figure 2 A flowchart illustrating a temperature detection method according to an embodiment of the present disclosure is shown schematically.

[0047] Figure 3 A flowchart illustrating the location information conversion according to an embodiment of the present disclosure is shown schematically.

[0048] Figure 4 A flowchart illustrating the construction of a transformation matrix according to an embodiment of this disclosure is shown schematically;

[0049] Figure 5 The schematic diagram illustrates the principle of the temperature detection terminal judgment process according to an embodiment of the present disclosure;

[0050] Figure 6 A schematic block diagram of a temperature detection device according to an embodiment of the present disclosure is shown.

[0051] Figure 7 A block diagram of an electronic device suitable for implementing a temperature detection method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0052] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0053] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0054] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0055] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0056] In the embodiments disclosed herein, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security and network security.

[0057] Embodiments of this disclosure provide a temperature detection method, including:

[0058] Acquire the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period.

[0059] Based on the reference image obtained by the camera device from the image acquisition of the object under test, the temperature measurement area of ​​the object under test in the reference image is determined;

[0060] Based on the first pose information, the basic pose information, and the second pose information, the first position information of the temperature measurement area in the image coordinate system of the reference image is converted into the second position information of the temperature measurement area in the world coordinate system.

[0061] Based on the second location information, a detection command is generated to instruct the infrared temperature measuring device to perform temperature detection on the object being measured.

[0062] Figure 1 The illustration schematically depicts an exemplary system architecture for the temperature detection method and apparatus to which embodiments of this disclosure can be applied. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0063] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a temperature measuring device 101, a network 102, and a server 103. The network 102 serves as a medium for providing a communication link between the temperature measuring device 101 and the server 103. The network 102 may include various connection types, such as wired and / or wireless communication links.

[0064] Temperature measuring device 101 interacts with server 103 via network 102 to receive or send messages, etc. Temperature measuring device 101 can be of various types, such as unmanned or manned mobile objects, such as unmanned robots or manned robots.

[0065] In the scenario of this disclosure embodiment, the temperature measuring device 101, in a certain application scenario, can interact with the server 103, for example, sending current location information, measurement information, environmental information, etc. to the server and requesting instructions to adjust the machine's operating status. The server 103 executes the temperature detection method of this disclosure embodiment, for example, first using an image recognition algorithm to identify the area location of the predetermined measurement part; further establishing an area location transformation relationship, converting the measurement area location information to a world coordinate system, and finally sending the final movement instruction to the temperature measuring device 101, so as to instruct the temperature measuring device 101 to adjust its position or the position of its internal infrared temperature measuring device according to the instruction, thereby performing temperature detection.

[0066] It should be noted that the temperature detection method provided in this embodiment can generally be executed by server 103. Correspondingly, the temperature detection device provided in this embodiment can generally be located in server 103. The temperature detection method provided in this embodiment can also be executed by a server or server cluster that is different from server 103 but capable of communicating with temperature measuring device 101 and / or server 103. Correspondingly, the temperature detection device provided in this embodiment can also be located in a server or server cluster that is different from server 103 but capable of communicating with temperature measuring device 101 and / or server 103. Alternatively, the temperature detection method provided in this embodiment can also be executed by electronic equipment in temperature measuring device 101, or by other terminal devices different from electronic equipment in temperature measuring device 101. Correspondingly, the temperature detection device provided in this embodiment can also be located in electronic equipment in temperature measuring device 101, or in other terminal devices different from electronic equipment in temperature measuring device 101.

[0067] It should be understood that Figure 1 The number of movable objects, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0068] Figure 2 The flowchart of a temperature detection method according to an embodiment of the present disclosure is illustrated. The main body implementing the temperature detection method in the embodiment of the present disclosure can be a temperature measuring device, a mobile temperature measuring robot, an intelligent robot, an unmanned robot or other mobile terminal, or more specifically, a processor within the aforementioned device.

[0069] like Figure 2 As shown, the method includes operations S201 to S204.

[0070] In operation S201, the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period are acquired.

[0071] In operation S202, the temperature measurement area of ​​the object under test is determined based on the reference image obtained by the camera device from image acquisition of the object under test.

[0072] In operation S203, based on the first pose information, the basic pose information, and the second pose information, the first position information of the temperature measuring area in the image coordinate system of the reference image is converted into the second position information of the temperature measuring area in the world coordinate system.

[0073] In operation S204, based on the second position information, a detection command is generated to instruct the infrared temperature measuring device to perform temperature detection on the object being measured.

[0074] According to embodiments of this disclosure, the camera device is a device capable of capturing visible light images, and can be of various types and models, such as miniature cameras, cameras integrating artificial intelligence algorithms, and variable focal length cameras. The infrared temperature measuring device is a device capable of measuring temperature using the principle of infrared radiation, such as point-type infrared thermometers, scanning infrared thermometers, multi-band infrared thermometers, long-wave infrared thermometers, mid-wave infrared thermometers, short-wave infrared thermometers, intelligent infrared thermometers integrating artificial intelligence algorithms, and infrared temperature measuring devices with infrared thermal imaging cameras, etc.

[0075] According to embodiments of this disclosure, the pose information includes the angle information and position information of the device, and both the camera device and the infrared temperature measuring device have the function of being movable up, down, left, and right; furthermore, the camera device and the infrared temperature measuring device have stepless rotation functions such as omnidirectional rotation or panoramic rotation.

