CN112215905A - Automatic calibration method of mobile infrared temperature measurement system - Google Patents
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- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
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Abstract
The invention discloses an automatic calibration method of a mobile infrared temperature measurement system, which comprises the following steps: the automatic calibration method comprises the following steps of fixing a focus of a visible light camera, a focus of an infrared camera, a rotatable holder, a laser radar and a mobile device, wherein the visible light camera and the infrared camera are installed on the mobile device with the laser radar through the rotatable holder, and have the same rotation effect and partial overlapped view fields relative to the rotatable holder, and the automatic calibration method comprises the following steps: and calibrating the relative position of the visible light camera and the infrared camera, and calibrating the relative position of the laser radar and the visible light camera by the rotatable holder at different rotation angles to obtain the real-time relative position of the laser radar and the infrared camera. The invention can effectively finish the external reference calibration of the visible light camera and the infrared camera, so that the calibration of the visible light camera and the infrared camera is not interfered with each other, and the calibration efficiency is obviously improved.
Description
Technical Field
The invention relates to the technical field of computer vision. More specifically, the invention relates to an automatic calibration method for a mobile infrared temperature measurement system.
Background
At present, infrared temperature measurement systems are deeply developed in multiple fields, particularly when measurement is carried out in certain high-risk environments, however, the reliability of data collected by the systems is directly influenced by the distortion of infrared temperature measurement cameras; in addition, the imaging definition of the infrared temperature measurement camera is not as good as that of visible light, so that the infrared temperature measurement camera and the visible light are often required to be used in a matched mode, and therefore, the research on the infrared calibration technology has important significance. In order to improve the coverage of the infrared temperature measurement system, the infrared temperature measurement camera can be installed on the mobile equipment, and a rotatable holder is equipped to cover the environment and equipment at different angles in all directions. The mobile device is generally positioned based on a laser radar, and in order to acquire the position of a measured object, the laser radar, the rotatable holder, the visible light camera and the infrared camera need to be calibrated in a unified manner.
Disclosure of Invention
An object of the present invention is to solve at least the above problems and to provide at least the advantages described later.
The invention also aims to provide an automatic calibration method of the mobile infrared temperature measurement system, which can effectively finish the external reference calibration of the visible light camera and the infrared camera, so that the calibration of the two cameras is not interfered with each other, and the calibration efficiency is obviously improved.
To achieve the above objects and other advantages in accordance with the present invention, there is provided an automatic calibration method of a mobile infrared temperature measurement system, the mobile infrared temperature measurement system including: the automatic calibration method comprises the following steps of fixing a focus of a visible light camera, a focus of an infrared camera, a rotatable holder, a laser radar and a mobile device, wherein the visible light camera and the infrared camera are installed on the mobile device with the laser radar through the rotatable holder, and have the same rotation effect and partial overlapped view fields relative to the rotatable holder, and the automatic calibration method comprises the following steps: and calibrating the relative position of the visible light camera and the infrared camera, and calibrating the relative position of the laser radar and the visible light camera by the rotatable holder at different rotation angles to obtain the real-time relative position of the laser radar and the infrared camera.
Preferably, the specific implementation manner of calibrating the relative position of the visible light camera and the infrared camera is as follows: the method comprises the steps of shooting a target by a visible light camera, obtaining an image, calculating an internal reference matrix and a distortion coefficient of the visible light camera, shooting the target by an infrared camera, obtaining the image, calculating the internal reference matrix and the distortion coefficient of the infrared camera, shooting the target by the visible light camera and the infrared camera, changing the pose, obtaining a plurality of pairs of images in different poses, and calculating external reference matrices of the visible light camera and the infrared camera by combining the internal reference matrix and the distortion coefficient of the visible light camera and the infrared camera.
Preferably, the target comprises a black and white chessboard lattice calibration plate, a heat insulation layer and a constant temperature heating plate which are sequentially overlapped in an equal size, the target is provided with a through hole in a penetrating manner, the circle center of the through hole is overlapped with the center of each chessboard, and the number of the through holes and the number of the angular points of the chessboard lattices can at least determine a unique space plane;
the method comprises the steps of preheating a target before shooting the target, enabling a visible light camera and an infrared camera to be located on one side facing a black and white checkerboard calibration plate, carrying out corner point detection and extraction on an image obtained by shooting the target by the visible light camera, carrying out dot detection and extraction on the image obtained by shooting the target by the infrared camera, constructing a plane homography matrix, and calculating an external reference matrix between the visible light camera and the infrared camera.
