CN115272491A - Binocular PTZ camera dynamic self-calibration method - Google Patents
Binocular PTZ camera dynamic self-calibration method Download PDFInfo
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Abstract
A binocular PTZ camera dynamic self-calibration method solves the problem of calibrating parameters of a PTZ binocular camera after zooming and in-situ rotation adjustment, and belongs to the technical field of active vision. The invention comprises the following steps: s1, initially calibrating a binocular PTZ camera to obtain initial internal parameters and binocular initial external parameters of two monocular cameras; s2, according to the obtained initial internal reference and binocular initial external reference, respectively carrying out dynamic self-calibration on two monocular cameras in the binocular PTZ camera by using an infinite homography constraint method to obtain an internal reference sum after the two monocular cameras move and a front-back rotation matrix sum of the two monocular cameras after the two monocular cameras move; and S3, obtaining the pose relationship of the two monocular cameras after the movement according to the view relationship of the two monocular cameras before and after the movement and the initial pose relationship of the two monocular cameras, completing self-calibration, and obtaining the external parameters of the binocular PTZ camera after the movement.
Description
Technical Field
The invention relates to a binocular PTZ camera dynamic self-calibration method, and belongs to the technical field of active vision.
Background
Various diagnostic instruments are installed in the inertial confinement nuclear fusion spherical vacuum target chamber, and in the working and debugging process, the instruments enter and exit from the central accessory of the target chamber through a flange port, so that collision risks exist among the instruments, and the problem of collision detection among the moving instruments needs to be solved.
The main approach for solving the problem is to measure by a plurality of cameras distributed outside the target chamber, the traditional binocular vision system is limited by the installation positions of the cameras, the shooting angle and the range are fixed, the target cannot be dynamically tracked, the observation visual angle is changed, and the target is easily lost due to the movement of the target or the shielding of the cameras; traditional binocular vision system camera focus is fixed can't change multiplying power adjustment visual field size, and measurement accuracy is limited, and above-mentioned problem can be solved to PTZ binocular camera system, but has focusing and directional regulation back internal and external reference and change, can't solve the problem that PTZ binocular camera from demarcating with the calibration plate in the online environment recalibration.
Disclosure of Invention
The invention provides a binocular PTZ camera dynamic self-calibration method, which aims at the problem of calibrating parameters of a PTZ binocular camera after zooming and in-situ rotation adjustment.
The invention discloses a binocular PTZ camera dynamic self-calibration method, which comprises the following steps:
s1, initially calibrating a binocular PTZ camera to obtain initial internal parameters K of two monocular cameras 0 And binocular initial external parameters;
the binocular initial extrinsic parameter includes an initial translation vector T between two monocular cameras 0 And an initial rotation matrix R between the two monocular cameras 0 ；
S2, according to the obtained initial internal reference and binocular initial external reference, respectively carrying out dynamic self-calibration on two monocular cameras in the binocular PTZ camera by using an infinite homography constraint method to obtain internal reference K of the two monocular cameras after movement j_l And K j_r Two monocular cameras rotate matrix R before and after moving 0_jl And R 0_jr ；
S3, obtaining pose relations of the two monocular cameras after movement according to the view relations of the two monocular cameras before and after movement and the initial pose relations of the two monocular cameras, completing self-calibration, and obtaining external parameters of the binocular PTZ camera after movement;
the extrinsic parameters of the binocular PTZ camera after motion comprise a rotation matrix R between two monocular cameras after motion j And translation vector T j ；
T j ＝R 0_jl T 0 。
Preferably, S2 comprises:
projection point x of the same point in the scene in the front and back view of monocular camera motion 0 And x j ：x i ＝H ij x j ，H ij Representing an infinite homography matrix, x i Representing a projection point, x, in the view at the time of initial calibration j Representing projection points in the j view after any change;
after the monocular camera moves, according to the initial internal reference K 0 Obtaining the internal reference K of the two monocular cameras after movement j_l And K j_r ：
Obtaining a front and back rotation matrix R of the two monocular cameras 0_jl And R 0_jr ：
Infinite homography matrix H ij Can be obtained by adopting the following modes:
the method I comprises the following steps: the fit is calculated from the image measurements.
The second method comprises the following steps: infinite homography matrix H ij Using correspondence of points or lines, orThe fit is calculated based on the image intensity method.
