CN114650402B - Method, system, device and medium for calculating and adjusting adjustment curve of projection image - Google Patents

Method, system, device and medium for calculating and adjusting adjustment curve of projection image Download PDF

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CN114650402B
CN114650402B CN202011516248.5A CN202011516248A CN114650402B CN 114650402 B CN114650402 B CN 114650402B CN 202011516248 A CN202011516248 A CN 202011516248A CN 114650402 B CN114650402 B CN 114650402B
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projection image
point
calculating
points
adjustment curve
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CN114650402A (en
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徐金虎
王鑫
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Chengdu Jimi Technology Co Ltd
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Chengdu Jimi Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H04N9/3185—Geometric adjustment, e.g. keystone or convergence
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03B—APPARATUS OR ARRANGEMENTS FOR TAKING PHOTOGRAPHS OR FOR PROJECTING OR VIEWING THEM; APPARATUS OR ARRANGEMENTS EMPLOYING ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ACCESSORIES THEREFOR
    • G03B21/00—Projectors or projection-type viewers; Accessories therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]

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Abstract

The invention is suitable for the technical field of projection, and provides a method, a system, a device and a medium for calculating and adjusting an adjustment curve of a projection image, wherein the method comprises the following steps: computing featuresPoint(s)
Figure DDA0002847482650000011
Corresponding collection of data sets at n-level
Figure DDA0002847482650000012
Wherein m is G i The sequence number of the point in m E [1, n ]]The method comprises the steps of carrying out a first treatment on the surface of the With the characteristic points
Figure DDA0002847482650000013
Set G of data sets at n-level i As a set of control points
Figure DDA0002847482650000014
Calculating feature points
Figure DDA0002847482650000015
The corresponding adjustment curve, when j=0,
Figure DDA0002847482650000016
when j is not equal to 0, let m=j,
Figure DDA0002847482650000017
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure DDA0002847482650000018
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a coordinate point set of all feature points in a feature map in a projection image coordinate system A is adopted, the feature map is included in a projection image, the feature map is provided with feature points, n is a scale multiple, and a shooting image is obtained by shooting the projection image. The invention can correct the distortion of the projection image and change the size of the projection image, and simultaneously, the whole adjustment process of the projection image is very smooth, thereby being capable of giving better use experience to users.

Description

Method, system, device and medium for calculating and adjusting adjustment curve of projection image
Technical Field
The invention belongs to the technical field of projection, and particularly relates to a method, a system, a device and a medium for calculating and adjusting an adjustment curve of a projection image.
Background
In the prior art, when the projected image is subjected to trapezoidal correction, the method at least comprises three steps: the method comprises the steps of firstly, determining an initial position of a projection image; secondly, determining the position to be adjusted of the projection image; and thirdly, adjusting the projection image from the initial position to the position to be adjusted.
Although the prior art has been able to solve the technical problem of trapezoidal correction, in the process of adjusting the projection image from the initial position to the position to be adjusted, there are also the following technical problems:
on the one hand, the size of the projection image after adjustment is almost the same as the size of the projection image before adjustment, that is, the problem of trapezoidal correction is only solved in the prior art, and the projection image is not provided with a proper size; the size adjustment of the projected image in the prior art is adjusted separately after the trapezoidal correction, or the size adjustment of the projected image is adjusted separately before the trapezoidal correction; thus, the prior art adjustments are less efficient;
on the other hand, in the prior art, the trapezoidal correction is often carried out in one step in the process of adjusting the projection image from the initial position to the position to be adjusted, so that the whole adjustment process gives people a very unsmooth feel, and the use experience is influenced.
Therefore, how to provide a solution to the technical problems is a problem that a person skilled in the art needs to solve at present
Disclosure of Invention
The invention aims to provide a method, a system, a device and a medium for calculating and adjusting an adjustment curve of a projection image, and aims to solve the technical problems of low adjustment efficiency and poor adjustment impression of the projection image in the prior art.