Preferably, the specific implementation manner of the relative position of the laser radar and the visible light camera by the rotatable holder at different rotation angles is as follows: calibrating the relative position of the laser radar and an axis I of the rotatable holder, and then calibrating the relative position of the axis I of the rotatable holder and an axis II of the rotatable holder and the relative position of the axis II of the rotatable holder and the visible light camera to obtain the relative position of the laser radar and the visible light camera;
wherein the I axis of the rotatable pan/tilt is mounted on the mobile device.
Preferably, when calibrating the relative position of the laser radar and the axis I of the rotatable pan-tilt, fixing the axis II of the rotatable pan-tilt, rotating the axis I of the rotatable pan-tilt for at least 2 angles, calibrating the external reference matrix of the laser radar and the visible light camera, acquiring the rotation matrix of the axis I of the rotatable pan-tilt relative to 0 degree, and acquiring the external reference matrix of the axis I of the laser radar and the rotatable pan-tilt in a nonlinear optimization mode according to the transformation matrix relation of the laser radar and the visible light camera;
when the relative position of an I axis of a rotatable tripod head and an II axis of the rotatable tripod head and the relative position of the II axis of the rotatable tripod head and a visible light camera are calibrated, the I axis of the rotatable tripod head is fixed, the II axis of the rotatable tripod head is rotated for at least 2 angles, the external reference matrix of a laser radar and the visible light camera is calibrated, the rotation matrix of the I axis of the rotatable tripod head relative to 0 degree is obtained, the rotation matrix of the II axis of the rotatable tripod head relative to 0 degree is obtained by combining the external reference matrix of the laser radar and the I axis of the rotatable tripod head, and the external reference matrix of the I axis of the rotatable tripod head and the II axis of the rotatable tripod head and the external reference matrix of the rotatable tripod head and the visible light camera are obtained in a nonlinear optimization mode according to the transformation matrix relation of the laser radar and the visible light;
the method comprises the steps of taking the rotation angle of an axis I of a rotatable cloud platform and an axis II of the rotatable cloud platform as a known variable, obtaining a rotation matrix when the axis I of the rotatable cloud platform rotates for a certain angle, taking an external parameter matrix of a laser radar and the axis I of the rotatable cloud platform, an external parameter matrix of the axis I of the rotatable cloud platform and the axis II of the rotatable cloud platform, and an external parameter matrix of the axis II of the rotatable cloud platform and a visible light camera as known variables, and obtaining real-time pose calculation of the laser radar and the visible light camera in a nonlinear optimization mode according to the transformation matrix relation of the laser radar and the visible light camera.
An electronic device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method.
A storage medium having stored thereon a computer program which, when executed by a processor, implements the method.
The invention at least comprises the following beneficial effects:
firstly, the method can effectively solve the difficult problem of calibrating the internal parameters of the infrared camera, and further finish the external parameter calibration of the visible light camera and the infrared camera by only utilizing the images collected by one target, so that the calibration of the two cameras is not interfered with each other, and the calibration efficiency is obviously improved;
secondly, in places with large space limitation, the target can be fixed, and a good calibration effect can be achieved by simply controlling the rotatable tripod head to drive the camera to shoot, so that the method is simple to operate, convenient and quick;
and thirdly, the calibration of the laser radar and the rotatable holder is skillfully completed by means of the external reference calibration of the laser radar and the visible light camera arranged on the rotatable holder, and the calibration is realized by changing different observation angles of the rotatable holder. The existence of the mobile equipment and the rotatable holder can greatly increase the measurement range of the visible light camera and the infrared camera.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a schematic diagram showing the relative position relationship between the laser radar, the rotatable pan/tilt head, the visible light camera and the infrared camera according to the present invention;
FIG. 3 is a schematic structural diagram of a target of the present invention.
Detailed Description
The present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.
It will be understood that terms such as "having," "including," and "comprising," as used herein, do not preclude the presence or addition of one or more other elements or groups thereof.
It is to be noted that the experimental methods described in the following embodiments are all conventional methods unless otherwise specified, and the reagents and materials, if not otherwise specified, are commercially available; in the description of the present invention, it should be noted that unless otherwise explicitly stated or limited, the terms "mounted," "connected," and "disposed" are to be construed broadly and can, for example, be fixedly connected, disposed, detachably connected, disposed, or integrally connected and disposed. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art. The terms "lateral," "longitudinal," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientation or positional relationship indicated in the drawings for convenience in describing the invention and to simplify the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the invention.
