CN115147498B - Method for calibrating camera by utilizing asymptote property of known conic of main shaft - Google Patents
Method for calibrating camera by utilizing asymptote property of known conic of main shaft Download PDFInfo
- Publication number
- CN115147498B CN115147498B CN202210768188.9A CN202210768188A CN115147498B CN 115147498 B CN115147498 B CN 115147498B CN 202210768188 A CN202210768188 A CN 202210768188A CN 115147498 B CN115147498 B CN 115147498B
- Authority
- CN
- China
- Prior art keywords
- image
- conic
- quadratic curve
- principal axis
- asymptote
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 17
- 239000011159 matrix material Substances 0.000 claims description 36
- 230000003287 optical effect Effects 0.000 claims description 6
- 238000000354 decomposition reaction Methods 0.000 description 9
- 238000003384 imaging method Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000013507 mapping Methods 0.000 description 2
- 238000003909 pattern recognition Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Computing Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Length Measuring Devices By Optical Means (AREA)
- Image Analysis (AREA)
Abstract
A method for calibrating a camera by utilizing the asymptotic nature of a known conic of a principal axis. The principal axis image and the asymptote image are solved by using the characteristic that the absolute point is relative to the polar line of the quadratic curve, i.e. the tangent line passing through the absolute point is the asymptote. The relation between the asymptote and the absolute point about the quadratic curve meets the polar line relation, and the absolute point image can be obtained by combining the projective invariance, so that the vanishing line is restored. The relationship between the center of the quadratic curve and the infinity line about the quadratic curve satisfies the polar line, and the image of the center of the quadratic curve is obtained by combining the invariance of the projective. The principal axis image intersects the vanishing point with the vanishing line, and forms a set of orthogonal vanishing points with the principal axis image about the poles of the conic. Then 5 images can obtain 5 sets of orthogonal vanishing points, thereby solving the parameters in the pinhole camera using the image constraints of the orthogonal vanishing points and the absolute conic.
Description
Technical Field
The invention belongs to the field of computer vision, and relates to a method for solving parameters in a pinhole camera by utilizing the property of a conic asymptote of a known main shaft in space.
Background
The central task of computer vision is to understand an image, and its ultimate goal is to give the computer the ability to recognize three-dimensional environmental information through two-dimensional images. This capability will not only enable the machine to perceive geometric information of objects in a three-dimensional environment, including shape, pose, motion, etc., but also describe, store, identify and understand them. Camera calibration is the determination of the mapping from a three-dimensional point to its two-dimensional image point, which is an essential step in many computer vision applications. In order to determine this mapping process, a geometric imaging model of the camera needs to be built, and parameters of the geometric model are called camera parameters, and the camera parameters can be classified into an internal parameter and an external parameter. The internal parameters describe the imaging geometry of the imaging system and the external parameters describe the orientation and position of the imaging system with respect to the world coordinate system. Camera calibration can be categorized into traditional calibration, self-calibration, and geometric entity-based calibration. Whichever calibration method aims at establishing a constraint relation, in particular a linear constraint relation, between a two-dimensional image and parameters in a camera, which is a target pursued by current camera calibration and is one of hot spots of current computer vision field research.