In order to achieve the above objective, the technical solution provided in the embodiments of the present application is as follows:
in a first aspect, an embodiment of the present application provides a method for calculating an adjustment curve of a projection image, including the steps of:
calculating feature points
Figure BDA0002847482630000021
Corresponding set of data sets at n-level +.>
Figure BDA0002847482630000022
Wherein m is G i The sequence number of the point in m E [1, n ]]；
With the characteristic points
Figure BDA0002847482630000023
Set G of data sets at n-level i As a set of control points
Figure BDA0002847482630000024
Calculate feature points->
Figure BDA0002847482630000025
Corresponding adjustment curves, when j=0, < > is given>
Figure BDA0002847482630000026
Let m=j +.0 when j+.0 +.>
Figure BDA0002847482630000027
wherein ,
Figure BDA0002847482630000028
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a feature map is included in a projection image, wherein the feature map is a coordinate point set of all feature points in the feature map in a projection image coordinate system A, the feature map is provided with feature points, n is a scale multiple between the projection image coordinate system A and a shooting image coordinate system B, and the shooting image is an image obtained by shooting the projection image.
Optionally, in the method for calculating the adjustment curve of the projection image, a calculation formula of the scale multiple n is as follows:
Figure BDA0002847482630000029
wherein, centroid A 、centroid B Respectively coordinate point sets P A Coordinate point set P B Centroid of (2)Coordinate point set P B The average is an average function of a coordinate point set of all feature points in the feature map in a shooting image coordinate system B.
Optionally, in the method for calculating an adjustment curve of a projection image, m=1 to n are substituted into each of the two values
Figure BDA00028474826300000210
Get the spot->
Figure BDA00028474826300000211
From the point->
Figure BDA00028474826300000212
Common constituent feature Point->
Figure BDA00028474826300000213
Corresponding set G of data sets at n-level i R is a rotation matrix between the projection image coordinate system a and the photographed image coordinate system B.
Optionally, in the above method for calculating an adjustment curve of a projection image,
Figure BDA0002847482630000031
Figure BDA0002847482630000032
wherein N is the number of feature points, +.>
Figure BDA0002847482630000033
For the set of coordinate points P B Is the i-th point in (a).
Optionally, in the method for calculating the adjustment curve of the projection image, the rotation matrix R is calculated by a singular value decomposition method.
Optionally, in the method for calculating an adjustment curve of a projection image, calculating the rotation matrix R includes the following steps:
constructing a covariance matrix H;
let h=usv T Calculating U and V, wherein U and V are positive unit fixed matrixes, and S is a diagonal matrix；
Let r=vu T Obtaining a rotation matrix R.
Optionally, in the method for calculating an adjustment curve of a projection image, the covariance matrix H is:
Figure BDA0002847482630000034
optionally, in the method for calculating an adjustment curve of a projection image, the feature points
Figure BDA0002847482630000035
The corresponding adjustment curve is B (t) i, wherein
Figure BDA0002847482630000036
j is the control point number, ">
Figure BDA0002847482630000037
For K i The j+1th control point in the table, t is a curve adjustment parameter, t is E [0,1 ]]。
In a second aspect, an embodiment of the present application provides an adjustment curve computing system for a projection image, including:
a set calculation module of the n-level data set: for calculating characteristic points
Figure BDA0002847482630000038
Corresponding set of data sets at n-level +.>
Figure BDA0002847482630000039
Wherein m is G i The sequence number of the point in m E [1, n ]]；
An adjustment curve calculation module: with the characteristic points
Figure BDA00028474826300000310
Set G of data sets at n-level i As a set of control points
Figure BDA00028474826300000311
Calculate feature points->
Figure BDA00028474826300000312
Corresponding adjustment curves, when j=0, < > is given>
Figure BDA00028474826300000313
Let m=j +.0 when j+.0 +.>
Figure BDA00028474826300000314
wherein ,
Figure BDA00028474826300000315
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a feature map is included in a projection image, wherein the feature map is a coordinate point set of all feature points in the feature map in a projection image coordinate system A, the feature map is provided with feature points, n is a scale multiple between the projection image coordinate system A and a shooting image coordinate system B, and the shooting image is an image obtained by shooting the projection image.
