CN105430333B - A kind of method and device for being back-calculated gunlock distortion factor in real time - Google Patents
A kind of method and device for being back-calculated gunlock distortion factor in real time Download PDFInfo
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Abstract
A kind of method and device for being back-calculated gunlock distortion factor in real time, this method comprise the following steps：Obtain a gunlock picture, obtain two with Apparatus for feeding balls as disintegrating members image, per adjacent two ball machine images in have it is overlapping, ball machine image and gunlock image it is interior have it is overlapping；The characteristic point of ball machine image is extracted respectively and is matched；The homography matrix established respectively according to the characteristic point of adjacent two ball machine images match between two ball machine images；Ball machine distortion factor is calculated using the homography matrix between adjacent two ball machine images；The characteristic point of a ball machine image and gunlock image is extracted respectively and is matched；The homography matrix established using the characteristic point matched between ball machine image and gunlock image between ball machine image and gunlock image；Gunlock distortion factor is calculated using the homography matrix between ball machine distortion factor, ball machine image and gunlock image.The present invention can calculate accurate gunlock distortion factor in real time with the change of focal length, and algorithm is simple, efficiency high.
Description
Technical Field
The invention relates to the technical field of video monitoring, in particular to a method and a device for real-time backcalculating a distortion coefficient of a bolt face.
Background
Security monitoring is an important part in the current safe city construction, and the traditional video monitoring has the defects that target detail information cannot be captured in a large scene, other surrounding moving targets can be ignored if the target detail information is concerned, and real-time intelligent analysis, target tracking, track recording, characteristic picture snapshot and the like cannot be realized, so that the modern security monitoring needs an intelligent security means to assist the related protection monitoring. And the video monitoring scheme of the gun-ball linkage system (so-called gun-ball linkage refers to 'one gun with multiple balls', wherein 'one gun' is a high-definition network gun type camera and 'multiple balls' are high-definition network ball type cameras), adopts the advanced video analysis algorithm, image processing and other technologies, greatly improves the practicability and efficiency of the security system, and compared with the traditional video monitoring, the video monitoring system not only can 'see completely and clearly' on the scene, but also can more efficiently capture and alarm suspicious events and suspicious crowd/individual targets, thereby avoiding the phenomenon of missing report in artificial monitoring, and truly achieving the intellectualization of modern security.
And detecting the target in the gun camera image, determining the orientation of the target, registering the dome camera image with the gun camera image, and constructing a projection matrix to obtain the orientation of the target in a dome camera coordinate system, so as to obtain an initial position for controlling the dome camera to track the target. However, the conventional bolt machine needs to obtain a monitoring area in a large range as possible, and often uses a wide-angle lens, which has large distortion, so that coordinate mapping between the gun and the gun is not linear mapping relation, which seriously affects calibration accuracy, and thus calibration of a camera distortion coefficient is an urgent technical problem to be solved. With the progress of the technology, the resolution of the monitoring camera is higher and higher, and the image distortion calibration precision can meet the requirements of engineering gradually. However, the traditional calibration method utilizes a control field to perform strict calibration, which is too expensive, large in workload and low in efficiency. Zhang Zhengyou professor of Microsoft institute, the method for checking and correcting by using the checkerboard, i.e. Zhang's calibration method, has very low requirements on required experimental sites and equipment, greatly reduces the checking and correcting cost and is widely applied. However, the Zhang-Zhengyou calibration method needs to calibrate each set of equipment independently before installation, otherwise, because of individual differences, all the equipment adopt the same set of distortion coefficients, which is inaccurate; in addition, in the installation process of the equipment, real-time focusing is required according to a monitoring scene, the distortion coefficient can also change along with the change of the focal length, and obviously the Zhang-Zhengyou calibration method cannot adapt to the requirement of real-time calibration. While some other camera self-checking methods utilize light beam adjustment models, such as SFM (Structure from Motion) technology or space-three technology in photogrammetry, these methods are not suitable for the situation where the movement of the rifle bolt and the ball machine is limited, for example, the rifle bolt is still, and the ball machine rotates approximately concentrically, the algorithm is completely ineffective.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defects that the distortion coefficient needs to be checked and corrected in advance through a control field or a calibration board, the method cannot be applied to the individual difference of the equipment, and the change of the focal length of the bolt after the equipment is installed can cause the change of the distortion coefficient, so as to provide a method and a device for calculating the distortion coefficient of the bolt in real time.
The invention also aims to overcome the defect that the self-calibration method of the beam adjustment model based on the stereoscopic vision three-dimensional reconstruction in the prior art cannot be suitable for the situation that the gunlock is not moved and the movement of the equipment with approximately concentric rotation of the dome camera is limited, thereby providing a method and a device for relatively simplified real-time calculation of the distortion coefficient of the gunlock without calculating the three-dimensional structure of the scenery.
Therefore, the invention provides the following technical scheme:
a method for real-time backcalculating distortion coefficients of a bolt face comprises the following steps:
the method comprises the steps that a gun camera is used for obtaining a gun camera picture, a ball machine is used for keeping rotating and shooting at the same focal length to obtain more than two ball machine images, at least the shooting contents of every two adjacent ball machine images are overlapped, and the ball machine images are overlapped with the shooting contents of the gun camera image;
respectively extracting the characteristic points of the dome camera images, and matching the characteristic points of every two adjacent dome camera images;
respectively establishing a homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images, wherein the homography matrix comprises a dome camera distortion coefficient to be calculated;
calculating the distortion coefficient of the dome camera by utilizing the homography matrix between the images of the two adjacent dome cameras;
respectively extracting the characteristic points of a dome camera image and a gun camera image, and matching the characteristic points of the dome camera image and the gun camera image;
establishing a homography matrix between the dome camera image and the gun camera image by utilizing matched characteristic points between the dome camera image and the gun camera image, wherein the homography matrix comprises a gun camera distortion coefficient to be calculated;
and calculating the distortion coefficient of the gunlock by using the distortion coefficient of the dome camera and the homography matrix between the dome camera image and the gunlock image.