As shown in fig. 1 to 3, the present invention provides an automatic calibration method for a mobile infrared temperature measurement system, wherein the mobile infrared temperature measurement system comprises: the automatic calibration method comprises the following steps that an electric pan tilt can be adopted as the fixed-focus visible light camera, the fixed-focus infrared camera, the rotatable pan tilt, the laser radar and the mobile equipment, the left-right rotation and the up-down rotation are easier to realize, the mobile equipment can adopt a wheel type and track type movable structure, the visible light camera and the infrared camera are installed on the mobile equipment with the laser radar through the rotatable pan tilt, the visible light camera and the infrared camera have the same rotation effect and partial overlapped view fields relative to the rotatable pan tilt, and the phenomenon that an I shaft and/or an II shaft of the rotatable pan tilt rotate to drive the visible light camera and the infrared camera to synchronously rotate and can shoot the same target is solved, and the automatic calibration method comprises the following steps: and calibrating the relative position of the visible light camera and the infrared camera, and calibrating the relative position of the laser radar and the visible light camera by the rotatable holder at different rotation angles to obtain the real-time relative position of the laser radar and the infrared camera.
Calibrating the relative position of the visible light camera and the infrared camera can be realized by the following modes:
1. making the black-and-white checkerboard template pattern into a metal material, simultaneously shooting the heated metal black-and-white checkerboard target by two types of cameras, and solving the relative position of the visible light camera and the infrared camera by extracting the intersection points of the corner points in the visible light image and the four edges of the metal target in the infrared image and calculating a single mapping matrix according to the object point image points;
2. aiming at the optical characteristics of infrared light, a black-and-white checkerboard target is made of special materials capable of distinguishing high reflection and low reflection of the infrared light, then the angle point information is respectively extracted from an infrared image and a visible light image after the whole target system reaches a thermal equilibrium state through a constant temperature controller, and then after homography matrixes among respective image point object points are calculated, the relative positions of a visible light camera and an infrared camera are solved;
the relative position of the laser radar and the visible light camera under different rotation angles of the rotatable holder can be realized by the following modes:
1. under the condition of low precision requirement, the relative position of the holder and the camera can be directly obtained according to factory parameters, and the relative position of the radar and the holder can be measured;
2. the relative position of the holder and the camera is directly obtained according to factory parameters, and the relative position of the radar and the holder is obtained by back calculation of the relative position of the radar and the camera which are calibrated to be at fixed angles;
combining the laser radar and the infrared camera to obtain the real-time relative position of the laser radar and the infrared camera:
after the fixed relative position between the visible light camera and the infrared camera in the system and the real-time relative position between the laser radar and the visible light camera on the holder in the system are obtained through calculation, the position of the visible light camera in the system is used as a bridge connection, and then the real-time relative position of the laser radar in the infrared camera can be obtained.
According to the technical scheme, the calibration difficulty of the internal reference of the infrared camera can be effectively solved, the external reference calibration of the visible light camera and the infrared camera is completed, and the calibration efficiency is high.
In another technical scheme, a specific implementation manner for calibrating the relative position of the visible light camera and the infrared camera is as follows: the visible light camera shoots a target, only a high-precision checkerboard calibration plate is adopted to obtain an image, an internal reference matrix and a distortion coefficient of the visible light camera are calculated, a Zhang-Yongyou calibration method is mature for the calibration of the visible light camera, and for the visible light camera, the corner point information of the high-precision checkerboard calibration plate target is easy to obtain, how the inside of a black and white grid does not influence the final calibration result, the infrared camera shoots the target to obtain the image, the internal reference matrix and the distortion coefficient of the infrared camera are calculated, the calibration method of the infrared camera usually needs to use the calibration target plate, and the existing infrared calibration target mainly has the following 4 forms: the technical scheme includes that the self-heating target, the transmission external infrared heat source target, the infrared light emitting diode target and the infrared radiation coating target are selected, the infrared heat source with a large area is placed on one side of the target far away from the infrared camera, infrared radiation released by the heat source is transmitted to the infrared camera through holes in a metal plate, the visible light camera and the infrared camera shoot the target, the high-precision checkerboard target and the transmission external infrared heat source target can be set to be in the same size specification, the circle center of a through hole and the angular points of each checkerboard are positioned, namely under the condition that the relative positions of the two targets are known and unchanged, the object point coordinates of each characteristic point can be mutually converted in the calculation process, the pose is changed, the complete targets with different visual angles are shot, the two targets are corrected, and multiple pairs of images with different poses are obtained, and calculating external parameter matrixes of the visible light camera and the infrared camera by combining the internal parameter matrixes and the distortion coefficients of the visible light camera and the infrared camera.