[0076] According to embodiments of this disclosure, in operation S201, the camera device and infrared temperature measuring device in the first detection period can be the initial position before temperature detection or the position at the end of the previous temperature measurement. The second detection period can specifically be the detection period for determining the object being measured, or the period for collecting reference objects of the object being measured.

[0077] In some specific embodiments of this disclosure, when the camera device and the infrared temperature measuring device are set to return to their initial positions after each temperature measurement, the first pose information of the camera device and the basic pose information of the infrared temperature measuring device during the first detection period are fixed values, both of which are the initial position values.

[0078] Specifically, instructions to restore the initial position can be set, which can be located on the outside of the device containing the camera and infrared temperature measuring device, using methods such as buttons or voice prompts; or the equipment can be calibrated periodically, for example, by re-acquiring the first pose information of the camera and the basic pose information of the infrared temperature measuring device at fixed preset intervals such as every 5 days or every 30 days, and correcting the fixed value of the initial position; furthermore, the fixed value of the initial position can be corrected when the camera or infrared temperature measuring device is disassembled or modified, or when the temperature measuring device containing the camera and infrared device is opened.

[0079] In the embodiments of this disclosure, in operation S202, the user's authorization or consent is obtained before acquiring or collecting the user's personal information, such as facial images.

[0080] According to embodiments of this disclosure, in operation S202, the object under test can be identified by transmitting the acquired image to the backend processor in real time, or by directly identifying the object under test using a camera integrated with artificial intelligence algorithms, acquiring a reference image, and then transmitting it to the backend processor. Identification of the object under test can be achieved using image recognition technology, face recognition technology, object recognition technology, feature matching technology, etc., and can be implemented using edge detection algorithms, feature extraction algorithms, template matching algorithms, deep learning algorithms, etc. It should be noted that the algorithms mentioned in the embodiments of this disclosure should be considered exemplary, and their purpose is merely to illustrate the feasibility of implementing the technical solution of this application, but does not imply that the applicant has already used or necessarily used this solution.

[0081] Furthermore, after identifying and determining the object to be measured and acquiring its image, the temperature measurement area can be determined by transmitting the acquired reference image to the back-end processor, or the temperature measurement area can be determined directly by using a camera with integrated artificial intelligence algorithms.

[0082] More specifically, the temperature measurement area can be determined based on the actual application:

[0083] For example, in applications such as hospitals where temperature detection of people is required, the preset temperature measurement area can be set to the center of the forehead or the temple.

[0084] For example, in applications such as pet hospitals where temperature detection of animals is required, the preset temperature measurement area can be the inner ear or groin area.

[0085] According to an embodiment of this disclosure, in operation S203, the first position information and the second position information can be coordinate points (x, y) in the image coordinate system and the world coordinate system, respectively, or they can be feature points. Furthermore, the position information can also be represented as a region or boundary, for example, by defining the position of a temperature measurement area through a rectangle, polygon, or mask.

[0086] Furthermore, by utilizing camera intrinsics and transformation matrices, the first position information in the image coordinate system can be converted into the second position information in the world coordinate system. Alternatively, by combining the image coordinates and camera parameters from two or more viewpoints, the position of an object in the world coordinate system can be calculated through triangulation. Specific feature points in an image can be identified through image segmentation and feature matching, and corresponding points can be found in the two coordinate systems through feature matching. Furthermore, machine learning or deep learning models can be used to learn the mapping relationship between images and world coordinates from a large amount of data.

[0087] More specifically, since the camera device and the infrared temperature measuring device are two devices with a spatial position difference, the coordinates of the temperature measuring area in the reference image acquired by the camera device cannot be directly used in the infrared temperature measuring device. It is necessary to consider the relative position and relative angle differences between the two devices and convert and calculate them so that the infrared temperature measuring device can find the position information of the target temperature measuring area in the world coordinate system.

[0088] According to embodiments of this disclosure, after obtaining the second position information in operation S204, it can be used to guide the infrared temperature measuring device to adjust to a position where the temperature measuring beam can be directly shone on the temperature measuring area, and to issue instructions for transmitting and receiving infrared beams, as well as to calculate and convert the transmitted and received infrared intensity values ​​to obtain the final temperature measurement result.

[0089] Specifically, after receiving the reflected signal from the infrared beam, the temperature measuring device can amplify and filter the signal to remove noise, and then calculate the measured infrared radiation intensity into a temperature value based on Planck's radiation law and Stefan-Boltzmann's law. This process may involve calibrating the response characteristics of the infrared temperature measuring device and environmental conditions such as emissivity, ambient temperature, and humidity.

[0090] According to embodiments of this disclosure, by combining the visible light image acquired by the camera device, the temperature measurement area can be determined more accurately, facilitating the infrared temperature measurement device to more accurately emit the infrared temperature measurement beam to the temperature measurement area for temperature detection. Simultaneously, because the movement of the camera device during the search for the temperature measurement area will change its relative position with the infrared temperature measurement device, based on the first pose information of the camera device before searching for the temperature measurement area and the second pose information of the camera device after searching for and determining the temperature measurement area, along with the pose information of the infrared temperature measurement device, the determined temperature measurement area is transformed between coordinate systems, enabling the infrared temperature measurement device to perform position modulation. This ensures that the infrared temperature measurement beam can be accurately emitted to the determined temperature measurement area, avoiding temperature detection errors caused by inaccurate temperature measurement areas and improving the accuracy of temperature detection.