Preferably, the step of establishing a homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images respectively comprises the following steps:
respectively obtaining undistorted coordinates corresponding to matched feature points between two adjacent dome camera images, wherein the undistorted coordinates are a function of the distortion coefficient of the dome camera to be calculated;
and establishing a homography matrix between the two adjacent dome camera images according to the undistorted coordinates respectively corresponding to the matched characteristic points between the two adjacent dome camera images.
Preferably, the step of respectively acquiring undistorted coordinates corresponding to the feature points matched between two adjacent dome camera images includes:
respectively calculating the coordinates and the radius of the characteristic points of the dome camera image relative to the main point of the dome camera;
and acquiring corresponding undistorted coordinates according to the coordinates and radius of the characteristic points of the dome camera image relative to the dome camera principal point, the coordinates of the dome camera principal point and the dome camera distortion coefficient to be calculated.
Preferably, the step of calculating the distortion coefficient of the dome camera by using the homography matrix between two adjacent dome camera images comprises the following steps:
presetting an initial value of the distortion coefficient of the dome camera, and correspondingly acquiring an initial value of a homography matrix between every two adjacent dome camera images;
acquiring the increment of the distortion coefficient of the dome camera by using a first-order Newton iteration method according to the homography matrix between every two adjacent dome camera images;
and obtaining the distortion coefficient of the dome camera according to the initial value of the distortion coefficient of the dome camera and the increment of the distortion coefficient of the dome camera.
Preferably, the increment of the distortion coefficient of the dome camera is calculated by the following formula:
wherein,
F(P0) The initial value of the homography function between the m adjacent dome camera images corresponding to the initial value of the preset dome camera distortion coefficient is obtained, and the m homography functions are respectively in one-to-one correspondence with the homography matrixes between the m adjacent dome camera images;
wherein,i.e. P is the distortion coefficient (k) of the ball machine1,k2,k3,p1,p2) And m homography matrices (H)1,H2…Hm) (ii) a F (P) is a homography function corresponding to m homography matrixes containing the distortion coefficient of the dome camera; n is the same asNumber of points, F11…FnmN homonymous points respectively correspond to m homography functions.
Preferably, the method further comprises the step of converting the distortion coefficient of the dome camera into a forward distortion coefficient:
acquiring distorted image coordinate sampling points of a plurality of dome camera images, and calculating corresponding non-distorted image coordinates according to the distortion coefficient of the dome camera;
respectively establishing corresponding equations of distortion-free image coordinates, forward distortion coefficients and distorted coordinate sampling points;
and solving the forward distortion coefficient.
Preferably, the step of calculating the distortion coefficient of the bolt face by using the distortion coefficient of the ball machine and the homography matrix between the image of the ball machine and the image of the bolt face comprises:
presetting an initial value of a gunlock distortion coefficient, and correspondingly acquiring an initial value of a homography matrix between a dome camera image and a gunlock image;
acquiring the increment of the distortion coefficient of the gunlock by utilizing a first-order Newton iteration method according to the homography matrix between the dome camera image and the gunlock image;
and acquiring the distortion coefficient of the gunlock according to the distortion coefficient of the dome camera and the increment of the distortion coefficient of the gunlock.
Preferably, the increment of the bolt distortion coefficient is calculated by the following formula:
wherein,
F′(P′0) The initial value of the homography function between the dome image and the gunlock image corresponding to the initial value of the preset gunlock distortion coefficientHomography functions between the images of the gunlock correspond to homography matrixes of the images;
wherein,i.e. P is the distortion coefficient of the boltHomography matrix (H ') between the dome camera image and the gun camera image, and F (P') is a homography function corresponding to the homography matrix between the dome camera image and the gun camera image; f'1…F′rIs a homography function between the dome camera image and the gun camera image respectively corresponding to the r homonymous points.
An apparatus for real-time backcalculating a distortion coefficient of a bolt face, comprising:
the image acquisition unit is used for acquiring a gunlock image by using a gunlock, and rotationally shooting by using a dome camera under the same focal length to acquire more than two dome camera images, wherein the shot contents of at least two adjacent dome camera images are overlapped, and the dome camera images are overlapped with the shot contents of the gunlock images;
the first characteristic point extracting and matching unit is used for respectively extracting the characteristic points of the dome camera images and matching the characteristic points of every two adjacent dome camera images;
the first homography matrix establishing unit is used for establishing a homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images, and the homography matrix comprises a dome camera distortion coefficient to be calculated;
the dome camera distortion coefficient calculation unit is used for calculating the dome camera distortion coefficient by utilizing the homography matrix between the two adjacent dome camera images;
the second characteristic point extracting and matching unit is used for respectively extracting the characteristic points of a dome camera image and a gun camera image and matching the characteristic points of the dome camera image and the gun camera image;
the second homography matrix establishing unit is used for establishing a homography matrix between the dome camera image and the gun camera image by utilizing the matched characteristic points between the dome camera image and the gun camera image, and the homography matrix comprises a gun camera distortion coefficient to be calculated;
and the gunlock distortion coefficient calculating unit is used for calculating the gunlock distortion coefficient by utilizing the dome camera distortion coefficient and the homography matrix between the dome camera image and the gunlock image.
Preferably, the first homography matrix establishing unit includes:
the first undistorted coordinate acquisition unit is used for respectively acquiring undistorted coordinates corresponding to the matched feature points between the two adjacent dome camera images, and the undistorted coordinates are a function of the distortion coefficient of the dome camera to be calculated;
and the first homography matrix acquisition unit is used for establishing a homography matrix between the two adjacent dome camera images according to the undistorted coordinates respectively corresponding to the matched characteristic points between the two adjacent dome camera images.
