CN114463432A - Parameter correction method for electronic anti-shake of gyroscope - Google Patents
Parameter correction method for electronic anti-shake of gyroscope Download PDFInfo
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Abstract
The invention discloses a parameter correction method for electronic anti-shake of a gyroscope, which has the technical scheme that the method is characterized in that a weight matrix K is obtained by combining the rotation angle and the translation amount of an X, Y, Z axis of a camera image sensor acquired by the gyroscope and calculating the rotation angle, the transverse translation amount and the longitudinal translation amount of a calibration chart, and the parameter correction of the electronic anti-shake of the gyroscope is completed; and obtaining an affine matrix P on the basis of the weight matrix K, and performing inverse affine transformation on the original image of the jittering video through the affine transformation matrix P to obtain an anti-jittering image. The correction method eliminates the influence of different camera internal parameters on the anti-shake effect, effectively improves the accuracy of the affine transformation matrix P, and improves the electronic anti-shake effect of the gyroscope; effectively reduce or even eliminate the video shake who patrols and examines the robot in darker space, provide help for video post-processing and personnel's watching.
Description
Technical Field
The invention belongs to the technical field of camera video anti-shake, and particularly relates to a parameter correction method for electronic anti-shake of a gyroscope.
Background
Camera video jitter is a common problem in video processing, and screen jitter affects the accuracy of camera image acquisition data and affects post-processing of data and viewing by related personnel. In order to effectively reduce and eliminate video jitter, the research of camera video anti-jitter technology is applied to different fields of image processing, such as robot inspection, camera shooting, projection and the like.
The camera video anti-shake mainly comprises mechanical anti-shake and electronic anti-shake, wherein the mechanical anti-shake has high requirements on an external mechanical structure and a driving unit, and the advantage of being difficult to play in high-frequency micro-shake is achieved. Electronic anti-shake is classified into an image processing method that removes "shake" that is subjectively perceived from the viewpoint of each frame image of video, but is difficult to apply in dark light or when a video-taking subject has motion properties, and a gyro detection correction method.
The gyroscope detection and correction method is a video anti-shake method integrating the advantages of mechanical anti-shake and electronic anti-shake. The electronic anti-shake of the gyroscope utilizes the shake data of the gyroscope to compensate the movement and rotation of a video picture, and the compensation weight is the most important parameter for the good and bad anti-shake effect of the picture under the condition that the detection precision of the gyroscope is enough. The current method for determining the mainstream compensation weight parameters is a parameter calculation method and a trial and error method. The weight parameter calculation method is determined according to camera internal parameters such as lens focal length, camera image sensor size, object distance and the like; another trial and error method is to artificially try and finally select a suitable weighting parameter according to the subjective jitter condition of the picture.
The weight parameter calculation method is determined according to camera internal parameters, such as a lens focal length, a camera image sensor size, an object distance and the like, and the greatest defect is that the camera internal parameters are acquired, but in many cases, the camera internal parameters cannot be acquired, and the anti-shake effect is influenced by slight deviation of the internal parameters. Another trial and error method is to artificially try and finally select a proper weight parameter according to the subjective jitter condition of the picture, and the disadvantage is that the anti-jitter effect depends on subjective feeling of personnel, and the trial and error method cannot obtain good effect in the face of small-amplitude high-frequency jitter. The invention adopts the weight parameter optimization starting from the picture angle, obtains the shaking condition of the video shot by the camera by a machine vision method, can minimize the shaking of the picture and does not depend on the acquisition of camera internal parameters.
Disclosure of Invention
The present invention is directed to a method for correcting electronic anti-shake parameters of a gyroscope, so as to solve the problems mentioned in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
the parameter correction method comprises the following steps: collecting the rotation angle and the translation amount of an X, Y, Z shaft of the sensor; calibrating the circle center coordinates and the horizontal line in the calibration chart; calculating to obtain the rotation angle, the transverse translation amount and the longitudinal translation amount of the calibration graph; and combining the rotation angle, the transverse translation amount, the longitudinal translation amount and the gyroscope data of the calibration chart to obtain a weight matrix K, and completing parameter correction.
Preferably, the parameter correction method detects the X, Y, Z axis rotation angle and translation amount of the camera image sensor through a gyroscope, and detects the calibration chart rotation and translation through a computer vision method.
Preferably, the gyroscope is installed in parallel with the camera image sensor, and the gyroscope is collinear with the central axis of the camera image sensor, so that coupling between the gyroscope and all-direction attitude information when the camera shakes greatly is reduced.