[0091] The following examples illustrate the advantages of the method of this disclosure compared to detection algorithms in related technologies:

[0092] For example, in related technologies, temperature detection is performed using only an infrared temperature measuring device, and the measurement location depends on the position of the machine or the object being measured moves to find the temperature measuring point. However, the method of this disclosure embodiment can automatically find the object being measured and identify the accurate temperature measuring area through a preset location, thereby improving the accuracy of temperature detection.

[0093] For example, in related technologies, facial recognition is performed using visible light images. However, this ignores the fact that the visible light acquisition device and the infrared emitting device are two devices with a positional difference, which results in a deviation in the obtained temperature measurement area. The embodiments of this disclosure take into account the relative positional difference between the two devices by transforming the coordinate system, thereby enabling the infrared beam to be emitted more accurately into the temperature measurement area.

[0094] It is evident that the method of this disclosure has significant advantages over methods in related technologies.

[0095] Figure 3 A flowchart illustrating the location information conversion according to an embodiment of the present disclosure is shown schematically.

[0096] like Figure 3 As shown, based on the first pose information, the basic pose information, and the second pose information, the first position information of the temperature measurement area in the image coordinate system of the reference image is converted into the second position information in the world coordinate system, including operations S301 to S303.

[0097] In operation S301, camera parameters of the camera device are obtained;

[0098] In operation S302, a mapping relationship between the image coordinate system and the world coordinate system is constructed based on the first pose information, the basic pose information, the second pose information, and the camera parameters.

[0099] In operation S303, the first position information of the temperature measuring area in the image coordinate system of the reference image is converted into the second position information of the temperature measuring area in the world coordinate system according to the mapping relationship.

[0100] According to embodiments of this disclosure, in operation S301, the two-dimensional reference image information is converted into a mapping relationship of the three-dimensional actual space world coordinate system. This process requires an accurate description of how the camera device projects points in the three-dimensional world onto the two-dimensional image plane. Therefore, the intrinsic parameters of the camera device are required, such as the focal length of the camera (f_x, f_y), which determines the scaling factor of the reference image, such as the optical center point marker (c_x, c_y), which is the point on the image plane that intersects with the optical axis of the camera. It may also include distortion parameters, such as radial distortion and tangential distortion parameters, to correct lens distortion, such as barrel distortion or pincushion distortion.

[0101] According to embodiments of this disclosure, in operation S302, the mapping relationship between the image coordinate system and the world coordinate system can be achieved by using a transformation matrix, which is calculated using vectors of relative position and relative angle to perform position transformation; alternatively, epipolar constraints, i.e., the geometric relationship between two planes, can be used to find the relationship between image points and world points.

[0102] Furthermore, since the camera device's first pose information and second pose information in the first and second time periods respectively changed during the period, although the infrared temperature measuring device did not move in the first and second time periods, the relative pose between the camera device and the infrared temperature measuring device changed. Therefore, when establishing the mapping relationship, the two pose information of the camera device in the two time periods and the basic pose information of the infrared temperature measuring device must be calculated to establish an accurate mapping relationship.

[0103] According to an embodiment of this disclosure, in operation S303, when a transformation matrix is ​​used as the mapping relationship, the first position information and the second position information can be directly transformed by the transformation matrix; when an epipolar constraint is used as the mapping relationship, the position information can be transformed by the essential matrix or the fundamental matrix.

[0104] According to embodiments of this disclosure, by accurately transforming the mapping relationship, it can be ensured that the infrared temperature measuring device is accurately aligned with the temperature measuring area, thereby improving the accuracy of temperature measurement; constructing the mapping relationship between the image coordinate system and the world coordinate system enables the temperature measurement process to be automated, reducing manual operation and improving efficiency.

[0105] Figure 4 A flowchart illustrating the construction of a transformation matrix according to an embodiment of this disclosure is shown schematically.

[0106] like Figure 4 As shown, the mapping relationship between the image coordinate system and the world coordinate system is constructed based on the first pose information, the basic pose information, the second pose information and the camera parameters, including operations S401 to S402.

[0107] Operation S401 determines the translation vector t and rotation matrix R based on the first pose information, the basic pose information, the second pose information, and the camera parameters.

[0108] Operation S402 constructs a coordinate transformation matrix T based on the translation vector t and the rotation matrix R, serving as a mapping relationship.

[0109] According to the embodiments of this disclosure, in operations S401 to S402, the first pose information of the camera device and the basic pose information of the infrared temperature measuring device in the first time period can be calibrated first to serve as the initial relative pose state of the two devices. Then, based on this, the relative position of the second pose information of the camera device in the second time period relative to the infrared temperature measuring device is used as the translation vector t, and the relative angle is used as the rotation matrix R, thereby constructing the rotation matrix T.

[0110] Furthermore, a specific example of the rotation matrix T is as follows:

[0111] (1);

[0112] Alternatively, it can be expressed as:

[0113] (2);

[0114] In equations (1) and (2), R is a 3×3 rotation matrix and t is a 3×1 translation vector.

[0115] Specifically, the rotation matrix R represents the rotation of the image coordinate system of the camera device relative to the world coordinate system, the translation vector t represents the translation of the image coordinate system of the camera device relative to the origin of the world coordinate system, 0 is a 1×3 zero vector, 1 is the last element of the matrix, located in the last column of the last row, and the last row [0,0,1] is the normalized row in the homogeneous coordinate system, used to maintain the correctness of matrix multiplication. In programming implementation, various programming languages ​​and mathematical / scientific computing libraries can be used to create and manipulate the transformation matrix T.