The third method comprises the following steps: detecting and extracting matching line segments in front and rear views of the motion of two monocular cameras by adopting a SOLD2 self-supervision deep learning method, extracting matching points from the matching line segments, and fitting a homography matrix H by using the matching points ij 。
Preferably, in S1, the binocular PTZ camera is initially calibrated by using a checkerboard calibration method as a calibration object.
The invention has the beneficial effects that the invention has the advantages that,
the method comprises the steps of firstly carrying out initial calibration, then using an infinite homography constraint method to realize the internal reference self-calibration of the monocular camera and obtain the rotation matrix before and after the movement of the camera, combining the pose relationship before and after the movement of the two monocular cameras and the pose relationship before and after the movement of the two cameras to realize the binocular self-calibration, and obtaining the external reference result after the movement of the binocular camera.
Drawings
FIG. 1 is a schematic diagram of a binocular PTZ camera dynamic self-calibration method;
FIG. 2 is a relationship of imaging planes before and after a monocular camera is moved;
FIG. 3 is an infinite homography constraint for a corresponding point;
FIG. 4 is a pose relationship before and after the binocular PTZ camera moves;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
The binocular PTZ camera dynamic self-calibration method comprises the following three steps:
firstly, calibrating initial internal and external parameters of a binocular PTZ camera:
carrying out initial calibration on the binocular PTZ camera to obtain initial internal parameters K of two monocular cameras 0 And binocular initial external parameters; the binocular initial extrinsic reference includes an initial translation vector T between two monocular cameras 0 And an initial rotation matrix R between the two monocular cameras 0 ；
Step two, dynamic self-calibration of the two monocular cameras:
respectively carrying out dynamic self-calibration on two monocular cameras in the binocular PTZ camera by using an infinite homography constraint method according to the obtained initial internal reference and the obtained binocular initial external reference, and obtaining the internal reference K after the two monocular cameras move j_l And K j_r Two monocular cameras rotate matrix R before and after moving 0_jl And R 0_jr ；
Step three, binocular dynamic self-calibration:
obtaining the pose relationship of the two monocular cameras after the two monocular cameras move according to the view relationship of the two monocular cameras before and after the two monocular cameras move and the initial pose relationship of the two monocular cameras, completing self-calibration, and obtaining the external parameters of the binocular PTZ camera after the two monocular cameras move;
the extrinsic parameters of the binocular PTZ camera after motion comprise a rotation matrix R between two monocular cameras after motion j And translation vector T j ；
T j ＝R 0_jl T 0 。
The first step in this embodiment:
and selecting a calibration method using a checkerboard calibration board as a calibration object to perform initial calibration on the binocular vision system.
The calibration of the binocular vision system is realized by combining the known structure information of a calibration object with the image of the calibration object acquired by the vision system, the internal parameters of two cameras of the binocular vision system and the external parameters between the two cameras are solved according to the camera imaging principle, the internal parameters of the cameras are mainly influenced by lens parameters, the internal parameters of the cameras represent the spatial relationship between the camera lens and the CCD image sensor, for most cameras with fixed focal lengths, the relative position between the camera lens and the CCD image sensor is fixed and the internal parameters of the cameras are fixed. When a vision system consisting of cameras completes a measurement task, besides internal references, external references also need to be determined, for a monocular camera, the external references are expressed as the spatial position relation between the coordinate system of the monocular camera and the coordinate system of a calibration object, including rotation and translation, which are respectively expressed by a matrix and a vector, and for a binocular vision system, the external references are expressed as the rotation and translation relation of the camera coordinate system of a right camera relative to the camera coordinate system of a left camera. Therefore, initial calibration of the binocular PTZ camera can determine the initial internal reference and the initial external reference of the two cameras. Initial calibration may also be accomplished using conventional methods, such as the Zhang friend calibration method.
Step two in the present embodiment:
after the binocular PTZ camera executes pointing movement, focusing zooming and other operations, internal and external parameters of the camera are changed, and the calibration plate cannot be used again in the working process for recalibration, so that internal parameters changing after the monocular camera moves and rotation matrixes before and after the movement need to be obtained by using a self-calibration method. The projection planes before and after the monocular camera is moved are shown in fig. 2.