The key links in the specific implementation method can be summarized as the following steps:
1. according to a traditional camera internal reference calibration method, corresponding calibration plate feature points in internal reference calibration images shot by two cameras are utilized, and respective internal reference data of the two cameras are calculated through a calibretacarama function in OpenCV;
2. the relative position of the two cameras is kept unchanged, a plurality of pairs of images with different poses are shot simultaneously, the object point coordinates under the camera coordinate system corresponding to the feature points in the images of each camera and the corresponding homography matrix are solved through an EPNP algorithm, and the object point coordinates and the corresponding homography matrix are arranged into a feature point coordinate set under each camera coordinate system strictly according to the corresponding sequence;
and solving the pose relation of coordinate systems of the two cameras by aiming at the feature point object point coordinate set corresponding to each camera obtained in the previous step through a function of estimaafffine 3D in OpenCV, namely solving an external parameter matrix of the visible light camera and the infrared camera.
In the technical scheme, the two targets can be fixed at the place with large space limitation, the camera is simply controlled to shoot, a good calibration effect can be achieved, the operation is simple, the operation is convenient and fast, and the relative position of the visible light camera and the infrared camera can be well calibrated.
In another technical scheme, the target comprises a black and white checkerboard calibration board, a heat insulation layer and a constant temperature heating board which are overlapped in sequence in equal size, at least 2 × 2 checkerboards are selected for the black and white checkerboard calibration board, preferably 7 × 8 checkerboards shown in fig. 3, a through hole is arranged in the target in a penetrating mode, the circle center of the through hole is overlapped with the center of each checkerboard, the number of the through holes and the number of the angular points of the checkerboards at least can determine a unique space plane, the constant temperature heating board is not limited to be an infrared heat source, as long as the infrared heat source can be uniformly heated and recognized by an infrared camera, the modified target presents infrared light structural characteristic points and can be used for internal parameter calibration of the visible light camera, internal parameter calibration of the infrared camera, and external parameter calibration of the visible light camera and the infrared camera;
before shooting a target, preheating the target to enable an infrared camera to identify characteristic points, wherein a visible light camera and the infrared camera are positioned on one side facing a black-and-white checkerboard calibration board, namely the other side far away from a constant-temperature heating board, performing corner point detection and extraction on an image obtained by shooting the target by the visible light camera, performing dot detection and extraction on an image obtained by shooting the target by the infrared camera, performing corner point detection on an image obtained by shooting the target by the visible light camera by using a findchessboardcameras function in OpenCV, performing dot detection on an image obtained by shooting the target by the infrared camera by using a findCirclesGrid function in OpenCV, constructing a plane homography matrix, and calculating an extrinsic parameter matrix between the visible light camera and the infrared camera;
in the technical scheme, firstly, a purpose-made target is designed, a target transmitting an external infrared heat source is combined with a chessboard pattern calibration method, when internal parameters are measured, a visible light camera and an infrared camera can respectively shoot the target to respectively obtain a certain number of images, the angular points and the round points are respectively detected by utilizing OpenCV, the internal parameters of the visible light camera and the infrared camera, including focal length, stagnation points, distortion, camera parameters and the like, when the external parameters are measured and calculated, the visible light camera and the infrared camera simultaneously shoot images of the target, the target pose is changed to ensure the integrity of the target, the two cameras are clear in imaging, a certain number of paired images are obtained by shooting, angular point detection and round point detection are carried out after the images are grayed, because the center of the target is provided with a through hole, in the actual calculation, an object point coordinate set of characteristic points of the images with different target poses in corresponding camera coordinate systems is solved through an EPNP algorithm, and performing extrinsic parameter matrix calculation of the visible light camera and the infrared camera by using the two feature point object point coordinate sets. The external reference calibration of the visible light camera and the infrared camera is completed only by using the images collected by one target, so that the calibration of the two cameras is not interfered with each other, and the calibration efficiency is obviously improved.
In another technical scheme, the specific implementation manner of the relative position of the laser radar and the visible light camera by the rotatable holder at different rotation angles is as follows: calibrating the relative position of the laser radar and an axis I of the rotatable holder, and then calibrating the relative position of the axis I of the rotatable holder and an axis II of the rotatable holder and the relative position of the axis II of the rotatable holder and the visible light camera to obtain the relative position of the laser radar and the visible light camera;
wherein, the I axis of the rotatable pan/tilt is installed on the mobile device, as shown in fig. 2, the I axis of the rotatable pan/tilt is a vertical axis, and the II axis of the rotatable pan/tilt is a horizontal axis.