[0116] More specifically, after obtaining the transformation matrix T, the first position information in the image coordinate system is transformed to the world coordinate system as the second position information using the transformation matrix T, including:

[0117] (3);

[0118] In equation (3), P w The coordinates of the temperature measurement area in the world coordinate system are the second location information, T is the coordinate transformation matrix, i.e., the mapping relationship, and P is the coordinates of the temperature measurement area in the world coordinate system. v The coordinates of the temperature measurement area in the image coordinate system of the reference image acquired by the camera device are the first position information.

[0119] Furthermore, the coordinates P of the temperature measurement area in the world coordinate system are obtained. w Then, based on the basic pose information of the infrared temperature measuring device, the coordinates Pr of the infrared temperature measuring device in the world coordinate system can be obtained. This is then calculated using Pr. r and P w The difference can be used to obtain the difference value △p. Based on the difference value △p, an instruction is generated to determine the direction and distance of adjustment, which is used to guide the infrared temperature measuring device to perform necessary up, down, left, right rotation or translation, so that the infrared temperature measuring device can accurately emit the infrared beam used for temperature measurement into the determined temperature measuring area, thereby improving the accuracy of temperature detection.

[0120] According to embodiments of this disclosure, determining the temperature measurement area of ​​the object under test in the reference image obtained by the camera device from image acquisition of the object under test includes:

[0121] A fused image is obtained by fusing a reference image acquired by a camera device from the object under test with a thermal imaging image acquired from the object under test.

[0122] The temperature measurement area of ​​the object under test in the reference image is determined based on the fused image and the predetermined temperature measurement location.

[0123] According to embodiments of this disclosure, thermal imaging images can be acquired using a thermal imaging device or an infrared temperature measurement device with thermal imaging capabilities. When the thermal imaging acquisition device and the camera device are mounted at the same shooting angle and position, the thermal imaging image and a reference image can be fused to obtain a fused image. When there are differences in the shooting angle and position of the thermal imaging acquisition device and the camera device, the thermal imaging image and the reference image can be processed, for example, by using image registration techniques such as feature-based registration, region-based registration, or deep learning to align and fuse the two images to obtain a fused image.

[0124] Specifically, it may also include preprocessing steps for the reference image and thermal imaging image, including noise reduction, contrast enhancement, etc., to improve image quality.

[0125] Furthermore, after obtaining the fused image, different target temperature measurement sites are predetermined for different application scenarios:

[0126] For example, when the object being measured is a person, the predetermined temperature measurement area can be set to the center of the forehead or the temple. At this time, a face detection algorithm can be used to locate the face in the fused image, and then the main feature points of the face, such as the eyes, nose, and corners of the mouth, can be found according to the face key point detection algorithm. Based on the main feature points, especially the contours of the eyes and head, the position of the center of the forehead or the temple can be determined, and the determined position can be used as the target temperature measurement area.

[0127] Furthermore, image segmentation technology can be used to accurately divide the temperature measurement area. Features such as color, texture, and temperature threshold can be used for segmentation. Then, features such as temperature distribution and hot spots can be extracted within the temperature measurement area. The center of the forehead can be determined as the target temperature measurement area based on information such as a preset face temperature distribution area map.

[0128] Furthermore, the temperature measurement area determined by visible light through facial recognition technology and the temperature measurement area obtained by dividing the image based on temperature can be post-processed and verified to ensure the accuracy of the determined temperature measurement area. For example, deep learning algorithms can be used for verification and correction. By pre-training a large model of the center of the forehead or temple in the fused image, the accuracy of the target temperature measurement area can be corrected to obtain an accurate temperature measurement area.

[0129] For example, when the object being measured is an animal, the animal species can be pre-defined. For instance, if the predetermined measurement area is the groin, pre-setting the anatomical features of the groin region for different animals helps identify this area in the image. Then, features related to the groin region, such as skin texture, hair distribution, and body contours, are extracted from the image. Image segmentation techniques are used to separate the animal's body parts from the background. Computer vision algorithms are then used to detect specific body parts, such as limbs and genitals. The positions of these parts help infer the location of the groin. Based on the geometric relationships of the animal's body parts, the approximate location of the groin can be estimated. A deep learning model can then be trained to identify and locate the animal's groin region. This requires a large amount of training data with labeled groin locations, and continuous optimization of the algorithm and model iterations to improve recognition accuracy. Finally, the deep learning model identifies the groin location in the fused image, using the groin location as the temperature measurement area.

[0130] According to embodiments of this disclosure, the determination of the temperature measurement area in related technologies is often achieved through single visible light image facial recognition techniques. However, the accuracy of determination using only visible light images is not high. Image fusion combines the temperature information of thermal imaging images with the detailed visual features of visible light images, which helps to more accurately identify the temperature measurement area. For example, thermal imaging can highlight the heat distribution of the body, and the forehead area will show obvious temperature changes when heated, which helps to more accurately locate the forehead. Moreover, thermal imaging is not affected by lighting conditions; even in insufficient or excessive light, the forehead area can be clearly identified. By comparing thermal imaging images and visible light images, the correspondence between heat distribution and facial features can be seen more clearly. Similarly, if only thermal imaging is used to identify the temperature measurement area, interference factors such as ambient temperature or the presence of other heat sources nearby can interfere with the identification results. Therefore, using the fusion technology of thermal imaging and visible light images can fully utilize the advantages of both types of images, improving the accuracy and reliability of temperature measurement area identification.