The pinhole camera has simple imaging model and convenient manufacture, does not need a plurality of special mirrors, and is one of hot spots for researching the panoramic vision field. Objects of special geometric properties are visible everywhere in an actual scene, and the objects are taken as templates to become an important research direction for camera calibration. Such as points, lines, circles, spheres, etc. The conic with known principal axis and the diameter of special case and confocal conic have good geometric characteristics, which is easy to obtain in real scene. The document "The common self-polar triangle of concentric circles and its application to camera calibration" (H.F.Huang, H.Zhang and y.m. proceedings of The IEEE International Conference on Computer Vision and Pattern Recognition,2015 (1): 4065-4072) uses The properties of a common self-polar triangle of concentric circles to obtain vanishing lines by generalized eigenvalue decomposition, each image being able to obtain two constraints of an image of an absolute conic. In the presence of noise, the concentric images also need to be corrected. The document "Geometric and algebraic constraints of projected concentric circles and their applications to camera calibration" (J.S. Kim, and P.Gurdjos and I.S. Kwen. IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27 (4): 637-642) uses concentric circles as calibration templates to obtain a linear conic beam based on an image of the envelope of two circles, the image of the envelope of the ring points being a linear conic beam degenerate case. The image of the envelope of the ring point can be obtained through generalized eigenvalue decomposition, and a homography matrix is obtained. Each image can get two constraints on the image of the absolute conic. In the presence of noise, the method is applicable anyway. Document "Euclidean structure from confocal conics: theory and application to camera calibration" (J.S.Kim, P.Gurdjos, I.S.Kweon.Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition,2010,11 (4): 803-812) uses confocal conic as a calibration template, and a special case including confocal conic, that is, concentric circles, to obtain a linear conic beam based on an image of an envelope of the confocal conic, and a case where an image of an envelope of a ring point is linear conic degenerated. The image of the envelope of the ring point can be obtained through generalized eigenvalue decomposition, and a homography matrix is obtained. A conic of a known focus, two confocal conic of known half-area ratio and two confocal conic of unknown focus are discussed separately. However, the image of the envelope of the ring point is calculated after the minimum characteristic value is judged, the running time is long, and the robustness is not strong enough under the condition of large noise. The literature Camera calibration using principal-axes aligned central conics (x.h. ying and h.b. zha. Proceedings of the Eighth Asian Conference on Computer Vision,2007 (1): 138-148) uses two principal axis aligned quadric curves as templates, which are more general than confocal quadric curves, and performs eigenvalue decomposition on the two principal axis aligned quadric curves to obtain a set of images of orthogonal vanishing points and centers, and finally linearly solves for camera internal parameters. Document "Central conics with a Common Axis of Symmetry: properties and Applications to Camera Calibration" (Z.J.Zhao.Proc.Twiny-Second int.job conf.artifical Intelligence,2011 (1): 2079-2084) uses two conic lines of common symmetry axis as calibration template, carries out generalized eigenvalue decomposition to the images of the two conic lines to obtain vanishing line, and finally solves the parameters in the camera linearly. The calibration template studied by the method is more general, but after the generalized eigenvalue decomposition is carried out on the image of the quadratic curve, the eigenvalue is needed to be judged to determine the vanishing line, so that the robustness is not strong enough under the condition of large noise.
Disclosure of Invention
The invention provides a target for solving parameters in a pinhole camera, which is simple to manufacture, wide in application and good in stability, and the target is formed by a conic with a known main shaft. In the process of solving the internal parameters of the pinhole camera, 5 images of the target are shot by the pinhole camera, so that 5 internal parameters of the pinhole camera can be solved linearly.
The invention adopts the following technical scheme:
5 images containing a conic whose principal axis is known are taken with a pinhole camera from different positions. The invention relates to a method for solving parameters in a pinhole camera by using a conic with a known principal axis in a plane as a target. Firstly, edge points of a target image are respectively extracted from the image, and a quadratic curve image equation and an equation of an image of a principal axis are obtained by using least square fitting. The principal axis image and the asymptote image are solved by using the characteristic that the absolute point is relative to the polar line of the quadratic curve, i.e. the tangent line passing through the absolute point is the asymptote. The relation between the asymptote and the absolute point about the quadratic curve meets the polar line relation, and the absolute point image can be obtained by combining the projective invariance, so that the vanishing line is restored. The relationship between the center of the quadratic curve and the infinity line about the quadratic curve satisfies the polar line, and the image of the center of the quadratic curve is obtained by combining the invariance of the projective. The principal axis image intersects the vanishing point with the vanishing line, and forms a set of orthogonal vanishing points with the principal axis image about the poles of the conic. Then 5 images can obtain 5 sets of orthogonal vanishing points, thereby solving the parameters in the pinhole camera using the image constraints of the orthogonal vanishing points and the absolute conic. The method comprises the following specific steps of: fitting a target projection equation, solving an image of a pole of a principal axis about a quadratic curve and an image of an asymptote to obtain an absolute point image, recovering an image of a vanishing line and a quadratic curve center, obtaining an orthogonal vanishing point, determining an absolute quadratic curve image, and solving parameters in a pinhole camera.
And judging and obtaining an image of the ring point, determining an image of an absolute conic, and solving parameters in the pinhole camera.
1. Fitting a target projection equation
And extracting pixel coordinates of Edge points of the target image by using Edge functions in a Matlab program, and obtaining a target projection equation by using least square fitting.