In above-mentioned technical scheme, because the visible light camera is installed on rotatable cloud platform, consequently need mark the rotation axis simultaneously, the degree of freedom of every rotation axis is 4, and rotatable cloud platform includes horizontal axis and two axles of vertical axle, totally 8 degrees of freedom, consequently need mark laser radar and the relative position of the I axle of rotatable cloud platform, the I axle of rotatable cloud platform and the II axle of rotatable cloud platform, the II axle of rotatable cloud platform and visible light camera in proper order. The kinematic parameters of the rotatable cradle head are factory parameters mostly, but due to the influence of manufacturing errors and assembly errors, the factory parameters have certain deviation from actual conditions. The essence of the rotatable pan-tilt is a 2-axis mechanical arm, and the calibration of the mechanical arm and the camera is called hand-eye calibration, which is performed under the condition that the parameters of the mechanical arm are known, and no mature solution is provided at present for the condition of unknown parameters. The method and the device have the advantage that the kinematic parameters of the holder are indirectly obtained by skillfully using the calibration of the radar and the camera.
In another technical solution, the coordinate system of the I axis of the rotatable pan/tilt head is defined as: the origin is located at the intersection point of an axis I of the rotatable holder and the optical center rotation plane of the visible light camera, the axis x points to the optical center of the visible light camera, the axis z is consistent with the positive rotation direction (the rotation direction of the second angle relative to the first angle), and the axis y is obtained through a right-hand rule. When the relative position of the laser radar and the axis I of the rotatable holder is calibrated, the axis II of the rotatable holder is fixed, the axis I of the rotatable holder is rotated for at least 2 angles, and the external parameter matrix of the laser radar and the visible light camera is calibratedlidarAcamObtaining a rotation matrix R of the I axis of the rotatable pan/tilt head relative to 0 DEG1According to the transformation matrix relation between the laser radar and the visible light cameralidarAcam＝lidarArot1·R1·rot1AcamIs calibrated oncelidarAcamThe total of 6 degrees of freedom of rotation + translation is known quantity, and similarly,lidarArot1、rot1Acamthere are 12 degrees of freedom in total, sincerot1AcamThe y-axis component and the z-axis component in the translation are both 0, so that 6+ 4-10 degrees of freedom are in total and are unknown, and therefore, the calibration is performed at least twicelidarAcamThrough 2 times and more measurement, 6 multiplied by 2-12 degrees of freedom can be obtained as constraint > 10 degrees of freedom, and an external parameter matrix of the laser radar and the I axis of the rotatable holder is obtained through a nonlinear optimization modelidarArot1；
When the relative position of the I shaft of the rotatable cloud platform and the II shaft of the rotatable cloud platform and the relative position of the II shaft of the rotatable cloud platform and the visible light camera are calibrated, the rotatable cloud platform is fixedThe I axle of platform, as above, rotates the II axle of rotatable cloud platform 2 angles at least, and the coordinate system definition of the II axle of rotatable cloud platform is: the origin is located at the intersection point of the axis II of the rotatable holder and the optical center rotation plane of the visible light camera, the axis x points to the optical center of the visible light camera, the axis z is consistent with the positive rotation direction (the rotation direction of the second angle relative to the first angle), and the axis y is obtained through a right-hand rule. External parameter matrix for calibrating laser radar and visible light cameralidarAcamObtaining a rotation matrix R of the I axis of the rotatable pan/tilt head relative to 0 DEG1The axis II of the rotatable head is opposite to the rotation matrix R at 0 DEG2External parameter matrix combining laser radar and I axis of rotatable holderlidarArot1According to the transformation matrix relation between the laser radar and the visible light camera,lidarAcam＝lidarArot1·R1·rot1Arot2·R2·rot2Acamobtaining an external parameter matrix of an axis I of the rotatable holder and an axis II of the rotatable holder in a nonlinear optimization moderot1Arot2And the II axis of the rotatable holder and the external parameter matrix of the visible light camerarot2Acam；
Taking the rotation angles of the I axis of the rotatable tripod head and the II axis of the rotatable tripod head as known variables, acquiring a rotation matrix R1 (alpha) when the I axis of the rotatable tripod head rotates by a certain angle alpha, acquiring a rotation matrix R2 (beta) when the II axis of the rotatable tripod head rotates by another angle beta, and acquiring an external reference matrix R2 (beta) of the laser radar and the I axis of the rotatable tripod headlidarArot1External parameter matrix of I shaft of rotatable holder and II shaft of rotatable holderrot1Arot2And the II axis of the rotatable holder and the external parameter matrix of the visible light camerarot2AcamFor known quantity, according to the transformation matrix relation between the laser radar and the visible light cameralidarAcam(α，β)＝lidarArot1·R1(α)·rot1Arot2·R2(β)·rot2AcamAnd real-time pose calculation of the laser radar and the visible light camera is obtained in a nonlinear optimization mode.