Optionally, in the above adjustment curve computing system for a projection image, the adjustment curve computing system further includes a scale factor computing module, configured to compute a scale factor n:
Figure BDA0002847482630000041
wherein, centroid A 、centroid B Respectively coordinate point sets P A Coordinate point set P B Centroid of (2), set of coordinate points P B The average is an average function of a coordinate point set of all feature points in the feature map in a shooting image coordinate system B.
Alternatively, in the above-mentioned projected image adjustment curve calculation system, m=1 to n are substituted respectively
Figure BDA0002847482630000042
Get the spot->
Figure BDA0002847482630000043
From the point->
Figure BDA0002847482630000044
Common constituent feature Point->
Figure BDA0002847482630000045
Corresponding set G of data sets at n-level i R is a rotation matrix between the projection image coordinate system a and the photographed image coordinate system B.
Optionally, in the above adjustment curve computing system for projection image, the adjustment curve computing system further includes a centroid computing module for computing centroid A 、centroid B ：
Figure BDA0002847482630000046
Wherein N is the number of feature points, +.>
Figure BDA0002847482630000047
For the set of coordinate points P B Is the i-th point in (a).
Optionally, in the above system for calculating an adjustment curve of a projection image, the rotation matrix R is calculated by a singular value decomposition method.
Optionally, in the above adjustment curve computing system for projection images, the adjustment curve computing system further includes a singular value decomposition computing module, configured to compute the rotation matrix R:
constructing a covariance matrix H;
let h=usv T Calculating U and V, wherein U and V are unit positive definite matrixes, and S is a diagonal matrix;
let r=vu T Obtaining a rotation matrix R.
Optionally, in the above adjustment curve computing system for projection images, the covariance matrix H is:
Figure BDA0002847482630000048
optionally, in the above system for calculating an adjustment curve of a projection image, the feature points
Figure BDA0002847482630000051
The corresponding adjustment curve is Betz curve B (t) i Said->
Figure BDA0002847482630000052
Wherein j is the control point number, +.>
Figure BDA0002847482630000053
For K i The j+1th control point in the table, t is the Betz curve adjustment parameter, t E [0,1 ]]。
In a third aspect, an embodiment of the present application provides a method for adjusting a projection image, including the steps of: and adjusting the projection image by taking each characteristic point as a track according to a corresponding adjusting curve, wherein the adjusting curve is calculated by the method or the adjusting curve is calculated by the system.
In a fourth aspect, embodiments of the present application provide a projection apparatus, including a memory and a processor, where the memory stores program instructions that, when executed by the processor, perform the steps of the method as described above.
In a fifth aspect, embodiments of the present application provide a storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of the method as described above.
Compared with the prior art, the invention has the technical effects that:
according to the method, the system, the device and the medium for calculating and adjusting the adjustment curve of the projection image, the adjustment curve corresponding to each characteristic point is required to be calculated, after the adjustment curves corresponding to all the characteristic points are calculated, each characteristic point on the projection image moves according to the corresponding adjustment curve as a track, namely the adjustment of the projection image is completed, the rotation matrix between the coordinate system of the projection image and the coordinate system of the shooting image is considered in the calculation of the adjustment curve, so that the azimuth relation between the projection image and the shooting image is considered, and the scale multiple between the coordinate system of the projection image and the coordinate system of the shooting image is considered, so that the size relation between the projection image and the shooting image is also considered, the distortion of the projection image can be corrected, the size of the projection image can be changed, and meanwhile, the whole adjustment process of the projection image is very smooth, and a user can have better use experience.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly explain the embodiments of the present invention or the drawings used in the description of the prior art, and it is obvious that the drawings described below are only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic illustration of a projected image having distortion;
FIG. 2 is a schematic illustration of a prior art adjustment;
FIG. 3 is a schematic illustration of an adjusted projection image of the prior art;
FIG. 4 is a schematic diagram of one embodiment of the present invention in which the orientation and size of the projected image are simultaneously adjusted;
fig. 5 is a flowchart of a method for calculating an adjustment curve of a projection image according to the present embodiment;
fig. 6 is a relationship diagram of a projection image, a feature map, and a photographed image in the present embodiment;
fig. 7 is a graph showing the relationship between an adjustment curve and a control point in the present embodiment.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Fig. 1 is a schematic diagram showing distortion of a projection image, wherein a projection assembly 11 is arranged on a projection device 10, a projection image 22 is projected by the projection assembly 11, and the projection image 22 in fig. 1 has distortion, that is, the projection image 22 has deviation from an expected azimuth; the projection device 10 is also provided with the photographing assembly 12, the photographing assembly 12 can photograph the area where the projection image 22 is located to obtain a photographed image 21, and generally, the photographed image 21 has a regular azimuth, so that the projection image 22 can be adjusted by taking the photographed image 21 as a reference, and when the azimuth of the projection image 22 is adjusted to be the same as the azimuth of the photographed image 21, the distortion problem of the projection image 22 is solved;
the camera assembly 12 may be a conventional camera, ultra-wide angle camera, etc., and is user-customizable. Embodiments of the present invention correct for distortion of a projected image of a projection device, including but not limited to a short-focus projector, which may be a laser television, or a tele projector.