Camera projection model and infinite homography matrix constraints: an X-projection of a point in a scene onto the image of a camera can be represented using a projection equation X = PX, P is a 3 × 4 camera projection matrix, the rank of the matrix P is 3, and can be decomposed into P = K (R | t), R and t are represented as the rotation and translation transformation of the camera with the time coordinate system, and the initial parameters K of two monocular cameras 0 And internal reference K after exercise j_l And K j_r Is defined as K. K is as defined in formula (1)Shown in the figure.
Where γ is a warping parameter indicating the degree of warping of a point on the pixel coordinate system in the x-axis and y-axis, and f x ＝αf，f y Where α and β represent the number of pixels per unit distance on the image, the focal length f of the monocular camera is transformed to be represented in the x, y direction as a metric in pixels.
Defining the optical center of the monocular camera as the origin of the coordinate system of the camera, and the monocular camera does not generate any translation transformation when the rotation motion and the focusing change occur, so the projection matrix of each view i of the monocular camera under different angles and magnification states can be represented as:
P i ＝K i [R i |0] (2)
then a point in the scene X = [ X, Y, Z,1 =] T The projection relationship with the projection point x on the image can be expressed as:
since the last column of the projection matrix is zero, the depth of the world point along the ray is insignificant, considering only the projection of the 3D ray X. Thus, in the case of a rotating camera, the projection points of the 3D rays onto the image can be represented by a 3 x 3 matrix transform:
for the same point in the scene, its projections of the 3D ray on the different images are respectively denoted x i ，x j ：
x i Representing a projection point, x, in the view at the time of initial calibration j Representing projection points in the j view after any change;
by elimination in formula (5)
Then, the relationship between two projection points can be obtained, which can pass through an infinite homography matrix H ij In connection with, x i And x j The relationship of (1) is:
x i ＝H ij x j (6)
R ij representing the rotation matrix between the i, j-th two views.
R ij Is an orthogonal matrix satisfying R = R -T Relationship, from which can be derived:
as shown in fig. 3, the initial internal reference K of the camera is obtained by performing initial calibration on the binocular PTZ camera 0 Combining infinite homography matrixes before and after movement, internal reference K after two monocular cameras move j_l And K j_r ：
To obtain K j_l And K j_r Then, a front and back rotation matrix R of the two monocular cameras can be calculated 0_jl And R 0_jr ：
Completing the self-calibration of the monocular camera to obtain the internal reference K after the left camera and the right camera are changed j_l And K j_r And a rotation matrix R 0_jl And R 0_jr 。
Infinite homography matrix H of the present embodiment ij Can be obtained by adopting the following modes:
the first method is as follows: the fit is calculated from the image measurements.
The second method comprises the following steps: infinite homography matrix H ij The fit is calculated using a correspondence of points or lines, or an image intensity-based method.
The third method comprises the following steps: detecting and extracting matching line segments in front and rear views of the motion of two monocular cameras by adopting a SOLD2 self-supervision deep learning method, extracting matching points from the matching line segments, and fitting a homography matrix H by using the matching points ij 。
Step three in this embodiment:
in the binocular vision system of the embodiment, the two monocular cameras can rotate independently, after the rotation motion occurs, the pose relationship between the two monocular cameras changes, namely, the external parameters of the binocular vision system change, and the external parameters of the binocular vision system are obtained through calibration again. As shown in fig. 4, the pose relationship of the two cameras after movement is derived by using the view relationship before and after movement of the left and right monocular cameras and the initial pose relationship of the left and right monocular cameras.
Self-calibration parameter calculation of the binocular PTZ camera: the method comprises the steps of respectively carrying out self-calibration on two monocular cameras in a binocular vision system to obtain rotation matrixes R before and after the motion of the two monocular cameras 0_jl ，R 0_jr Then the rotation matrix R of the two monocular cameras after motion relative to the initial world coordinate system jl ，R jr Comprises the following steps:
wherein R is 0l 、R 0l Which are rotation matrixes of the left camera and the right camera relative to a world coordinate system before motion respectively.