[0131] Figure 5 The schematic diagram illustrates the principle of the temperature detection terminal judgment process according to an embodiment of the present disclosure.

[0132] like Figure 5As shown, the temperature detection method disclosed herein can be implemented through a terminal, which can be a mobile terminal, such as a temperature-measuring robot, intelligent robot, or other temperature-measuring device. This terminal can be equipped with an infrared temperature measuring device and a camera, and can also be fitted with an infrared thermal imaging device, as well as corresponding sensors and a processor. The terminal first identifies the object to be measured, then determines whether the distance between the object and the terminal meets a preset value. If not, the terminal actively moves to the preset value and determines the temperature measurement area. If there is an obstruction within the temperature measurement area, a prompt message is issued, and the terminal waits for a period of time before detecting the obstruction again. Because obstructions directly affect the temperature detection results, they are a necessary condition; the next step of judgment must be performed only if there are no obstructions. After confirming the absence of obstructions, the terminal determines whether the physiological state of the object being measured is stable. If unstable, only a prompt message is issued, and subsequent temperature detection continues.

[0133] According to embodiments of this disclosure, the following will be combined with Figure 5 The judgment steps are explained in detail. Through multiple judgment steps, the accuracy of temperature measurement can be avoided due to factors such as inaccurate measurement distance, obstruction of the temperature measurement area, and the influence of the physiological state of the measured object. By combining visible light images and infrared thermal imaging, the accuracy of temperature measurement is improved.

[0134] According to embodiments of this disclosure, after determining the temperature measurement area, the following operations may also be included:

[0135] Based on the fused image, determine whether there are any obstructions within the temperature measurement area of ​​the object being measured in the reference image; if obstructions are present in the temperature measurement area, generate a first prompt message.

[0136] According to embodiments of this disclosure, if there are obstructions within a defined temperature measurement area, they can first be identified using image detection technology. For example, easily identifiable obstructions such as hair or hats that are clearly distinguishable from the forehead in the temperature measurement area can be identified. Once identified, a first prompt message is generated. Further identification can be performed using a fused image of the thermal imaging image and a reference image. By analyzing features such as color, texture, and shape within the temperature measurement area, possible obstructions can be identified. Temperature distribution analysis can also be performed, for example, uneven temperature distribution may be a sign of the presence of obstructions. Furthermore, deep learning technology, such as a trained convolutional neural network model, can be used to identify obstructions in the image. Furthermore, the fusion technology of thermal imaging and visible light images can be used to detect occlusions by comparing the differences between the two images. For example, the feature differences of different regions in the fused image can be compared to identify possible occlusions. For example, an occlusion may appear as a temperature anomaly in a thermal imaging image, but as a discontinuity in shape or texture in a visible light image. Then, a threshold is set according to the feature differences to segment the image into occluded and non-occluded regions, thereby identifying the occlusion. In addition, if no occlusion is identified, the subsequent temperature detection method can continue.

[0137] According to embodiments of this disclosure, the manner in which the first notification message is presented can be varied, and at least one of the following can be selected:

[0138] For example, the first prompt can be an audio prompt, such as a voice prompt or warning sound, such as issuing a voice prompt to the test subject through a voice system and speaker, such as "There is an obstruction on the forehead" or "There is an obstruction on the temple", or a special sound effect to provide a prompt.

[0139] For example, the first prompt could be a light prompt, such as setting up an obstruction prompt light that turns on when there is an obstruction, or setting a special light flashing mode.

[0140] For example, the first prompt can be a text prompt, such as a text prompt on a display device, such as "There is something obstructing your forehead, please retake your temperature" or "There is something obstructing your temples".

[0141] Furthermore, after issuing the initial alert, a waiting period can be set for re-detecting obstructions, such as 3 seconds or 5 seconds. After detecting no obstruction, subsequent temperature detection operations can be performed.

[0142] According to the embodiments of this disclosure, the step of judging obstructions can avoid inaccurate temperature measurement results caused by obstructions in the temperature measurement area. Considering the principle of infrared thermometry, obstructions will directly affect the temperature measurement results. Judging solely by visible light images or solely by thermal imaging temperature distribution may not be accurate enough. Therefore, combining fused images to judge obstructions can improve the accuracy of temperature detection.

[0143] According to embodiments of this disclosure, before formal temperature measurement after obtaining the fused image, it is also possible to determine whether the physiological state of the tested object is stable based on the fused image; if the physiological state of the tested object is unstable, a second prompt message is generated.

[0144] According to embodiments of this disclosure, when the subject is a human or other animal, the purpose of temperature detection is conventionally to obtain a body temperature value. However, strong emotional fluctuations such as anger, tension, and anxiety can affect the body temperature of the subject, thereby affecting the temperature detection results. However, according to relevant technical research, in cases of pathological fever, the overall body temperature is higher than normal, and the temperature distribution is relatively even, showing an overall temperature increase. In cases of fever caused by emotional factors, the activation of the sympathetic nervous system often leads to increased blood flow in local areas, resulting in an increase in temperature in specific areas of the face. For example, facial temperature changes during anger may be more localized, such as on the cheeks or forehead.