In the nonlinear optimization method, the objective function is an error value of the calibration external parameter, the optimization variable is an unknown quantity of 10 degrees of freedom, and finally whether the calibration is successful or not can be judged according to the error magnitude, and the square root of the error is a more ideal result when the square root is less than one percent. Nonlinear optimization algorithms are various, and can be classified into line search and confidence domains according to different iteration modes, and can be classified into Newton methods, quasi-Newton methods and the like according to different second-order approximation modes.
In the technical scheme, the calibration of the laser radar and the holder is skillfully completed by means of the external reference calibration of the laser radar and the visible light camera installed on the holder, and the calibration is realized by changing different observation angles of the holder. The existence of the movable equipment and the holder can greatly increase the measurement range of the visible light camera and the infrared temperature measurement system.
An electronic device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method.
A storage medium having stored thereon a computer program which, when executed by a processor, implements the method.
In one example:
the portable infrared temperature measurement system includes: the system comprises a fixed-focus visible light camera, a fixed-focus infrared camera, a rotatable holder, a laser radar and a mobile device, wherein the visible light camera and the infrared camera are mounted on the mobile device with the laser radar through the rotatable holder, and have the same rotating effect and partial overlapped view fields relative to the rotatable holder;
s1: constructing a target: the black and white chessboard grid calibration plate comprises a black and white chessboard grid calibration plate, a heat insulation layer and a constant temperature heating plate which are sequentially stacked in equal size, wherein a through hole is arranged in a penetrating manner in the target, the circle center of the through hole is superposed with the center of each chessboard, and the black and white chessboard grid calibration plate comprises 7 multiplied by 8 chessboard grids;
s2: the visible light camera and the infrared camera are both positioned at one side facing the black and white checkerboard calibration board, respectively shoot targets, when shooting the targets, preheating the targets, forming clear images by the two cameras, shooting the targets by the visible light camera to obtain images, ensuring the integrity of the targets in the images, carrying out corner point detection by using a findchessboardcorrers function in OpenCV after graying the checkerboard images shot by the visible light camera, constructing a plane homography matrix, calculating an internal reference matrix and a distortion coefficient of the visible light camera, shooting the targets by the infrared camera to obtain the images, ensuring the integrity of the targets in the images, carrying out detection by using a findCirclesGrid function in OpenCV after graying the infrared source images shot by the infrared temperature measuring camera, constructing the plane homography matrix, and calculating the internal reference matrix and the distortion coefficient of the infrared camera,
s3: shooting a target by the visible light camera and the infrared camera, changing the pose, shooting a plurality of groups of images on the target, ensuring the integrity of the target, obtaining a plurality of pairs of images with different poses, calculating the external parameter matrixes of the visible light camera and the infrared camera by combining the internal parameter matrixes and the distortion coefficients of the visible light camera and the infrared camera,
s4: fixing the II axis of the rotatable tripod head, rotating the I axis of the rotatable tripod head by at least 2 angles, and calibrating the external parameter matrix of the laser radar and the visible light cameralidarAcamObtaining a rotation matrix R of the I axis of the rotatable pan/tilt head relative to 0 DEG1According to the transformation matrix relation between the laser radar and the visible light cameralidarAcam＝lidarArot1·R1·rot1AcamIs calibrated oncelidarAcamThe total of 6 degrees of freedom of rotation + translation is known quantity, and similarly,lidarArot1、rot1Acamthere are 12 degrees of freedom in total, sincerot1AcamThe y-axis component and the z-axis component in the translation are both 0, so that 6+ 4-10 degrees of freedom are in total and are unknown, and therefore, the calibration is performed at least twicelidarAcamObtaining the external parameter matrix of the laser radar and the I axis of the rotatable holder in a nonlinear optimization mode through 2 or more measurementslidarArot1(ii) a The angle of the II shaft is fixed to be 0, and the I shaft is respectively rotated toExternal parameter matrixes of radar and camera at 45 degrees, 0 degrees and 45 degrees for calibrating 3 positions, (b) and (c)lidarAcam)1，(lidarAcam)2，(lidarAcam)3Corresponding to a rotation matrix of 3 angles simultaneously, (R)1)1，(R1)2，(R1)3Wherein the unknown parameter islidarArot1Androt1Acamconstructing the optimized objective function as f | | | x1||2+||x2||2+||x3||2Wherein x is1＝log((lidarAcam)1 -1*lidarArot1*(R1)1*rot1Acam)，x2＝log((lidarAcam)2 -1*lidarArot1*(R1)2*rot1Acam)，x3＝log((lidarAcam)3 -1*lidarArot1*(R1)3*rot1Acam) The log () function is a logarithmic mapping of the Euclidean transform, and is finally obtained by minimizing the objective functionlidarArot1Androt1Acam。