A rotation matrix exists between two cameras of a binocular vision system, and when the initial calibration is carried out, the rotation matrix between the two cameras is set to be R 0 The rotation matrix between the two cameras after the movement is set as R j And according to the rotation relationship between the two cameras and the world coordinate system, the method comprises the following steps:
the camera rotation matrix is an orthogonal matrix, the inverse of which is equal to the transpose of the matrix, i.e. R -1 ＝R T Obtaining the rotation matrix R between two monocular cameras after movement j ：
The translation vector reflects the coordinates of the origin of the coordinate system of the right camera in the coordinate system of the left camera, and the translation vector T between the two monocular cameras after movement can be obtained j ：
T j ＝R 0_jl T 0 (15)
Finally, an external reference result R after the binocular PTZ camera moves can be obtained j 、T j 。
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that various dependent claims and the features described herein may be combined in ways different from those described in the original claims. It is also to be understood that features described in connection with individual embodiments may be used in other described embodiments.
Claims (9)
1. The binocular PTZ camera dynamic self-calibration method is characterized by comprising the following steps:
s1, initially calibrating a binocular PTZ camera to obtain initial internal reference K of two monocular cameras 0 And binocular initial external parameters;
the binocular initial extrinsic parameter includes an initial translation vector T between two monocular cameras 0 And an initial rotation matrix R between the two monocular cameras 0 ；
S2, according to the obtained initial internal parameters and binocular initial external parameters, respectively carrying out dynamic self-calibration on two monocular cameras in the binocular PTZ camera by using an infinite homography constraint method to obtain internal parameters K after the two monocular cameras move j_l And K j_r Two monocular cameras rotate matrix R before and after moving 0_jl And R 0_jr ；
S3, obtaining pose relations of the two monocular cameras after movement according to the view relations of the two monocular cameras before and after movement and the initial pose relations of the two monocular cameras, completing self-calibration, and obtaining external parameters of the binocular PTZ camera after movement;
the extrinsic parameters of the binocular PTZ camera after motion comprise a rotation matrix R between two monocular cameras after motion j And translation vector T j ；
T j ＝R 0_jl T 0 。
2. The binocular PTZ camera dynamic self-calibration method according to claim 1, wherein the S2 comprises:
projection point x of the same point in the scene in the front and back view of monocular camera motion 0 And x j ：x i ＝H ij x j ，H ij Representing an infinite homography matrix, x i Representing a projection point, x, in the view at the time of initial calibration j Representing projection points in the j view after any change;
after the monocular camera moves, according to the initial internal reference K 0 Obtaining the internal reference K of the two monocular cameras after movement j_l And K j_r ：
Obtaining a rotation matrix R before and after the motion of the two monocular cameras 0_jl And R 0_jr ：
3. The binocular PTZ camera dynamic self-calibration method according to claim 2, wherein an infinite homography matrix H in S2 ij The fit is calculated from the image measurements.
4. The binocular PTZ camera dynamic self-calibration method according to claim 2, wherein an infinite homography matrix H in S2 ij The fit is calculated using a correspondence of points or lines, or an image intensity-based method.
5. The binocular PTZ camera dynamic self-calibration method according to claim 2, wherein the infinity homography in S2Character matrix H ij The acquisition method comprises the following steps:
detecting and extracting matching line segments in front and rear views of the motion of two monocular cameras by adopting a SOLD2 self-supervision deep learning method, extracting matching points from the matching line segments, and fitting a homography matrix H by using the matching points ij 。
6. The binocular PTZ camera dynamic self-calibration method according to claim 1, wherein in S1, the binocular PTZ camera is initially calibrated by using a calibration method using a checkerboard calibration board as a calibration object.
7. The binocular PTZ camera dynamic self-calibration method according to claim 2, wherein initial internal reference K of the two monocular cameras 0 And internal reference K after exercise j_l And K j_r Is defined as K:
where γ is a warping parameter indicating the degree of warping of a point on the pixel coordinate system in the x-axis and y-axis, and f x ＝αf，f y Where α and β represent the number of pixels per unit distance on the image, the focal length f of the monocular camera is transformed to be represented in the x, y direction as a metric in pixels.
8. A computer-readable storage device, storing a computer program, wherein the computer program when executed implements the method of any of claims 1 to 7.
9. A binocular PTZ camera dynamic self-calibration apparatus comprising a storage device, a processor and a computer program stored in the storage device and executable on the processor, wherein the processor executes the computer program to implement the method of any one of claims 1 to 7.
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