[0145] Specifically, for example, when the subject is a human, computer vision algorithms are first used to detect the face region in the visible light image in the fused image, and thermal imaging images are used to analyze the temperature distribution of the face. Then, different physiological states can be identified through pre-trained machine learning models, such as support vector machines, random forests, or deep neural networks. If the physiological state is determined to be unstable, a second prompt message is issued.

[0146] According to embodiments of this disclosure, the second prompt message can be presented in various ways, and at least one of the following can be selected:

[0147] For example, the second prompt can be an audio prompt, such as a voice prompt or warning sound, such as issuing a voice prompt to the subject through a voice system and speaker, such as "the subject's physiological state is unstable" or "the physiological state is abnormal", or a special sound effect to provide a prompt.

[0148] For example, the second prompt could be a light prompt, such as setting an emotion prompt light that turns on when the subject's physiological state is unstable, or setting a special light flashing mode.

[0149] For example, the second prompt can be a text prompt, such as a text prompt displayed on a monitor or other display device, such as "The physiological state of the tested object is unstable" or "The physiological state is abnormal".

[0150] Furthermore, after issuing the second prompt, a period of time can be waited before re-performing the physiological stability test. For example, a wait of 10 seconds or 15 seconds can be set. After the physiological state is tested, the subsequent temperature test can be performed. Alternatively, a prompt can be issued and the subsequent temperature test can continue without affecting the temperature test process.

[0151] According to embodiments of this disclosure, there is a strong correlation between the physiological state and temperature of the tested subject. For example, the forehead temperature of an angry person may reach above 37 degrees Celsius, which could easily be misjudged as a low-grade fever. By detecting the stability of the physiological state and providing prompts, the results of temperature detection can be used as a reference. For instance, if the physiological state is unstable and the detected temperature is 37.5 degrees Celsius, the tested subject can consider that the elevated body temperature may be due to the unstable physiological state and can consider measuring again when the temperature is stable. This improves the accuracy of temperature detection and enhances the user experience of the tested subject.

[0152] According to embodiments of this disclosure, after determining the object to be tested, the following operations are also included:

[0153] Operation S1: Obtain the first distance information between the infrared temperature measuring device and the object being measured;

[0154] Operation S2: Generate a movement command based on the first distance information to instruct the infrared temperature measuring device to move before performing temperature detection.

[0155] According to embodiments of this disclosure, before determining the temperature measurement area, first distance information between the infrared temperature measuring device and the object being measured is obtained. The first distance information is used to represent the distance between the infrared temperature measuring device and the object being measured. For example, it can be numerical information, such as 2 meters, 2.5 meters, etc., or it can be coordinate information. For example, by establishing a Cartesian coordinate system on the ground with the person being measured as the origin, the Euclidean distance between the coordinates of the basic pose of the infrared temperature measuring device and the origin is determined as the first distance information. Alternatively, the first distance information can be represented by a vector. Then, a movement command is generated based on the first distance information, so that the infrared temperature measuring device moves to a preset distance to perform temperature detection.

[0156] Furthermore, the first distance information can be acquired through a camera device or an infrared temperature measuring device. The first distance information can be acquired by transmitting the signal returned by the camera device or the infrared temperature measuring device to the back-end processor for calculation, or the first distance information can be directly acquired by a camera device or infrared temperature measuring device with integrated algorithm function and transmitted to the back-end processor.

[0157] For example, the focal length-object distance method using a camera device involves adjusting the focal length of the camera lens to make the object being measured appear clearly in the image, and then estimating the distance based on the focal length and the size of the object in the image.

[0158] For example, an infrared thermometer can emit infrared light pulses of a specific wavelength using the time-of-flight method, measure the time required for the reflected light pulses to return, and calculate the distance based on the speed of light.

[0159] Specifically, an optimal temperature detection distance can be preset, which can be determined based on the performance of the infrared temperature measuring device, environmental conditions, and the nature of the object being measured. For example, the optimal distance for a common temperature measuring robot to emit an infrared beam to a person's forehead and receive the returned signal is generally 1.5 meters. In such application scenarios, the preset distance can be set to 1.5 meters, thereby generating movement commands based on the preset distance.

[0160] In some specific embodiments of this disclosure, operation S2 includes obtaining second distance information based on the difference between the first distance information and the preset distance information; and generating a movement command to instruct the infrared temperature measuring device to move based on the second distance information.

[0161] Specific examples are as follows:

[0162] For example, the first distance information is that the distance between the infrared temperature measuring device and the object being measured is 2 meters, and the preset distance set by the system in advance is 1.5 meters. At this time, the second distance information is obtained, that is, the difference is 0.5 meters. Then, an instruction will be generated to guide the infrared temperature measuring device to move 0.5 meters toward the object being measured.

[0163] For example, the first distance information is that the distance between the infrared temperature measuring device and the object being measured is 1 meter, and the preset distance set by the system in advance is 1.5 meters. At this time, the second distance information is obtained, which is a difference of -0.5 meters. Then, an instruction will be generated to guide the infrared temperature measuring device to move 0.5 meters away from the object being measured.

[0164] According to the embodiments of this disclosure, when using an infrared beam for temperature measurement, the appropriate temperature measurement distance will directly affect the accuracy of the temperature measurement. There are many factors that affect the appropriate temperature measurement distance, such as the performance of the infrared temperature measuring device, the usage scenario, the object being measured, and the ambient temperature. By preset an optimal distance and moving the infrared temperature measuring device to the optimal distance, the accuracy of temperature measurement can be improved, and inaccurate temperature measurement results caused by an unsuitable distance can be avoided.