Preferably, the parameter correction method uses a computer vision closed figure detection method to calibrate two circle center coordinates in the calibration graph.
Preferably, the parameter correction method calculates an included angle between a connecting line of two circle centers and a horizontal line to obtain a rotation angle α of the calibration chartimgThe rotation angle of the calibration chart corresponds to the Z-axis rotation angle alpha of the camera image sensorsen。
Preferably, the parameter correction method calculates coordinates of a midpoint of a connecting line of two circle centers to obtain a transverse translation amount x of the calibration graphimgThe transverse translation amount of the calibration chart corresponds to the Y-axis rotation angle beta of the camera image sensorsenAnd X-axis translation Xsen。
Preferably, the parameter correction method calculates coordinates of a midpoint of a connecting line of two circle centers to obtain a longitudinal translation amount y of the calibration graphimgThe longitudinal translation amount of the calibration chart corresponds to the X-axis rotation angle delta of the camera image sensorsenAnd the amount of Y-axis translation Ysen。
Preferably, the parameter correction method combines the transformation information a of the three imagesimg、ximg、yimgAnd five types of gyroscope data alphasen、βsen、xsen、δsen、ysenObtaining a weight matrix K, wherein the weight matrix is as follows:
αimg＝K1αsen
wherein K1、K2、K3、K4、K5The parameters are respectively obtained by independent Z-axis rotation, Y-axis rotation, X translation, X-axis rotation and Y-axis translation calculation of the camera image sensor.
Preferably, the parameter correction method obtains an affine matrix P on the basis of the weight matrix K, and the affine transformation matrix P performs inverse affine transformation on the original image of the jittered video to obtain the anti-jittering image, where the affine matrix P is as follows:
preferably, the weight matrix K is used for parameter correction of electronic anti-shake of the gyroscope. The parameter correction method eliminates the influence of different camera internal parameters on the anti-shake effect, can effectively improve the accuracy of the affine transformation matrix P, and improves the electronic anti-shake effect of the gyroscope.
The invention has the technical effects and advantages that: the parameter correction method for electronic anti-shake of the gyroscope adopts weight parameter optimization starting from a picture angle, obtains the shake condition of the video shot by the camera through a machine vision method, can minimize the shake of the picture, does not depend on the acquisition of camera internal parameters, eliminates the influence of different camera internal parameters on the anti-shake effect, can effectively improve the accuracy of an affine transformation matrix P, improves the electronic anti-shake effect of the gyroscope, effectively reduces or even eliminates the video shake of an inspection robot in a dark space, and provides help for the post-processing of the video and the watching of personnel.
Drawings
FIG. 1 is a flow chart of a parameter calibration method for electronic anti-shake of a gyroscope according to the present invention;
FIG. 2 is a schematic view of a gyroscope and camera image sensor of the present invention in parallel;
FIG. 3 is a schematic structural diagram of a black background of the present invention comprising two white closed circles;
FIG. 4 is a schematic structural diagram of the center point coordinate of the connection line of the centers of two circles and the rotation angle of the connection line.
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.
The invention provides a parameter correction method for electronic anti-shake of a gyroscope, which comprises the following steps: collecting the rotation angle and the translation amount of an X, Y, Z shaft of the sensor; calibrating the circle center coordinates and the horizontal line in the calibration chart; calculating to obtain the rotation angle, the transverse translation amount and the longitudinal translation amount of the calibration graph; and combining the rotation angle, the transverse translation amount, the longitudinal translation amount and the gyroscope data of the calibration chart to obtain a weight matrix K, and completing parameter correction.
The parameter correction method detects the X, Y, Z axis rotation angle and translation amount of the camera image sensor through a gyroscope, and detects the calibration chart rotation and translation through a computer vision method.
The electronic anti-shake of the gyroscope utilizes the shake data of the gyroscope to compensate the movement and rotation of the video picture, and the compensation weight in the shake data of the gyroscope is the most important parameter with good and bad anti-shake effect of the picture under the condition of enough detection precision of the gyroscope. The parameter correction method for electronic anti-shake of the gyroscope adopts weight parameter optimization starting from a picture angle, obtains the shake condition of a video shot by a camera through a machine vision method, can minimize the shake of the picture, and does not depend on the acquisition of camera internal parameters.