As shown in fig. 2, which is a schematic diagram of adjustment in the prior art, the dashed line represents the projection image after adjustment, the solid line represents the projection image before adjustment, taking the point 1 on the projection image as an example, after adjustment, the point 1 is directly displayed at the position of the point 1', and the whole adjustment process gives a sense of being abrupt to the user;
as shown in fig. 3, which is a schematic diagram of the adjusted projection image, the orientation of the projection image 22 is the same as the orientation of the photographed image 21; as can be seen from fig. 3, simply correcting the distortion of the projected image does not change the size of the projected image 22, but it is desirable that the projected image 22 be as large as possible during use;
fig. 4 is a schematic view showing that the orientation and the size of the projection image are adjusted at the same time, the projection image 22 and the photographed image 21 are overlapped, that is, it is desirable that the projection image 22 be adjusted so as to solve the distortion of the projection image 22 and to enable the projection image 22 to have a proper size;
it should be noted that, in fig. 3, there is a certain gap between the projection image 22 and the captured image 21, only to better express the projection image 22 and the captured image 21, and in actual use, the projection image 22 and the captured image 21 may not have the gap therebetween.
The present embodiment firstly provides a method for calculating an adjustment curve of a projection image, and after the projection image is adjusted according to the adjustment curve calculated in the present embodiment, the projection image can reach an optimal size while realizing trapezoidal correction.
Fig. 5 is a flowchart of a method for calculating an adjustment curve of a projection image according to the present embodiment, which specifically includes:
s10: calculating feature points
Figure BDA0002847482630000073
Corresponding set of data sets at n-level +.>
Figure BDA0002847482630000071
Wherein m is G i The sequence number of the point in m E [1, n ]]；
wherein ,
Figure BDA0002847482630000072
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a feature map is included in a projection image, wherein the feature map is a coordinate point set of all feature points in the feature map in a projection image coordinate system A, the feature map is provided with feature points, n is a scale multiple between the projection image coordinate system A and a shooting image coordinate system B, and the shooting image is an image obtained by shooting the projection image.
As shown in fig. 6, the projection image 22 includes a feature map 23, the feature map 23 in fig. 6 is formed of a plurality of straight lines, the intersections between the straight lines form feature points, the projection image has a projection image coordinate system a in which all the feature points form a coordinate point set P A ，
Figure BDA0002847482630000081
For the set of coordinate points P A Is the i-th point in (a). The photographed image 21 has a photographed image seatThe standard system B, all the characteristic points form a coordinate point set P in the shooting image coordinate system B B ，
Figure BDA0002847482630000082
For the set of coordinate points P B Is the i-th point in (a).