[0165] According to embodiments of this disclosure, the method further includes: acquiring the detection result of the infrared temperature measuring device detecting the temperature of the object being measured; and generating a third prompt message based on the detection result and a preset detection result.

[0166] According to the embodiments of this disclosure, the temperature detection result is generally a calculated value, such as 37, 36.7, 38, etc. The unit can be set to a unit that expresses temperature, such as degrees Celsius. After obtaining the detection result, the value can be broadcast directly, such as through sound or text broadcast. The value can also be further judged, as exemplified in Table 1 below. The preset detection results in Table 1 are set based on the human body temperature measurement results.

[0167] Table 1

[0168]

[0169] Furthermore, the third prompt message is determined and broadcast based on the preset detection result obtained from the judgment. The third prompt message can be presented in various ways, and at least one of the following can be selected:

[0170] For example, the third prompt can be an audio prompt, such as a voice prompt or warning sound. For instance, the voice system and speaker can issue voice prompts to the subject such as "The subject's body temperature is high" or "The body temperature is normal," or different special sound effects can be used for prompting.

[0171] For example, the third prompt can be a light prompt, such as setting different prompt lights for different results, such as a yellow light when the temperature is abnormal, a green light when the temperature is normal, a red light when the temperature is too high, and a blue light when the temperature is too low, or setting a special light flashing mode.

[0172] For example, the third prompt can be a text prompt, such as a text prompt displayed on a monitor or other display device, such as "The subject's body temperature is high" or "The body temperature is normal".

[0173] According to embodiments of this disclosure, by adding a comparison between the detection result and the preset value, the temperature measurement process can be improved and the user experience enhanced.

[0174] Figure 6 A schematic block diagram of a temperature detection device according to an embodiment of the present disclosure is shown.

[0175] like Figure 6 As shown, the temperature detection device 600 includes an acquisition module 601, a judgment module 602, a conversion module 603, and a detection module 604.

[0176] The acquisition module 601 is used to acquire the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period.

[0177] The judgment module 602 is used to determine the temperature measurement area of ​​the object under test in the reference image obtained by the camera device from image acquisition of the object under test.

[0178] The conversion module 603 is used to convert the first position information of the temperature measuring area in the image coordinate system of the reference image into the second position information of the temperature measuring area in the world coordinate system of the infrared temperature measuring device, based on the first pose information, the basic pose information, and the second pose information.

[0179] The detection module 604 is used to generate a detection command based on the second position information, which instructs the infrared temperature measuring device to perform temperature detection on the object being measured.

[0180] According to embodiments of this disclosure, the conversion module includes a camera parameter unit, a mapping relationship construction unit, and a location information conversion unit.

[0181] The camera parameter unit is used to acquire the camera parameters of the imaging device.

[0182] The mapping relationship construction unit is used to construct the mapping relationship between the image coordinate system and the world coordinate system based on the first pose information, the basic pose information, the second pose information, and the camera parameters.

[0183] The position information conversion unit is used to convert the first position information of the temperature measurement area in the image coordinate system of the reference image into the second position information of the temperature measurement area in the world coordinate system according to the mapping relationship.

[0184] According to embodiments of this disclosure, the mapping relationship construction unit includes a translation vector rotation matrix determination subunit and a transformation matrix construction subunit.

[0185] The translation vector and rotation matrix determine the sub-unit, which is used to determine the translation vector t and rotation matrix R based on the first pose information, the basic pose information, the second pose information, and the camera parameters.

[0186] The transformation matrix constructs a sub-unit, which is used to construct the coordinate transformation matrix T based on the translation vector t and the rotation matrix R, as a mapping relationship.

[0187] According to embodiments of this disclosure, the determination module includes a fused image unit and a temperature measurement area determination unit.

[0188] The image fusion unit is used to fuse the reference image obtained by the camera device from the image acquisition of the object under test and the thermal imaging image obtained by the thermal imaging acquisition of the object under test to obtain a fused image.

[0189] The temperature measurement area determination unit is used to determine the temperature measurement area of ​​the object under test in the reference image based on the fused image and the predetermined temperature measurement location.

[0190] According to embodiments of this disclosure, the temperature detection device further includes a first prompting module.

[0191] The first prompt module is used to determine whether there are obstructions in the temperature measurement area of ​​the object under test in the reference image based on the fused image; if there are obstructions in the temperature measurement area, a first prompt message is generated.

[0192] According to embodiments of this disclosure, the temperature detection device further includes a second prompting module.

[0193] The second prompt module is used to determine whether the physiological state of the tested object is stable based on the fused image; if the physiological state of the tested object is unstable, a second prompt message is generated.

[0194] According to embodiments of this disclosure, the temperature detection device further includes a ranging module.

[0195] The ranging module is used to acquire the first distance information between the infrared temperature measuring device and the object being measured; based on the first distance information, it generates a movement command to instruct the infrared temperature measuring device to move before performing temperature detection.

[0196] According to embodiments of this disclosure, the ranging module further includes a difference calculation unit and a movement command generation unit.

[0197] The difference calculation unit is used to obtain the second distance information based on the difference between the first distance information and the preset distance information;

[0198] The movement command generation unit is used to generate movement commands based on the second distance information to instruct the infrared temperature measuring device to move.