The gyroscope and the camera image sensor are installed in parallel, and the central axes of the gyroscope and the camera image sensor are collinear and are as close as possible to reduce the coupling between the gyroscope and the attitude information in all directions when the camera shakes greatly. The camera image Sensor is a camera Sensor. The camera image sensor is aligned to the exact center of the captured calibration image to ensure that the camera X, Y axis motion calculated from the video is not coupled to the Z axis rotation.
The parameter correction method uses a closed graph detection method of computer vision to calibrate two circle center coordinates in a calibration graph.
The parameter correction method calculates the included angle between the connecting line of the two circle centers and the horizontal line to obtain the rotation angle alpha of the calibration chartimgThe rotation angle of the calibration chart corresponds to the Z-axis rotation angle alpha of the camera image sensorsen。
The parameter correction method calculates the coordinates of the middle point of the connecting line of the two circle centers to obtain the transverse translation amount x of the calibration chartimgThe amount of lateral translation x of the calibration mapimgCorresponding to the Y-axis rotation angle beta of the camera image sensorsenAnd X-axis translation XsenRotation angle β of Y-axis of said SensorsenAnd X-axis translation XsenAmount of lateral translation x affecting calibration mapimg。
The parameter correction method calculates the coordinates of the middle point of the connecting line of the two circle centers to obtain the longitudinal translation amount y of the calibration chartimgThe longitudinal translation amount y of the calibration chartimgCorresponding to the X-axis rotation angle delta of the camera image sensorsenAnd the amount of Y-axis translation YsenThe X-axis of the Sensor is rotated by an angle deltasenAnd the amount of Y-axis translation YsenLongitudinal translation y affecting calibration mapimg。
The parameter correction method combines the transformation information of the three images and the five types of gyroscope data to calculate a correction weight matrix K. The five gyroscope data are Z-axis rotation angles alpha of the camera image sensorsenY-axis rotation angle betasenAngle of rotation of X axis deltasenX-axis translation XsenY-axis translation YsenThe three kinds of image change information are respectively the rotation angle alpha of the calibration graphimgTransverse to the calibration chartTranslation amount ximgLongitudinal translation y of calibration chartimgThe rotation angle of the calibration graph is the rotation angle alpha of the midpoint coordinate and the connecting lineimgThe transverse translation amount of the calibration chart is the transverse translation amount x of the midpoint coordinate of the connecting lineimgThe longitudinal translation amount of the calibration chart is the longitudinal translation amount y of the midpoint coordinate of the connecting lineimgThe three kinds of image change information are camera postures, and the relationship between the camera postures and the picture jitter is as follows:
αimg＝K1αsen
wherein K1、K2、K3、K4、K5The parameters are respectively obtained by independent Z-axis rotation, Y-axis rotation, X translation, X-axis rotation and Y-axis translation calculation of the camera image sensor.
Under the condition of obtaining the rotation angle of the axis of the gyroscope X, Y, Z and the translation amount of the axis X, Y, the parameter correction method combines the initial weight matrix K to obtain an affine transformation matrix P, and the affine transformation matrix P performs inverse affine transformation on the original image of the jittered video to obtain an anti-jittering image. The affine matrix P is as follows:
and the weight matrix K is used for correcting the parameters of the electronic anti-shake of the gyroscope.
The parameter correction method eliminates the influence of different camera internal parameters on the anti-shake effect, can effectively improve the accuracy of the affine transformation matrix P, and improves the electronic anti-shake effect of the gyroscope.
Further, the calibration chart is a large-area blackboard with two white circles.
Further, the updating of the weight matrix K through the calibration graph is an off-line process for calibrating parameters, and does not participate in the real-time operation of the anti-shake process.
Further, the affine transformation matrix P includes translation and rotation information of image transformation, and does not include deformation and scaling information.
Example 1
The invention provides a parameter correction method for electronic anti-shake of a gyroscope, which combines the rotation angle and translation amount of an X, Y, Z axis of a camera image sensor acquired by the gyroscope and the rotation angle, transverse translation amount and longitudinal translation amount of a calibration chart obtained by calculation to obtain a weight matrix K so as to finish the parameter correction of the electronic anti-shake of the gyroscope; an affine matrix P is obtained on the basis of the weight matrix K, and an anti-shake image is obtained by performing inverse affine transformation on the original image of the shake video through the affine transformation matrix P, as shown in fig. 1. In the process of acquiring the sensor data, the gyroscope and the camera image sensor are installed in parallel, the central axes of the gyroscope and the camera image sensor are collinear, and the gyroscope and the camera image sensor are as close as possible to ensure that all attitude information is not coupled, as shown in fig. 2. And in the process of acquiring the sensor data, the camera is aligned to the right center of the calibration chart, and the image is ensured to completely cover all the visual fields shot by the camera.