Preferably, the first distortion-free coordinate acquisition unit includes:
the first calculating unit is used for respectively calculating the coordinates and the radius of the characteristic points of the dome camera image relative to the main point of the dome camera;
the first acquisition unit acquires corresponding undistorted coordinates according to the coordinates and radius of the characteristic points of the dome camera image relative to the dome camera principal point, the coordinates of the dome camera principal point and the dome camera distortion coefficient to be calculated.
Preferably, the dome camera distortion coefficient calculation unit includes:
the first initial value calculation unit is used for presetting an initial value of the distortion coefficient of the dome camera and correspondingly acquiring an initial value of a homography matrix between every two adjacent dome camera images;
the first increment calculating unit is used for acquiring the increment of the distortion coefficient of the dome camera by utilizing a first-order Newton iteration method according to the homography matrix between every two adjacent dome camera images;
and the dome camera distortion coefficient acquisition unit is used for acquiring the dome camera distortion coefficient according to the initial value of the dome camera distortion coefficient and the increment of the dome camera distortion coefficient.
Preferably, the device further comprises a conversion unit comprising:
the computing unit is used for acquiring distorted image coordinate sampling points of a plurality of dome camera images and computing corresponding non-distorted image coordinates according to the distortion coefficient of the dome camera;
the equation establishing unit is used for respectively establishing corresponding equations of the distortion-free image coordinates, the forward distortion coefficients and the distorted coordinate sampling points;
and the forward distortion coefficient acquisition unit is used for solving a forward distortion coefficient.
Preferably, the bolt distortion coefficient calculation unit includes:
the second initial value calculation unit is used for presetting an initial value of the gunlock distortion coefficient and correspondingly acquiring an initial value of a homography matrix between the dome camera image and the gunlock image;
the second increment calculating unit is used for acquiring the increment of the distortion coefficient of the gunlock by utilizing a first-order Newton iteration method according to the homography matrix between the dome camera image and the gunlock image;
and the rifle bolt distortion coefficient acquisition unit is used for acquiring the rifle bolt distortion coefficient according to the distortion coefficient of the ball machine and the increment of the rifle bolt distortion coefficient.
The technical scheme of the invention has the following advantages:
the method and the device for calculating the distortion coefficient of the gunlock in real time solve the problem that the traditional distortion coefficient checking method cannot be calibrated again after the gun-ball linkage system is installed, can calculate the changed distortion coefficient in real time along with the change of the focal length, and meet the requirement of focusing at any time according to a monitoring site; in addition, the method does not need to reconstruct the three-dimensional structures of the point cloud and the camera, can calculate the accurate distortion coefficient of the image of the gunlock only through automatic matching and homography, simplifies the flow and the mathematical model, has higher algorithm efficiency, and thus does not increase the calculation burden of the operation unit of the camera.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for real-time backcalculating distortion coefficients of a bolt face according to embodiment 1 of the present invention;
FIG. 2 is a flowchart of establishing a homography matrix between two adjacent dome camera images in embodiment 1 of the present invention;
FIG. 3 is a flowchart of establishing an undistorted coordinate equation corresponding to a ball machine image feature point in embodiment 1 of the present invention;
FIG. 4 is a flowchart of calculating the distortion coefficient of the dome camera in embodiment 1 of the present invention;
FIG. 5 is a flowchart of converting the distortion coefficient of the dome camera into a forward distortion coefficient in embodiment 1 of the present invention;
fig. 6 is a flowchart of calculating a distortion coefficient of a bolt face in embodiment 1 of the present invention;
fig. 7 is a schematic block diagram of an apparatus for real-time backcalculating distortion coefficients of a bolt face according to embodiment 2 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
Example 1
The embodiment provides a method for real-time backcalculating a distortion coefficient of a bolt face, as shown in fig. 1, comprising the following steps:
s1: the method comprises the steps of obtaining a picture of a gunlock by using the gunlock, and obtaining more than two images of the dome camera by using the dome camera to rotate and shoot at the same focal length, wherein at least the shot contents of every two adjacent images of the dome camera are overlapped, and the shot contents of the image of the dome camera and the shot contents of the picture of the gunlock are overlapped. In a general gun and ball linkage system, the field of view of a gun is wide, and a ball machine performs rotary shooting in the field of view of the gun. In this step, the overlapping degree of the shot contents of two adjacent dome camera images among two or more dome camera images is preferably about 80%, and can be obtained by controlling the angular velocity of the rotation of the dome camera and the shooting interval. In the dome camera images, the shot contents can be overlapped between two other dome camera images except for two adjacent dome camera images, and if the content overlapping degree between the two dome camera images meets the requirement, namely the matched feature points are enough, the homography matrix between the two dome camera images can be calculated. In addition, the distortion coefficient of the dome camera is related to the focal length of the dome camera, so the dome camera needs to rotate and shoot at the same focal length to obtain a dome camera image.
S2: and respectively extracting the characteristic points of the dome camera images, and matching the characteristic points of every two adjacent dome camera images. Specifically, a sift algorithm can be adopted to respectively extract the feature points of the dome camera image, and knn is adopted to search and calculate the Euclidean distance of the feature point descriptors for matching.
S3: and respectively establishing a homography matrix between two corresponding dome camera images according to the matched characteristic points of the two adjacent dome camera images, specifically adopting conventional DLT direct linear transformation, and matching with a ransac algorithm to remove gross error points. The homography matrix contains the distortion coefficient of the dome camera to be calculated.
S4: and calculating the distortion coefficient of the dome camera by using the homography matrix between the images of the two adjacent dome cameras. Specifically, an initial homography matrix is used as a constraint model, and a nonlinear least square method is used for calculating the distortion coefficient of the dome camera.
S5: and respectively extracting the characteristic points of a dome camera image and a gun camera image, and matching the characteristic points of the dome camera image and the gun camera image.
S6: and establishing a homography matrix between the dome camera image and the gun camera image by utilizing the matched characteristic points between the dome camera image and the gun camera image, wherein the homography matrix comprises a gun camera distortion coefficient to be calculated.