[0199] According to embodiments of this disclosure, the temperature detection device further includes a third prompting module.

[0200] The third prompt module is used to obtain the detection results of the infrared temperature measuring device on the object being measured; and to generate a third prompt message based on the detection results and the preset detection results.

[0201] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-a-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0202] For example, any multiple of the initial acquisition module 601, judgment module 602, conversion module 603, and optimization model detection module 604 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the initial acquisition module 601, judgment module 602, conversion module 603, and optimization model detection module 604 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the initial acquisition module 601, the judgment module 602, the conversion module 603, and the optimization model detection module 604 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0203] It should be noted that the data processing system part in the embodiments of this disclosure corresponds to the data processing method part in the embodiments of this disclosure. The specific description of the data processing system part is referred to in the data processing method part, and will not be repeated here.

[0204] Figure 7 A block diagram of an electronic device suitable for implementing a temperature detection method according to an embodiment of the present disclosure is shown schematically.

[0205] Figure 7 A block diagram of an electronic device suitable for implementing the methods described above, according to embodiments of the present disclosure, is illustrated schematically. Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0206] like Figure 7As shown, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0207] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0208] According to embodiments of this disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the input / output (I / O) interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0209] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711. When the computer program is executed by processor 701, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0210] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0211] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0212] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 702 and / or RAM 703 described above and / or one or more memories other than ROM 702 and RAM 703.

[0213] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the temperature detection method provided in the embodiments of this disclosure.

[0214] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0215] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0216] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0217] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0218] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A temperature detection method, comprising: The system acquires the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period. Based on the reference image obtained by the camera device from the image acquisition of the object under test, the temperature measurement area of ​​the object under test in the reference image is determined; Based on the first pose information, the basic pose information, and the second pose information, the first position information of the temperature measuring area in the image coordinate system of the reference image is converted into the second position information of the temperature measuring area in the world coordinate system. Based on the second location information, a detection command is generated to instruct the infrared temperature measuring device to perform temperature detection on the object being measured.

2. The method according to claim 1, wherein, The step of converting the first position information of the temperature measuring area in the image coordinate system of the reference image into the second position information in the world coordinate system based on the first pose information, the basic pose information, and the second pose information includes: Obtain the camera parameters of the imaging device; The mapping relationship between the image coordinate system and the world coordinate system is constructed based on the first pose information, the basic pose information, the second pose information, and the camera parameters. Based on the mapping relationship, the first position information of the temperature measurement area in the image coordinate system of the reference image is converted into the second position information of the temperature measurement area in the world coordinate system.

3. The method according to claim 2, wherein, The step of constructing the mapping relationship between the image coordinate system and the world coordinate system based on the first pose information, the basic pose information, the second pose information, and the camera parameters includes: The translation vector t and rotation matrix R are determined based on the first pose information, the basic pose information, the second pose information, and the camera parameters. Construct a coordinate transformation matrix T based on the translation vector t and the rotation matrix R, which serves as the mapping relationship.

4. The method according to claim 1, wherein, The step of determining the temperature measurement area of ​​the object under test in the reference image obtained by the camera device from the image acquisition of the object under test includes: The reference image obtained by the camera device from the object under test and the thermal imaging image obtained by the thermal imaging image of the object under test are fused together to obtain a fused image; The temperature measurement area of ​​the object under test in the reference image is determined based on the fused image and the predetermined temperature measurement location.

5. The method according to claim 4, wherein, Also includes: Based on the fused image, determine whether the object under test has any obstructions in the temperature measurement area of ​​the reference image; If there is an obstruction in the temperature measurement area, a first prompt message is generated.

6. The method according to claim 4 or 5, wherein, Also includes: The physiological state of the tested object is determined based on the fused image; When the physiological state of the tested object is unstable, a second prompt message is generated.

7. The method according to any one of claims 1 to 5, further comprising: Obtain the first distance information between the infrared temperature measuring device and the object being measured; Based on the first distance information, a movement command is generated to instruct the infrared temperature measuring device to move before performing the temperature detection.

8. The method according to claim 7, wherein, The step of generating a movement command based on the first distance information to instruct the infrared temperature measuring device to move before performing the temperature detection includes: The second distance information is obtained based on the difference between the first distance information and the preset distance information; Based on the second distance information, a movement command is generated to instruct the infrared temperature measuring device to move.

9. The method according to any one of claims 1 to 5, wherein, Also includes: Obtain the temperature detection result of the infrared thermometer on the object being measured; A third prompt message is generated based on the detection results and the preset detection results.

10. A temperature detection device, wherein, include: The acquisition module is used to acquire the first pose information of the camera device when it detects the temperature of the object under test during the first detection period, the basic pose information of the infrared thermometer when it detects the temperature of the object under test during the first detection period, and the second pose information of the camera device when it detects the temperature of the object under test during the second detection period. The judgment module is used to determine the temperature measurement area of ​​the object under test in the reference image obtained by the camera device from the image acquisition of the object under test. The conversion module is used to convert the first position information of the temperature measuring area in the image coordinate system of the reference image into the second position information of the temperature measuring area in the world coordinate system of the infrared temperature measuring device, based on the first pose information, the basic pose information, and the second pose information. as well as The detection module is used to generate a detection command based on the second location information, which instructs the infrared temperature measuring device to perform temperature detection on the object being measured.

11. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 9.

12. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 9.

13. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 9.

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