s5: the I axle of fixed rotatable cloud platform rotates 2 at least angles in the II axle of rotatable cloud platform, and the coordinate system definition of the II axle of rotatable cloud platform is: the origin is located at the intersection point of the axis II of the rotatable holder and the optical center rotation plane of the visible light camera, the axis x points to the optical center of the visible light camera, the axis z is consistent with the positive rotation direction (the rotation direction of the second angle relative to the first angle), and the axis y is obtained through a right-hand rule. External parameter matrix for calibrating laser radar and visible light cameralidarAcamObtaining a rotation matrix R of the I axis of the rotatable pan/tilt head relative to 0 DEG1The axis II of the rotatable head is opposite to the rotation matrix R at 0 DEG2External parameter matrix combining laser radar and I axis of rotatable holderlidarArot1According to the transformation matrix relation between the laser radar and the visible light camera,lidarAcam＝lidarArot1·R1·rot1Arot2·R2·rot2Acamobtaining an external parameter matrix of an axis I of the rotatable holder and an axis II of the rotatable holder in a nonlinear optimization moderot1Arot2And the II axis of the rotatable holder and the external parameter matrix of the visible light camerarot2Acam(ii) a Fixed I-axis angle is 0, when R is1As a unit matrix, and then respectively rotating the II axis to-45 degrees, 0 degrees and 45 degrees to mark the external parameter matrixes of the radar and the camera at 3 positions, (b)lidarAcam)1，(lidarAcam)2，(lidarAcam)3Corresponding to a rotation matrix of 3 angles simultaneously, (R)2)1，(R2)2，(R3)3Wherein the unknown parameter isrot1Arot2Androt2Acamconstructing the optimized objective function as f | | | x1||2+||x1||2+||x1||2Wherein x is1＝log((lidarAcam)1 -1*lidarArot1*R1*rot1Arot2*(R2)1*rot2Acam)，x2＝log((lidarAcam)2 -1*lidarArot1*R1*rot1Arot2*(R2)2*rot2Acam)，x3＝log((lidarAcam)3 -1*lidarArot1*R1*rot1Arot2*(R2)3*rot2Acam) Finally, the target function is minimized to obtainrot1Arot2Androt2Acam。
s6: taking the rotation angles of the I axis of the rotatable pan-tilt and the II axis of the rotatable pan-tilt as known variables, obtaining a rotation matrix R1 (alpha) when the I axis of the rotatable pan-tilt rotates by a certain angle alpha, and obtaining a rotation moment when the II axis of the rotatable pan-tilt rotates by another angle betaArray R2 (beta) with reference to the laser radar and the I-axis of the rotatable pan and tilt headlidarArot1External parameter matrix of I shaft of rotatable holder and II shaft of rotatable holderrot1Arot2And the II axis of the rotatable holder and the external parameter matrix of the visible light camerarot2AcamFor known quantity, according to the transformation matrix relation between the laser radar and the visible light cameralidarAcam(α，β)＝lidarArot1·R1(α)·rot1Arot2·R2(β)·rot2AcamAnd real-time pose calculation of the laser radar and the visible light camera is obtained in a nonlinear optimization mode. According to the formulalidarAcam(α，β)＝lidarArot1·R1(α)·rot1Arot2·R2(β)·rot2AcamAnd substituting the actual angles a and b, and multiplying to obtain the relative position of the radar and the camera.
S7: how to directly obtain the relative position of the laser radar and the infrared camera based on S6 according to a formulalidarAinfrared(a,b)＝lidarAcam(a,b)*camAinfraredAnd substituting the angles a and b to obtain the relative position of the radar and the infrared.
The number of apparatuses and the scale of the process described herein are intended to simplify the description of the present invention. Applications, modifications and variations of the present invention will be apparent to those skilled in the art.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.
Claims (7)
1. The automatic calibration method of the mobile infrared temperature measurement system comprises the following steps: the automatic calibration method comprises the following steps of fixing a focus visible light camera, a focus infrared camera, a rotatable holder, a laser radar and a mobile device, wherein the visible light camera and the infrared camera are installed on the mobile device with the laser radar through the rotatable holder, and have the same rotation effect and partial overlapped view fields relative to the rotatable holder, and the automatic calibration method is characterized by comprising the following steps of: and calibrating the relative position of the visible light camera and the infrared camera, and calibrating the relative position of the laser radar and the visible light camera by the rotatable holder at different rotation angles to obtain the real-time relative position of the laser radar and the infrared camera.