S7: and calculating the distortion coefficient of the gunlock by using the distortion coefficient of the dome camera and the homography matrix between the dome camera image and the gunlock image.
The method for calculating the distortion coefficient of the gunlock in real time solves the problem that the traditional method cannot be calibrated again after the gun and ball linkage system is installed, can calculate the changed distortion coefficient in real time along with the change of the focal length, and meets the requirement of focusing at any time according to a monitoring site; in addition, the method does not need to reconstruct the three-dimensional structures of the point cloud and the camera, can calculate the accurate distortion coefficient of the image of the gunlock only through automatic matching and homography, simplifies the flow and the mathematical model, has higher algorithm efficiency, and thus does not increase the calculation burden of the operation unit of the camera.
The number of the dome camera images acquired in the embodiment is preferably three or more, so that the constraint is increased, the influence caused by individual large errors is weakened, the stability and the precision of the calculation of the distortion coefficient of the dome camera are improved, and the precision of the distortion coefficient of the gun camera is further improved. For example, images p1, p2 and p3 are overlapped, feature points t1, t2 and t3 are found respectively, if t1 and t2 can match, t2 and t3 can match, but if t3 and t1 may not match, the candidate same-name point is removed. The homonym point refers to a feature point matched between different images, which corresponds to an object point in the real world, and these matched feature points are called homonym points.
Specifically, as shown in fig. 2, the step S3, that is, the step of establishing a homography matrix between two corresponding dome image according to feature points matched between two adjacent dome image, includes:
s31: respectively obtaining undistorted coordinates corresponding to matched feature points between two adjacent dome camera images, wherein the undistorted coordinates are a function of the distortion coefficient of the dome camera to be calculated;
s32: and establishing a homography matrix between the two adjacent dome camera images according to the undistorted coordinates respectively corresponding to the matched characteristic points between the two adjacent dome camera images, wherein the elements of the homography matrix are functions of the distortion coefficients of the dome cameras to be calculated.
Specifically, as shown in fig. 3, the step S31 of obtaining undistorted coordinates corresponding to feature points matched between two adjacent dome camera images includes:
s311: respectively calculating the coordinates and the radius of the characteristic points of the dome camera image relative to the main point of the dome camera;
s312: and acquiring corresponding undistorted coordinates according to the coordinates and radius of the characteristic points of the dome camera image relative to the dome camera principal point, the coordinates of the dome camera principal point and the dome camera distortion coefficient to be calculated, wherein the undistorted coordinates are a function of the dome camera distortion coefficient to be calculated.
Specifically, in step S311, the coordinates of a pair of feature points matched between two adjacent dome image are (x) respectivelyd，yd)、(xd′，yd') and the coordinate of the principal point of the dome camera is (x)0，y0) The coordinate and the radius of the characteristic point of one dome camera image relative to the main point of the dome camera are calculated by the following formula:
wherein f is the focal length of the dome camera when the dome camera shoots the image of the dome camera,the coordinates of the characteristic points of one of the dome camera images relative to the main point of the dome camera.
The coordinates and the radius of the characteristic points of the other dome camera image relative to the main point of the dome camera are calculated by the following formulas:
wherein f is the focal length of the dome camera when the dome camera shoots the image of the dome camera,the coordinates of the corresponding characteristic point of the image of the other ball machine relative to the main point of the ball machine.
In the step S312, the undistorted coordinates corresponding to the feature points matched between two adjacent dome camera images are:
wherein k is1、k2、p1、p2、p3The distortion coefficient of the ball machine to be calculated.
Homography equation between two adjacent dome camera images is x'ud＝HxudI.e. fu(x′d)＝Hfu(xd) And H is a homography matrix between the two adjacent dome camera images. Since the homography matrix has 9 variables, one of which can be set to 1 and two equations can be listed for each pair of matched feature points, at least 4 pairs of matched features are requiredAnd (4) point. And in order to reduce the error, 5 pairs of the above uniformly distributed matching feature points are preferable.
The homography function derived from the above homography equation is:
wherein the homography matrix
From the first-order newton iterations: f (P) ═ F (P)0+Δ)＝F(P0) + J Δ, when F (P) ═ F (P)0When + Δ) ═ 0, J Δ ═ F (P)0) The equation is an iterative equation obtained by linearizing a nonlinear function of which the objective function is a parameter to be estimated. When the total number of the homography matrixes between m adjacent images of the dome camera is m, the parameter vector to be estimated is the homography matrixWherein k is1、k2、k3、p1、p2Distortion coefficient of ball machine H1、H2…HmFor m homography matrices, hi1、hi2、hi3…hi9Which is 9 elements of one of the homographies.
Specifically, as shown in fig. 4, the step S4 of calculating the distortion coefficient of the dome camera by using the homography matrix between two adjacent dome camera images includes:
s41: the initial value of the distortion coefficient of the dome camera is preset, and the initial value of the homography matrix between every two adjacent dome camera images is correspondingly obtained. The initial value of the distortion coefficient of the dome camera can also be preset according to an empirical value or a factory value.
S42: and obtaining the increment of the distortion coefficient of the dome camera by utilizing a first-order Newton iteration method according to the homography matrix between every two adjacent dome camera images.
S43: and obtaining the distortion coefficient of the dome camera according to the initial value of the distortion coefficient of the dome camera and the increment of the distortion coefficient of the dome camera.
In step S41, when the initial value of the distortion coefficient of the dome camera is preset to 0, a priori value or a factory value, the initial value of the homography matrix between two adjacent dome camera images calculated based on the initial value of the distortion coefficient of the dome camera is inaccurate (but is relatively similar to the actual homography matrix), that is, the homography matrix is used to map the feature points of one of the dome camera images to the precise positions of the corresponding points of the other dome camera image. However, in the subsequent steps, the homography matrix is taken as an initial value, the error is gradually reduced as a target, and a nonlinear least square method is utilized to calculate a new homography matrix and a dome camera distortion coefficient which are more accurate.