Taking the example of figure 7 as an example,
Figure BDA0002847482630000083
the corresponding data set at n-level comprises three points +.>
Figure BDA0002847482630000084
S20: with the characteristic points
Figure BDA0002847482630000085
Set G of data sets at n-level i As a set of control points
Figure BDA0002847482630000086
Calculate feature points->
Figure BDA0002847482630000087
Corresponding adjustment curves, when j=0, < > is given>
Figure BDA0002847482630000088
Let m=j +.0 when j+.0 +.>
Figure BDA0002847482630000089
Taking the example of figure 7 as an example,
Figure BDA00028474826300000810
together form a control point set K i Specifically, the->
Figure BDA00028474826300000811
Figure BDA00028474826300000812
By->
Figure BDA00028474826300000813
(i.e.)>
Figure BDA00028474826300000814
) Together, the adjustment curves are determined, it being noted that the adjustment curves in fig. 7 only pass the point +.>
Figure BDA00028474826300000815
Point->
Figure BDA00028474826300000816
Without passing through the spot->
Figure BDA00028474826300000817
Point->
Figure BDA00028474826300000818
However, the control point set K is passed i The calculation method of the adjustment curves of all the control points in the method is also within the protection scope of the invention, and the embodiment of the invention focuses on the characteristic points +.>
Figure BDA00028474826300000819
Set G of data sets at n-level i To jointly determine the adjustment curve.
The feature map may be a two-dimensional code, a checkerboard, a rectangle or other graphics, and may be set by a user in a user-defined manner. According to the feature map, feature points in the feature map can be accurately obtained, the phenomenon that the feature points are extracted incorrectly due to unobvious features is avoided, and the adjustment accuracy is improved.
In the embodiment of the invention, the adjustment curve corresponding to each characteristic point needs to be calculated, after the adjustment curves corresponding to all the characteristic points are calculated, each characteristic point on the projection image moves according to the corresponding adjustment curve as a track to finish the adjustment of the projection image.
Regarding the scale factor n between the projection image coordinate system a and the photographed image coordinate system B, the calculation formula is as follows:
Figure BDA0002847482630000091
wherein, centroid A 、centroid B Respectively coordinate point sets P A Coordinate point set P B R is the rotation matrix between the projected image coordinate system a and the captured image coordinate system B, and average is the average function.
The scale factor n represents the dimensional relationship between the projection image and the captured image B.
Further, regarding the feature points
Figure BDA0002847482630000092
Corresponding set G of data sets at n-level i The calculation method of (2) is as follows:
substituting m=1 to n into each of
Figure BDA0002847482630000093
Get the spot->
Figure BDA0002847482630000094
From the point->
Figure BDA0002847482630000095
Common constituent feature Point->
Figure BDA0002847482630000096
Corresponding set G of data sets at n-level i R is a rotation matrix between the projection image coordinate system a and the photographed image coordinate system B.
It can be seen that in calculation G i In the method, a rotation matrix between the projection image coordinate system A and the shooting image coordinate system B is considered, so that the azimuth relation between the projection image and the shooting image is considered, and meanwhile, the scale multiple between the projection image coordinate system A and the shooting image coordinate system B is considered, so that the size relation between the projection image and the shooting image is considered, therefore, the distortion of the projection image can be corrected, the size of the projection image can be changed, and meanwhile, the whole adjustment process of the projection image is very smooth, and better use experience can be given to a user.
Taking n=3 as an example:
substituting m=1, m=2, m=3 into each of the two groups
Figure BDA0002847482630000097
Obtaining a point
Figure BDA0002847482630000098
Figure BDA0002847482630000099
At this time, a->
Figure BDA00028474826300000910
Further, a set of coordinate points P A Coordinate point set P B The centroid calculation method of (2) is as follows:
Figure BDA00028474826300000911
wherein N is the number of feature points. />
The rotation matrix R between the projection image coordinate system A and the shooting image coordinate system B is obtained by calculation through a singular value decomposition method;
specifically, calculating the rotation matrix R includes the steps of:
s100: constructing a covariance matrix H;
s200: let h=usv T Calculating U and V, wherein U and V are unit positive definite matrixes, and S is a diagonal matrix;
s300: let r=vu T Obtaining a rotation matrix R.