2. The automatic calibration method of the mobile infrared temperature measurement system according to claim 1, wherein the specific implementation manner for calibrating the relative position of the visible light camera and the infrared camera is as follows: the method comprises the steps of shooting a target by a visible light camera, obtaining an image, calculating an internal reference matrix and a distortion coefficient of the visible light camera, shooting the target by an infrared camera, obtaining the image, calculating the internal reference matrix and the distortion coefficient of the infrared camera, shooting the target by the visible light camera and the infrared camera, changing the pose, obtaining a plurality of pairs of images in different poses, and calculating external reference matrices of the visible light camera and the infrared camera by combining the internal reference matrix and the distortion coefficient of the visible light camera and the infrared camera.
3. The automatic calibration method of the mobile infrared temperature measurement system according to claim 2, wherein the target comprises a black and white checkerboard grid calibration board, a thermal insulation layer and a constant temperature heating board which are stacked in sequence in equal size, the target is provided with through holes in a penetrating manner, the circle centers of the through holes coincide with the centers of the checkerboards, and the number of the through holes and the number of the checkerboard corner points need to determine at least a unique spatial plane;
the method comprises the steps of preheating a target before shooting the target, enabling a visible light camera and an infrared camera to be located on one side facing a black and white checkerboard calibration plate, carrying out corner point detection and extraction on an image obtained by shooting the target by the visible light camera, carrying out dot detection and extraction on the image obtained by shooting the target by the infrared camera, constructing a plane homography matrix, and calculating an external reference matrix between the visible light camera and the infrared camera.
4. The automatic calibration method of the mobile infrared temperature measurement system according to claim 1, wherein the specific implementation manner of the relative position of the laser radar and the visible light camera at different rotation angles of the rotatable holder is as follows: calibrating the relative position of the laser radar and an axis I of the rotatable holder, and then calibrating the relative position of the axis I of the rotatable holder and an axis II of the rotatable holder and the relative position of the axis II of the rotatable holder and the visible light camera to obtain the relative position of the laser radar and the visible light camera;
wherein the I axis of the rotatable pan/tilt is mounted on the mobile device.
5. The automatic calibration method of the mobile infrared temperature measurement system according to claim 4, wherein when calibrating the relative position of the laser radar and the I axis of the rotatable pan/tilt head, the II axis of the rotatable pan/tilt head is fixed, the I axis of the rotatable pan/tilt head is rotated by at least 2 angles, the outer reference matrix of the laser radar and the visible light camera is calibrated, the rotation matrix of the I axis of the rotatable pan/tilt head relative to 0 ° is obtained, and the outer reference matrix of the laser radar and the I axis of the rotatable pan/tilt head is obtained by a nonlinear optimization method according to the transformation matrix relationship of the laser radar and the visible light camera;
when the relative position of an I axis of a rotatable tripod head and an II axis of the rotatable tripod head and the relative position of the II axis of the rotatable tripod head and a visible light camera are calibrated, the I axis of the rotatable tripod head is fixed, the II axis of the rotatable tripod head is rotated for at least 2 angles, the external reference matrix of a laser radar and the visible light camera is calibrated, the rotation matrix of the I axis of the rotatable tripod head relative to 0 degree is obtained, the rotation matrix of the II axis of the rotatable tripod head relative to 0 degree is obtained by combining the external reference matrix of the laser radar and the I axis of the rotatable tripod head, and the external reference matrix of the I axis of the rotatable tripod head and the II axis of the rotatable tripod head and the external reference matrix of the rotatable tripod head and the visible light camera are obtained in a nonlinear optimization mode according to the transformation matrix relation of the laser radar and the visible light;
the method comprises the steps of taking the rotation angle of an axis I of a rotatable cloud platform and an axis II of the rotatable cloud platform as a known variable, obtaining a rotation matrix when the axis I of the rotatable cloud platform rotates for a certain angle, taking an external parameter matrix of a laser radar and the axis I of the rotatable cloud platform, an external parameter matrix of the axis I of the rotatable cloud platform and the axis II of the rotatable cloud platform, and an external parameter matrix of the axis II of the rotatable cloud platform and a visible light camera as known variables, and obtaining real-time pose calculation of the laser radar and the visible light camera in a nonlinear optimization mode according to the transformation matrix relation of the laser radar and the visible light camera.
6. An electronic device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of any of claims 1-5.
7. Storage medium on which a computer program is stored which, when being executed by a processor, carries out the method of any one of claims 1 to 5.
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