The calibration graph in the calibration process is two horizontally placed closed graphs with a certain distance under a pure color background, wherein the background color and the two closed graphs have larger brightness difference. The black background contains two white closed circles as shown in fig. 3.
In the calculation process, the calibration graph is fixed, the camera simulates a shaking environment to shoot the calibration graph, and each frame of the shot video is subjected to image processing. In the calculation process, a circle detection method, such as a Hough circle detection method, is used for identifying the coordinates of the centers of two circles in the graph and calibrating a connecting line and the midpoint of the connecting line; calibrating horizontal lines of the calibration graph; calculating to obtain the midpoint coordinate of the connecting line and the rotation angle alpha of the connecting lineimgAs shown in fig. 4. The calibration mapThe rotation angle corresponds to the Z-axis rotation angle alpha of the camera image sensorsenTransverse translation x of the coordinates of the middle points of the connecting linesimgThe transverse translation amount of the calibration chart corresponds to the Y-axis rotation angle beta of a camera image Sensor (Sensor)senAnd X-axis translation XsenLongitudinal translation y of midpoint coordinates of the linkimgThe longitudinal translation amount of the calibration chart corresponds to the X-axis rotation angle delta of the Sensor of the camera image SensorsenAnd the amount of Y-axis translation Ysen。
In the process of shooting a calibration chart by a camera and simulating jitter, the gyroscope records data alpha of five poses in real timesen、βsen、xsen、δsen、ysenAnd the three image posture information alphaimg、ximg、yimgCorrespondingly, the proportion value of each corresponding posture forms a weight matrix K, and the relationship between the image posture and the picture jitter is as follows:
αimg＝K1αsen
in the above relations, each relation contains two unknown coefficients (K) for the transverse translation and longitudinal translation processes of the calibration graph1，K2)(K3，K4) Each coefficient can be obtained by controlling an independent variable. Controlling the camera image sensor to rotate only about the Z axis, recording alphasenAnd alphaimgCalculating to obtain a parameter K1(ii) a Controlling the camera image sensor to rotate only about the Y-axis and recording betasenAnd ximgCalculating to obtain a parameter K2(ii) a Controlling the camera image sensor to only translate along the X axis and recording XsenAnd ximgCalculating to obtain a parameter K3(ii) a Controlling the camera image sensor to rotate only about the X-axisRecording deltasenAnd yimgCalculating to obtain a parameter K4(ii) a Controlling the camera image sensor to only translate along the Y axis and recording YsenAnd yimgCalculating to obtain a parameter K5. And establishing a whole coefficient K matrix to obtain the corresponding relation between the gyroscope data and the image attitude information. The coefficient matrix K derived from above is valid for both the camera at this focal length and the object distance condition in this calibration environment.
In the real-time anti-shake application process of the camera, five pose data alpha of the gyroscope in each framesen、βsen、xsen、δsen、ysenCalculating image attitude information by combining the matrix K, and synthesizing an affine matrix P of the image, wherein the affine matrix P is as follows:
the affine matrix P represents the pose relationship of the target image after the offset of the camera and the original image, and the original image can be obtained by carrying out inverse affine transformation on the offset image. And establishing an affine matrix P for each frame of the video and carrying out inverse affine transformation processing to obtain the video without jitter.
The working principle is as follows: the electronic anti-shake parameter correction method of the gyroscope utilizes a camera to shoot a calibration chart and simulate the shake process, the gyroscope records data of five poses in real time and corresponds to three image pose information, and the data of the five poses is the Z-axis rotation angle alpha of a camera image SensorsenY-axis rotation angle betasenAngle of rotation of X axis deltasenX-axis translation XsenY-axis translation YsenThe proportional values corresponding to the three image poses form a weight matrix K, and the three image poses are the rotation angles alpha of the calibration graphimgThe transverse translation amount x of the calibration chartimgAnd the longitudinal translation y of the calibration mapimgThe rotation angle of the calibration graph is the rotation angle alpha of the midpoint coordinate and the connecting lineimgThe calibration map is rotated by an angle alphaimgCorresponding camera image sensor Sensor Z-axis rotation angle alphasenThe transverse translation amount of the calibration chart is the transverse translation amount x of the midpoint coordinate of the connecting lineimgThe amount of lateral translation x of the calibration mapimgCorresponding to the Y-axis rotation angle beta of the Sensor of the camera imagesenAnd X-axis translation XsenThe longitudinal translation amount of the calibration chart is the longitudinal translation amount y of the midpoint coordinate of the connecting lineimgThe longitudinal translation amount y of the calibration chartimgCorresponding to the rotation angle delta of the X axis of the Sensor of the camera image SensorsenAnd the amount of Y-axis translation YsenAnd the weight matrix K is combined with each frame of gyroscope data to establish an affine matrix P, and the affine matrix P performs inverse affine transformation on the current frame to obtain a final anti-shake image.