Further, the covariance matrix H is set to:
Figure BDA0002847482630000101
the embodiment of the invention also provides a specific adjustment curve, in particular, the characteristic points
Figure BDA0002847482630000102
The corresponding adjustment curve is B (t) i, wherein
Figure BDA0002847482630000103
j is the control point number, ">
Figure BDA0002847482630000104
For K i The j+1th control point in the table, t is a curve adjustment parameter, t is E [0,1 ]]。
Specifically, when n=1,
Figure BDA0002847482630000105
that is, at this time, the feature point
Figure BDA0002847482630000106
The corresponding control points are only two:
Figure BDA0002847482630000107
wherein ,
Figure BDA0002847482630000108
The adjustment curve at this time is essentially a point of origin
Figure BDA0002847482630000109
To the point->
Figure BDA00028474826300001010
Is a straight line of (2);
when n=2, the number of the n-type groups,
Figure BDA00028474826300001011
that is, at this time the feature point +.>
Figure BDA00028474826300001012
The corresponding control points are three points:
Figure BDA00028474826300001013
wherein ,
Figure BDA00028474826300001014
The adjustment curve at this time is substantially defined by the point +.>
Figure BDA00028474826300001015
To the point->
Figure BDA00028474826300001016
Is a parabola of (2);
when n=3, the number of the n-type groups,
Figure BDA00028474826300001017
that is, at this time the feature point +.>
Figure BDA00028474826300001018
The corresponding control points are four points:
Figure BDA00028474826300001019
wherein ,
Figure BDA00028474826300001020
Figure BDA00028474826300001021
The adjustment curve at this time is substantially defined by the point +.>
Figure BDA00028474826300001022
To the point->
Figure BDA00028474826300001023
Is a cubic bezier curve.
The embodiment of the invention also provides a system for calculating the adjustment curve of the projection image, which comprises the following modules:
a set calculation module of the n-level data set: for calculating characteristic points
Figure BDA00028474826300001024
Corresponding set of data sets at n-level +.>
Figure BDA0002847482630000111
Wherein m is G i The sequence number of the point in m E [1, n ]]；
An adjustment curve calculation module: with the characteristic points
Figure BDA0002847482630000112
Set G of data sets at n-level i As a set of control points
Figure BDA0002847482630000113
Calculate feature points->
Figure BDA0002847482630000114
Corresponding adjustment curves, when j=0, < > is given>
Figure BDA0002847482630000115
Let m=j +.0 when j+.0 +.>
Figure BDA0002847482630000116
wherein ,
Figure BDA0002847482630000117
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a feature map is included in a projection image, wherein the feature map is a coordinate point set of all feature points in the feature map in a projection image coordinate system A, the feature map is provided with feature points, n is a scale multiple between the projection image coordinate system A and a shooting image coordinate system B, and the shooting image is an image obtained by shooting the projection image. />
Further, the device also comprises a scale factor calculation module for calculating a scale factor n:
Figure BDA0002847482630000118
wherein, centroid A 、centroid B Respectively coordinate point sets P A Coordinate point set P B Centroid of (2), set of coordinate points P B The average is an average function of a coordinate point set of all feature points in the feature map in a shooting image coordinate system B.
Further, in the set calculation module of the n-level data set:
substituting m=1 to n into each of
Figure BDA0002847482630000119
Get the spot->
Figure BDA00028474826300001110
From the point->
Figure BDA00028474826300001111
Common constituent feature Point->
Figure BDA00028474826300001112
Corresponding set G of data sets at n-level i R is a rotation matrix between the projection image coordinate system a and the photographed image coordinate system B.
Further, a centroid calculation module is also included for calculating centroid A 、centroid B ：
Figure BDA00028474826300001113
Wherein N is the number of feature points,
Figure BDA00028474826300001114
for the set of coordinate points P B Is the i-th point in (a).
Further, the rotation matrix R is calculated by a singular value decomposition method.
Further, the method also comprises a singular value decomposition calculation module for calculating the rotation matrix R:
constructing a covariance matrix H;
let h=usv T Calculating U and V, wherein U and V are unit positive definite matrixes, and S is a diagonal matrix;
let r=vu T Obtaining a rotation matrix R.