Specifically, the increment of the distortion coefficient of the dome camera can be calculated by the following formula:
wherein,
F(P0) The initial value of the homography function between the m adjacent dome camera images corresponding to the initial value of the preset dome camera distortion coefficient is obtained, and the m homography functions are respectively in one-to-one correspondence with the homography matrixes between the m adjacent dome camera images;
wherein,i.e. P is the distortion coefficient (k) of the ball machine1,k2,k3,p1,p2) And m homography matrices (H)1,H2…Hm) (ii) a F (P) is a homography function corresponding to m homography matrixes containing the distortion coefficient of the dome camera; n is the number of homologous points, F11…FnmN homonymous points respectively correspond to m homography functions.
In the present embodiment, each of the n points of the same name is preferably selected from at least 3 images of the dome camera whose shooting contents are overlapped. After the feature points of each dome camera image are extracted by adopting a sift algorithm or other feature point algorithms, feature point matching between two adjacent dome camera images is carried out, and homonymous points corresponding to feature points with larger errors are screened out according to whether the same homonymous points corresponding to more than 3 dome camera images can be matched with each other or not, so that the precision of calculating the distortion coefficient of the dome camera and the distortion coefficient of the gun camera is improved. Namely, the n homonymous points are selected according to the calculation requirement from the candidate homonymous points left after the homonymous point corresponding to the feature point with the larger error is screened out.
In accordance withAnd obtaining the distortion coefficient of the dome camera through multiple iterations after obtaining the increment of the distortion coefficient of the dome camera and the increment of the homography matrix between the images of the m adjacent dome cameras.
In addition, the obtained distortion coefficient of the dome camera is a reverse distortion coefficient, so that a subsequent module resamples and distorts a distorted source image conveniently, and pixel points of an undistorted result image are calculated to return to the distorted source image to find corresponding pixel points, so that the embodiment further comprises a step of converting the distortion coefficient of the dome camera into the forward distortion coefficient, and the step comprises the following steps:
firstly, acquiring distorted image coordinate sampling points of a plurality of dome camera images, and calculating corresponding non-distorted image coordinates according to the distortion coefficient of the dome camera, specifically s distorted image coordinate sampling points
The s distortion-free coordinates corresponding to the s distortion-containing coordinate sampling points are
Then, respectively establishing corresponding equations of the distortion-free coordinates, the forward distortion coefficients and the distorted coordinate sampling points, wherein the equations comprise:
wherein,
finally, the forward distortion coefficient (K) is solved according to the equation set1、K2、K3、P1、P2)。
Specifically, in step S5, the specific method of extracting the feature points of one dome image and one gun camera image and matching the feature points of the dome image and the gun camera image is similar to that in step S2, and the feature points of the dome image and the gun camera image are extracted by using the sift algorithm and matched by using knn search. In the gun and ball linkage system to which the technical scheme provided by the embodiment is applied, the gun camera is still, so only one image can be obtained, and the ball camera generally shoots in the visual field range of the gun camera, so that the shooting content of the image of the ball camera is completely overlapped with the shooting content of the image of the gun camera, and in other application systems, the shooting content of the image of the ball camera is also overlapped with the shooting content of the image of the gun camera in a large part. Therefore, a dome camera image and a gun camera image can be selected optionally to extract and match the feature points.
Specifically, step S6 is similar to step S3, and a homography between the dome image and the gunlock image is calculated by matching feature points between them using a conventional direct linear transformation method, and a RANSAC (Random sample consensus) algorithm is cooperatively used to remove coarse difference points. As shown in fig. 5, the specific process is as follows:
s61: respectively calculating the coordinates and the radius of the matched characteristic points between the dome camera image and the gun camera image relative to the corresponding principal points;
s62: obtaining undistorted coordinates corresponding to the characteristic points according to the coordinates and radius of the characteristic points of the dome camera image relative to the main point of the dome camera, the main point coordinates of the dome camera and the calculated dome camera distortion coefficient; obtaining an undistorted coordinate corresponding to the characteristic point according to the coordinate and radius of the characteristic point of the image of the gunlock relative to the principal point of the gunlock, the principal point coordinate of the gunlock and a distortion coefficient of the gunlock to be calculated, wherein the undistorted coordinate is a function of the distortion coefficient of the gunlock to be calculated;
s63: and acquiring a homography matrix between the gun camera image and the ball camera image by using the undistorted coordinates corresponding to the characteristic points of the gun camera image and the undistorted coordinates corresponding to the characteristic points of the ball camera image, wherein elements of the homography matrix are functions of distortion coefficients of the gun camera.
Specifically, as shown in fig. 6, the step of calculating the bolt distortion coefficient in step S7, that is, using the dome camera distortion coefficient and the homography matrix between the dome camera image and the bolt camera image, includes:
s71: presetting an initial value of a gunlock distortion coefficient, and correspondingly acquiring an initial value of a homography matrix between a dome camera image and a gunlock image;
s72: acquiring the increment of the distortion coefficient of the gunlock by utilizing a first-order Newton iteration method according to the homography matrix between the dome camera image and the gunlock image;
s73: and acquiring the distortion coefficient of the gunlock according to the distortion coefficient of the dome camera and the increment of the distortion coefficient of the gunlock.
In step S7, similar to step S4, the distortion coefficient of the bolt is calculated by using a homography matrix between the image of the dome camera and the image of the bolt as a constraint model, the distortion coefficient of the dome camera as a fixed initial value, and a nonlinear least square method.
Specifically, the increment of the bolt distortion coefficient is calculated by the following formula:
wherein,
F′(P′0) The initial value of the homography function between the dome camera image and the gun camera image corresponding to the initial value of the preset gun camera distortion coefficient is obtained, and the homography function between the dome camera image and the gun camera image corresponds to the homography matrix of the homography function;
wherein,i.e. P is the distortion coefficient of the boltAnd homography matrix (H ') between the dome camera image and the gun camera image, and F ' (P ') is a homography function corresponding to the homography matrix between the dome camera image and the gun camera image; f'1…F′rIs a homography function between the dome camera image and the gun camera image respectively corresponding to the r homonymous points. The r homonymous points are also selected according to calculation requirements after homonymous points corresponding to the feature points with larger errors are screened out.