The weight matrix K is as follows:
αimg＝K1αsen
the affine matrix P is as follows:
finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (11)
1. A parameter correction method for electronic anti-shake of a gyroscope is characterized by comprising the following steps: the parameter correction method comprises the following steps:
collecting the rotation angle and the translation amount of an X, Y, Z shaft of the sensor;
calibrating the circle center coordinates and the horizontal line in the calibration chart;
calculating to obtain the rotation angle, the transverse translation amount and the longitudinal translation amount of the calibration graph;
and combining the rotation angle, the transverse translation amount, the longitudinal translation amount and the gyroscope data of the calibration chart to obtain a weight matrix K, and completing parameter correction.
2. The parameter correction method for electronic anti-shake of gyroscope according to claim 1, characterized in that: the parameter correction method detects the X, Y, Z axis rotation angle and translation amount of the camera image sensor through a gyroscope, and detects the calibration chart rotation and translation through a computer vision method.
3. The parameter correction method for electronic anti-shake of gyroscope according to claim 2, characterized in that: the gyroscope is mounted in parallel with the camera image sensor, and the gyroscope is collinear with a central axis of the camera image sensor.
4. The parameter correction method for electronic anti-shake of gyroscope according to claim 2, characterized in that: the parameter correction method uses a closed graph detection method of computer vision to calibrate two circle center coordinates in a calibration graph.
5. The parameter correction method for electronic anti-shake of gyroscope according to claim 2, characterized in that: the parameter correction method calculates the included angle between the connecting line of the two circle centers and the horizontal line to obtain the rotation angle alpha of the calibration chartimgThe rotation angle of the calibration chart corresponds to the Z-axis rotation angle alpha of the camera image sensorsen。
6. According to claimThe method for correcting parameters for electronic anti-shake of a gyroscope according to claim 2, characterized by: the parameter correction method calculates the coordinates of the middle point of the connecting line of the two circle centers to obtain the transverse translation amount x of the calibration chartimgThe transverse translation amount of the calibration chart corresponds to the Y-axis rotation angle beta of the camera image sensorsenAnd X-axis translation Xsen。
7. The parameter correction method for electronic anti-shake of gyroscope according to claim 2, characterized in that: the parameter correction method calculates the coordinates of the middle point of the connecting line of the two circle centers to obtain the longitudinal translation amount y of the calibration chartimgThe longitudinal translation amount of the calibration chart corresponds to the X-axis rotation angle delta of the camera image sensorsenAnd the amount of Y-axis translation Ysen。
8. Parameter correction method for electronic anti-shake of gyroscopes according to claims 2 to 7, characterised in that: the parameter correction method combines the transformation information alpha of the three imagesimg、ximg、yimgAnd five types of gyroscope data alphasen、βsen、xsen、δsen、ysenObtaining a weight matrix K, wherein the weight matrix K is as follows:
αimg＝K1αsen
wherein K1、K2、K3、K4、K5The parameters are respectively obtained by independent Z-axis rotation, Y-axis rotation, X translation, X-axis rotation and Y-axis translation calculation of the camera image sensor.
9. The parameter correction method for electronic anti-shake of gyroscope according to claim 8, characterized in that: the parameter correction method obtains an affine matrix P on the basis of the weight matrix K, the affine transformation matrix P performs inverse affine transformation on the original image of the jittering video to obtain an anti-jittering image, and the affine matrix P is as follows:
10. the parameter correction method for electronic anti-shake of gyroscope according to claim 8, characterized in that: and the weight matrix K is used for correcting the parameters of the electronic anti-shake of the gyroscope.
11. The parameter correction method for electronic anti-shake of gyroscope according to any of claims 1-8, characterized in that: the parameter correction method eliminates the influence of different camera internal parameters on the anti-shake effect.
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