Further, the covariance matrix H is:
Figure BDA0002847482630000121
further, the feature points
Figure BDA0002847482630000122
The corresponding adjustment curve is Betz curve B (t) i The said
Figure BDA0002847482630000123
Wherein j is the control point number, +.>
Figure BDA0002847482630000124
For K i The j+1th control point in the table, t is the Betz curve adjustment parameter, t E [0,1 ]]。
The embodiment of the invention also provides a method for adjusting the projection image, which comprises the following steps: and adjusting the projection image by taking each characteristic point as a track according to a corresponding adjusting curve, wherein the adjusting curve is calculated by the method or the adjusting curve is calculated by the system.
The embodiment of the invention also provides a projection device, which comprises a memory and a processor, wherein the memory stores program instructions, and the processor executes the steps in the method when running the program instructions.
Embodiments of the present invention also provide a storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of the method as described above.
From the foregoing description of the embodiments, it will be apparent to those skilled in the art that the present application may be implemented in hardware, or by means of software plus a necessary general hardware platform, and based on this understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disc, a mobile hard disk, etc.), and includes several instructions to cause a computer device (may be a personal computer, a server, or a network device, etc.) to perform the methods described in the respective implementation scenarios of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus, system, and method may be implemented in other manners as well. The above-described apparatus, systems, and method embodiments are merely illustrative, for example, flow charts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. In addition, the functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
In the description, each embodiment is described in a progressive manner, and each embodiment is mainly described by the differences from other embodiments, so that the same similar parts among the embodiments are mutually referred. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.

Claims (17)

1. The method for calculating the adjustment curve of the projection image is characterized by comprising the following steps of:
calculating feature points
Figure FDA0004090991150000011
Corresponding set of data sets at n-level +.>
Figure FDA0004090991150000012
Wherein m is G i The sequence number of the point in m E [1, n ]]；
With the characteristic points
Figure FDA0004090991150000013
Set G of data sets at n-level i As a set of control points
Figure FDA0004090991150000014
Calculate feature points->
Figure FDA0004090991150000015
The corresponding adjustment curve, when j=0,
Figure FDA0004090991150000016
let m=j +.0 when j+.0 +.>
Figure FDA0004090991150000017
wherein ,
Figure FDA0004090991150000018
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a coordinate point set of all feature points in a feature map in a projection image coordinate system A is adopted, the feature map is included in the projection image, the feature points are arranged in the feature map, n is a scale multiple between the projection image coordinate system A and a shooting image coordinate system B, and the shooting image is an image obtained by shooting the projection image;
the characteristic points
Figure FDA0004090991150000019
The corresponding adjustment curve is B (t) i, wherein
Figure FDA00040909911500000110
j is the control point number, ">
Figure FDA00040909911500000111
For K i The j+1th control point in the table, t is a curve adjustment parameter, t is E [0,1 ]]。
2. The method for calculating an adjustment curve of a projection image according to claim 1, wherein the calculation formula of the scale factor n is as follows:
Figure FDA00040909911500000112
wherein, centroid A 、centroid B Respectively coordinate point sets P A Coordinate point set P B Centroid of (2), set of coordinate points P B The average is an average function of a coordinate point set of all feature points in the feature map in a shooting image coordinate system B.
3. An adjustment curve for a projection image as claimed in claim 2The calculation method is characterized in that: substituting m=1 to n into each of
Figure FDA00040909911500000113
Get the spot->
Figure FDA00040909911500000114
From the point->
Figure FDA00040909911500000115
Common constituent feature Point->
Figure FDA00040909911500000116
Corresponding set G of data sets at n-level i R is a rotation matrix between the projection image coordinate system a and the photographed image coordinate system B.
4. A method for calculating an adjustment curve for a projection image according to claim 2, wherein,
Figure FDA0004090991150000021
wherein N is the number of feature points, +.>
Figure FDA0004090991150000022
For the set of coordinate points P B Is the i-th point in (a).
5. A method of calculating an adjustment curve for a projection image according to claim 3, wherein: the rotation matrix R is calculated by a singular value decomposition method.