Example 2
The present embodiment provides an apparatus for real-time backcalculating a distortion coefficient of a bolt face, as shown in fig. 7, including:
the image acquisition unit U1 is used for acquiring a gunlock image by using a gunlock, and rotationally shooting by using a dome camera under the same focal length to acquire more than two dome camera images, wherein the shot contents of at least two adjacent dome camera images are overlapped, and the dome camera images are overlapped with the shot contents of the gunlock images;
the first feature point extracting and matching unit U2 is used for respectively extracting feature points of the dome camera images and matching the feature points of every two adjacent dome camera images;
the first homography matrix establishing unit U3 is used for establishing a homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images, wherein the homography matrix comprises a dome camera distortion coefficient to be calculated;
the dome camera distortion coefficient calculation unit U4 is used for calculating the dome camera distortion coefficient by utilizing the homography matrix between two adjacent dome camera images;
the second characteristic point extracting and matching unit U5 is used for respectively extracting the characteristic points of a dome camera image and a gunlock image and matching the characteristic points of the dome camera image and the gunlock image;
the second homography matrix establishing unit U6 is used for establishing a homography matrix between the dome camera image and the gun camera image by utilizing the matched characteristic points between the dome camera image and the gun camera image, and the homography matrix comprises a gun camera distortion coefficient to be calculated;
and the gunlock distortion coefficient calculation unit U7 is used for calculating the gunlock distortion coefficient by using the dome camera distortion coefficient and the homography matrix between the dome camera image and the gunlock image.
The device for real-time calculating the distortion coefficient of the bolt face provided by the embodiment of the invention can calculate the changed distortion coefficient in real time along with the change of the focal length, and meets the requirement of focusing at any time according to a monitoring field.
Specifically, the first homography matrix establishing unit U3 includes:
the first undistorted coordinate acquisition unit is used for respectively acquiring undistorted coordinates corresponding to the matched feature points between the two adjacent dome camera images, and the undistorted coordinates are a function of the distortion coefficient of the dome camera to be calculated;
and the first homography matrix acquisition unit is used for establishing a homography matrix between the two adjacent dome camera images according to the undistorted coordinates respectively corresponding to the matched characteristic points between the two adjacent dome camera images.
Specifically, the first distortion-free coordinate acquisition unit includes:
the first calculating unit is used for respectively calculating the coordinates and the radius of the characteristic points of the dome camera image relative to the main point of the dome camera;
the first acquisition unit acquires corresponding undistorted coordinates according to the coordinates and radius of the characteristic points of the dome camera image relative to the dome camera principal point, the coordinates of the dome camera principal point and the dome camera distortion coefficient to be calculated.
Specifically, in the first calculation unit, a pair of feature point coordinates matched between two adjacent dome image are (x) respectivelyd，yd)、(xd′，yd') and the coordinate of the principal point of the dome camera is (x)0，y0) The coordinate and the radius of the characteristic point of one dome camera image relative to the main point of the dome camera are calculated by the following formula:
wherein f is the focal length of the dome camera when the dome camera shoots the image of the dome camera,the coordinates of the characteristic points of one of the dome camera images relative to the main point of the dome camera.
The coordinates and the radius of the characteristic points of the other dome camera image relative to the main point of the dome camera are calculated by the following formulas:
wherein f is the focal length of the dome camera when the dome camera shoots the image of the dome camera,the coordinates of the corresponding characteristic point of the image of the other ball machine relative to the main point of the ball machine.
In the first obtaining unit, the undistorted coordinates corresponding to the feature points matched between two adjacent dome camera images are respectively:
wherein k is1、k2、k3、p1、p2The distortion coefficient of the ball machine.
Specifically, the sphere distortion coefficient calculation unit U4 includes:
the first initial value calculation unit is used for presetting an initial value of the distortion coefficient of the dome camera and correspondingly acquiring an initial value of a homography matrix between every two adjacent dome camera images;
the first increment calculating unit is used for acquiring the increment of the distortion coefficient of the dome camera by utilizing a first-order Newton iteration method according to the homography matrix between every two adjacent dome camera images;
and the dome camera distortion coefficient acquisition unit is used for acquiring the dome camera distortion coefficient according to the initial value of the dome camera distortion coefficient and the increment of the dome camera distortion coefficient.
Specifically, the increment of the distortion coefficient of the dome camera can be calculated by the following formula:
wherein,
F(P0) The initial value of the homography function between the m adjacent dome camera images corresponding to the initial value of the preset dome camera distortion coefficient is obtained, and the m homography functions are respectively in one-to-one correspondence with the homography matrixes between the m adjacent dome camera images;
wherein,i.e. P is the distortion coefficient (k) of the ball machine1,k2,k3,p1,p2) And m homography matrices (H)1,H2…Hm) (ii) a F (P) is a homography function corresponding to m homography matrixes containing the distortion coefficient of the dome camera; n is the number of homologous points, F11…FnmN homonymous points respectively correspond to m homography functions.
As another specific embodiment, the apparatus further includes a conversion unit, including:
a calculating unit for acquiring distorted image coordinate sampling points of multiple dome camera images, and calculating corresponding non-distorted image coordinates according to the dome camera distortion coefficient, specifically s distorted image coordinate sampling pointsThe s distortion-free coordinates corresponding to the s distortion-containing coordinate sampling points are；
The equation establishing unit is used for respectively establishing corresponding equations of the distortion-free image coordinates, the forward distortion coefficients and the distorted coordinate sampling points, and comprises the following steps:
a forward distortion coefficient obtaining unit for solving a forward distortion coefficient (K)1、K2、K3、P1、P2)。
Specifically, the bolt distortion coefficient calculation unit U7 includes:
the second initial value calculation unit is used for presetting an initial value of the gunlock distortion coefficient and correspondingly acquiring an initial value of a homography matrix between the dome camera image and the gunlock image;
the second increment calculating unit is used for acquiring the increment of the distortion coefficient of the gunlock by utilizing a first-order Newton iteration method according to the homography matrix between the dome camera image and the gunlock image;
and the rifle bolt distortion coefficient acquisition unit is used for acquiring the rifle bolt distortion coefficient according to the distortion coefficient of the ball machine and the increment of the rifle bolt distortion coefficient.