6. The method of calculating an adjustment curve of a projection image according to claim 5, wherein calculating the rotation matrix R includes the steps of:
constructing a covariance matrix H;
let h=usv T Calculating U and V, wherein U and V are unit positive definite matrixes, and S is a diagonal matrix;
let r=vu T Obtaining a rotation matrix R.
7. The method of calculating an adjustment curve for a projection image according to claim 6, wherein the covariance matrix H is:
Figure FDA0004090991150000023
8. an adjustment curve computing system for projection images, comprising the following modules:
a set calculation module of the n-level data set: for calculating characteristic points
Figure FDA0004090991150000024
Corresponding collection of data sets at n-level
Figure FDA0004090991150000025
Wherein m is G i The sequence number of the point in m E [1, n ]]；
An adjustment curve calculation module: with the characteristic points
Figure FDA0004090991150000026
Set G of data sets at n-level i As a set of control points
Figure FDA0004090991150000027
Calculate feature points->
Figure FDA0004090991150000028
The corresponding adjustment curve, when j=0,
Figure FDA0004090991150000029
let m=j +.0 when j+.0 +.>
Figure FDA00040909911500000210
wherein ,
Figure FDA00040909911500000211
for the set of coordinate points P A The ith point in (a), the coordinate point set P A The method comprises the steps that a coordinate point set of all feature points in a feature map in a projection image coordinate system A is adopted, the feature map is included in the projection image, the feature points are arranged in the feature map, n is a scale multiple between the projection image coordinate system A and a shooting image coordinate system B, and the shooting image is an image obtained by shooting the projection image;
the characteristic points
Figure FDA00040909911500000212
The corresponding adjustment curve is Betz curve B (t) i The said
Figure FDA00040909911500000213
Wherein j is the control point number, +.>
Figure FDA0004090991150000031
For K i The j+1th control point in the table, t is the Betz curve adjustment parameter, t E [0,1 ]]。
9. The system for calculating an adjustment curve for a projection image according to claim 8, further comprising a scale factor calculation module for calculating a scale factor n:
Figure FDA0004090991150000032
wherein, centroid A 、centroid B Respectively coordinate point sets P A Coordinate point set P B Centroid of (2), set of coordinate points P B The average is an average function of a coordinate point set of all feature points in the feature map in a shooting image coordinate system B.
10. The adjustment curve calculation system of a projection image as set forth in claim 9, wherein: substituting m=1 to n into each of
Figure FDA0004090991150000033
Get the spot->
Figure FDA0004090991150000034
From the point->
Figure FDA0004090991150000035
Common constituent feature Point->
Figure FDA0004090991150000036
Corresponding set G of data sets at n-level i R is a rotation matrix between the projection image coordinate system a and the photographed image coordinate system B.
11. The system of claim 9, further comprising a centroid calculation module for calculating centroid A 、centroid B ：
Figure FDA0004090991150000037
Wherein N is the number of feature points, +.>
Figure FDA0004090991150000038
For the set of coordinate points P B Is the i-th point in (a).
12. The system for calculating an adjustment curve for a projection image according to claim 10, wherein: the rotation matrix R is calculated by a singular value decomposition method.
13. The system for calculating an adjustment curve for a projection image according to claim 12, further comprising a singular value decomposition calculation module for calculating the rotation matrix R:
constructing a covariance matrix H;
let h=usv T Calculating U and V, wherein U and V are unit positive definite matrixes, and S is a diagonal matrix;
let r=vu T Obtaining a rotation matrix R.
14. The system for calculating an adjustment curve for a projection image according to claim 13, wherein the covariance matrix H is:
Figure FDA0004090991150000039
15. a method for adjusting a projection image, characterized in that each feature point is used as a track to adjust the projection image according to a corresponding adjustment curve, wherein the adjustment curve is calculated by the method according to one of claims 1 to 7 or the adjustment curve is calculated by the system according to one of claims 8 to 14.
16. A projection device, characterized in that it comprises a memory and a processor, in which program instructions are stored, which processor, when running the program instructions, performs the steps of the method of any of claims 1-7, 15.
17. A storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of the method of any of claims 1-7, 15.
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