Specifically, the increment of the bolt distortion coefficient is calculated by the following formula:
wherein,
F′(P′0) The initial value of the homography function between the dome camera image and the gun camera image corresponding to the initial value of the preset gun camera distortion coefficient is obtained, and the homography function between the dome camera image and the gun camera image corresponds to the homography matrix of the homography function;
wherein,i.e. P is the coefficient of distortion of the boltAnd homography matrix (H ') between the dome camera image and the gun camera image, and F ' (P ') is a homography function corresponding to the homography matrix between the dome camera image and the gun camera image; f'1…F′rIs a homography function between the dome camera image and the gun camera image respectively corresponding to the r homonymous points.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (14)
1. A method for real-time backcalculating distortion coefficient of a gunlock is characterized by comprising the following steps:
the method comprises the steps that a gun camera is used for obtaining a gun camera picture, a ball machine is used for keeping rotating shooting at the same focal length to obtain more than two ball machine images, the shooting content of every two adjacent ball machine images is overlapped, and the ball machine images are overlapped with the shooting content of the gun camera image;
respectively extracting the characteristic points of the dome camera images, and matching the characteristic points of every two adjacent dome camera images;
respectively establishing a homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images, wherein the homography matrix comprises a dome camera distortion coefficient to be calculated;
calculating the distortion coefficient of the dome camera by utilizing the homography matrix between the two adjacent dome camera images;
respectively extracting the characteristic points of one dome camera image and one gun camera image, and matching the characteristic points of the dome camera image and the gun camera image;
establishing a homography matrix between the dome camera image and the gun camera image by using the matched characteristic points between the dome camera image and the gun camera image, wherein the homography matrix comprises the distortion coefficient of the gun camera to be calculated;
and calculating the distortion coefficient of the gunlock by using the distortion coefficient of the dome camera and a homography matrix between the dome camera image and the gunlock image.
2. The method according to claim 1, wherein the step of establishing the homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images respectively comprises the following steps:
respectively obtaining undistorted coordinates corresponding to matched feature points between two adjacent dome camera images, wherein the undistorted coordinates are a function of the distortion coefficient of the dome camera to be calculated;
and establishing a homography matrix between the two adjacent dome camera images according to the undistorted coordinates respectively corresponding to the matched characteristic points between the two adjacent dome camera images.
3. The method according to claim 2, wherein the step of respectively acquiring undistorted coordinates corresponding to the feature points matched between two adjacent dome camera images comprises:
respectively calculating the coordinates and the radius of the characteristic points of the dome camera image relative to the main point of the dome camera;
and acquiring corresponding undistorted coordinates according to the coordinates and radius of the characteristic points of the dome camera image relative to the dome camera main point, the coordinates of the dome camera main point and the distortion coefficient of the dome camera to be calculated.
4. The method according to any one of claims 1-3, wherein the step of calculating the dome camera distortion coefficient using the homography matrix between the two adjacent dome camera images comprises:
presetting an initial value of the distortion coefficient of the dome camera, and correspondingly acquiring an initial value of a homography matrix between every two adjacent dome camera images;
acquiring the increment of the distortion coefficient of the dome camera by using a first-order Newton iteration method according to the homography matrix between every two adjacent dome camera images;
and obtaining the distortion coefficient of the dome camera according to the initial value of the distortion coefficient of the dome camera and the increment of the distortion coefficient of the dome camera.
5. The method of claim 4, wherein the increment of the ball machine distortion coefficient is calculated by the following formula:
<mrow> <msub> <mi>&Delta;</mi> <mn>1</mn> </msub> <mo>=</mo> <mo>-</mo> <msup> <mrow> <mo>(</mo> <msubsup> <mi>J</mi> <mn>1</mn> <mi>T</mi> </msubsup> <msub> <mi>J</mi> <mn>1</mn> </msub> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <msubsup> <mi>J</mi> <mn>1</mn> <mi>T</mi> </msubsup> <mi>F</mi> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow>
wherein,
F(P0) The initial value of the homography function between the m adjacent dome camera images corresponding to the initial value of the preset dome camera distortion coefficient is obtained, and the m homography functions are respectively in one-to-one correspondence with the homography matrixes between the m adjacent dome camera images;
wherein,that is, P is the distortion coefficient (k) of the ball machine1，k2，k3，p1，p2) And m homography matrices (H)1，H2…Hm) (ii) a F (P) is a homography function corresponding to m homography matrixes containing the distortion coefficient of the dome camera; n is the number of homologous points, F11…FnmN homonymous points respectively correspond to m homography functions.
6. The method of claim 1, further comprising the step of converting the ball machine distortion coefficient to a forward distortion coefficient:
acquiring distorted image coordinate sampling points of a plurality of dome camera images, and calculating corresponding non-distorted image coordinates according to the distortion coefficient of the dome camera;
respectively establishing corresponding equations of the distortion-free image coordinates, the forward distortion coefficient to be solved and the distorted coordinate sampling points;
and solving the forward distortion coefficient.
7. The method of claim 1, wherein the step of calculating the bolt distortion factor using a homography matrix between the dome image, and the bolt image comprises:
presetting an initial value of the distortion coefficient of the gunlock, and correspondingly acquiring an initial value of a homography matrix between the dome camera image and the gunlock image;
acquiring the increment of the distortion coefficient of the rifle bolt by using a first-order Newton iteration method according to the homography matrix between the dome camera image and the rifle bolt image;
and acquiring the distortion coefficient of the gunlock according to the distortion coefficient of the dome camera and the increment of the distortion coefficient of the gunlock.
8. The method of claim 1, wherein the increment of the bolt face distortion coefficient is calculated by the following equation:
<mrow> <msub> <mi>&Delta;</mi> <mn>2</mn> </msub> <mo>=</mo> <mo>-</mo> <msup> <mrow> <mo>(</mo> <msubsup> <mi>J</mi> <mn>2</mn> <mi>T</mi> </msubsup> <msub> <mi>J</mi> <mn>2</mn> </msub> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <msubsup> <mi>J</mi> <mn>2</mn> <mi>T</mi> </msubsup> <msup> <mi>F</mi> <mo>&prime;</mo> </msup> <mrow> <mo>(</mo> <msubsup> <mi>P</mi> <mn>0</mn> <mo>&prime;</mo> </msubsup> <mo>)</mo> </mrow> </mrow>
wherein,
F′(P′0) The initial value of the homography function between the dome camera image and the gun camera image corresponding to the initial value of the preset gun camera distortion coefficient is obtained, and the homography function between the dome camera image and the gun camera image corresponds to the homography matrix of the homography function;
wherein, P' ═ (k)1′ k2′ k3′ p1′ p2'H'), P 'is the bolt distortion coefficient (k'1k′2k′3p′1p′2) And homography matrix (H ') between the dome image and the gun camera image, F (P') being between the dome image and the gun camera imageThe homography matrix of (a); f'1…F′rIs a homography function between the dome camera image and the gun camera image corresponding to the r homonymous points respectively.
9. An apparatus for real-time backcalculating distortion coefficients of a bolt face, comprising:
the image acquisition unit is used for acquiring a gun camera image by using a gun camera, and rotationally shooting by using a dome camera under the same focal length to acquire more than two dome camera images, wherein the shot contents of at least two adjacent dome camera images are overlapped, and the dome camera images are overlapped with the shot contents of the gun camera images;
the first feature point extracting and matching unit is used for respectively extracting feature points of the dome camera images and matching the feature points of every two adjacent dome camera images;
the first homography matrix establishing unit is used for establishing a homography matrix between two adjacent dome camera images according to the feature points matched with the two adjacent dome camera images, and the homography matrix comprises a dome camera distortion coefficient to be calculated;
the dome camera distortion coefficient calculation unit is used for calculating the dome camera distortion coefficient by utilizing the homography matrix between the two adjacent dome camera images;
the second characteristic point extracting and matching unit is used for respectively extracting the characteristic points of the dome camera image and the gunlock image and matching the characteristic points of the dome camera image and the gunlock image;
the second homography matrix establishing unit is used for establishing a homography matrix between the dome camera image and the gun camera image by utilizing the matched characteristic points between the dome camera image and the gun camera image, and the homography matrix comprises the distortion coefficient of the gun camera to be calculated;
and the gunlock distortion coefficient calculating unit is used for calculating the gunlock distortion coefficient by utilizing the dome camera distortion coefficient, the dome camera image and the homography matrix between the gunlock images.
10. The apparatus of claim 9, wherein the first homography matrix establishing unit comprises:
the first undistorted coordinate acquisition unit is used for respectively acquiring undistorted coordinates corresponding to the matched feature points between the two adjacent dome camera images, and the undistorted coordinates are a function of the distortion coefficient of the dome camera to be calculated;
and the first homography matrix acquisition unit is used for establishing a homography matrix between the two adjacent dome camera images according to the undistorted coordinates respectively corresponding to the characteristic points matched between the two adjacent dome camera images.
11. The apparatus of claim 10, wherein the first undistorted coordinate acquisition unit comprises:
the first calculation unit is used for calculating the coordinates and the radius of the characteristic points of the dome camera image relative to the main point of the dome camera;
the first acquisition unit acquires corresponding undistorted coordinates according to the coordinates and radius of the feature points of the dome camera image relative to the dome camera principal point, the coordinates of the dome camera principal point and the dome camera distortion coefficient to be calculated.
12. The apparatus according to claim 9, wherein the sphere machine distortion coefficient calculation unit includes:
the first initial value calculation unit is used for presetting an initial value of the distortion coefficient of the dome camera and correspondingly acquiring an initial value of a homography matrix between every two adjacent dome camera images;
the first increment calculating unit is used for acquiring the increment of the distortion coefficient of the dome camera by utilizing a first-order Newton iteration method according to the homography matrix between every two adjacent dome camera images;
and the dome camera distortion coefficient acquisition unit is used for acquiring the dome camera distortion coefficient according to the initial value of the dome camera distortion coefficient and the increment of the dome camera distortion coefficient.
13. The apparatus of claim 9, further comprising a conversion unit comprising:
the computing unit is used for acquiring distorted image coordinate sampling points of a plurality of dome camera images and computing corresponding non-distorted image coordinates according to the distortion coefficients of the dome cameras;
the equation establishing unit is used for respectively establishing corresponding equations of the distortion-free image coordinates, the forward distortion coefficient to be solved and the distorted coordinate sampling points;
and the forward distortion coefficient acquisition unit is used for solving the forward distortion coefficient.
14. The apparatus according to any one of claims 9-13, wherein the bolt distortion coefficient calculation unit comprises:
the second initial value calculation unit is used for presetting an initial value of the gunlock distortion coefficient and correspondingly acquiring an initial value of a homography matrix between the dome camera image and the gunlock image;
the second increment calculating unit is used for acquiring the increment of the distortion coefficient of the gunlock by utilizing a first-order Newton iteration method according to the homography matrix between the dome camera image and the gunlock image;
and the rifle bolt distortion coefficient acquisition unit is used for acquiring the rifle bolt distortion coefficient according to the distortion coefficient of the dome camera and the increment of the rifle bolt distortion coefficient.
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