2. Solving the principal axis for the image of the pole of the conic and the image of the asymptote
Let the projection of the conic C known to any principal axis L in space be C. Establishing a world coordinate system O by taking the center O of a quadratic curve C as an origin w -x w y w z w Wherein the supporting plane pi where the conic C is located is limited to O w x w y w A plane. Then uses the camera optical center O c Establishing a camera coordinate system O as an origin c -x c y c z c Wherein the image plane pi and O c x c y c The planes are parallel. Then the arbitrary point X on the conic C and the image point X on the conic image C satisfy x=k [ r|t]X, wherein R and t are each the camera coordinate system O c -x c y c z c And world coordinate system O w -x w y w z w A rotation matrix and a translation vector therebetween. By O c The internal reference matrix of the camera which is the optical center isWherein [ u ] 0 v 0 1] T Is the homogeneous coordinate of the main point of the camera, s is the inclination factor, f u And f v Is a scale factor. Wherein f u ，f v ，s，u 0 ，v 0 Is 5 internal parameters of the camera. Here use c n (n=1, 2,3,4, 5) coefficient matrix representing image of conic in nth image, l n (n=1, 2,3,4, 5) represents a coefficient matrix of an image of a principal axis of a conic in the nth image. The curve and its coefficient matrix are denoted by the same letter for simplicity of description herein.
Due to c n Is an image of a conic, l n Is an image of the principal axis. From the nature of the conic asymptote, the image of the pole of the conic and the image of the asymptote can be determined IA ，l JA 。
3. Obtaining absolute point images
Because the asymptote and the absolute point meet the polar line relation about the quadratic curve, the absolute point image m can be obtained by combining the projective invariance IA ，m JA 。
4. Restoring the image of vanishing line and conic center
The asymptote is two special diameters of the quadratic curve, and intersects with the center of the quadratic curve, and can obtain an image o of the center of the quadratic curve by combining with the invariance of the projective. The secondary curve center and the infinity straight line meet the polar line relation about the secondary curve, so the vanishing line l can be restored by combining the projective invariance ∞ 。
5. Obtaining orthogonal vanishing points
The principal axis image intersects with the vanishing line at vanishing point v' ∞ Pole v of secondary curve with main axis ∞ Constitute a set of orthogonal vanishing points.
6. Determining an image of an absolute conic
The 5 images provide 5 groups of vanishing points, and the image omega of the absolute conic is obtained according to the constraint relation between the vanishing points and the image of the absolute conic.
7. Solving for pinhole camera internal parameters
According to ω=k -T K -1 And (3) performing Cholesky decomposition and inversion on the image omega of the absolute quadratic curve to obtain an internal parameter matrix K, namely obtaining 5 internal parameters of the camera.
The invention has the advantages that:
(1) The target is simple to manufacture, and only any secondary curve with a known main shaft is needed.
(2) The image boundary points of the target can be almost completely extracted, so that the accuracy of curve fitting is improved, and the calibration accuracy is further improved.
Drawings
Fig. 1 is a projection model of a target under a pinhole camera.
Detailed Description
The invention provides a target for solving parameters in a pinhole camera, which is composed of a quadratic curve with a known main axis in space, as shown in figure 1. The method for solving the parameters in the pinhole camera by using the novel target comprises the following specific steps:
1. fitting a target projection equation
And extracting pixel coordinates of Edge points of the target image by using Edge functions in a Matlab program, and obtaining a target projection equation by using least square fitting.
2. Solving the principal axis for the image of the pole of the conic and the image of the asymptote
Let the projection of the conic C known to any principal axis L in space be C. Establishing a world coordinate system O by taking the center O of a quadratic curve C as an origin w -x w y w z w . Limiting the plane pi where the quadratic curve C is positioned to O w x w y w A plane. With camera optical centre O c Establishing a camera coordinate system O as an origin c -x c y c z c . Then the arbitrary point X on the conic C and the image point X on the conic image C satisfy x=k [ r|t]X, wherein R and t are camera coordinate system and world, respectivelyRotation matrix and translation vector between boundary coordinate systems. If let O c The internal reference matrix of the camera which is the optical center isWherein [ u ] 0 v 0 1] T Is the homogeneous coordinate of the main point of the camera, s is the inclination factor, f u And f v Is a scale factor. Wherein f u ，f v ，s，u 0 ，v 0 Is 5 internal parameters of the camera. Here use c n (n=1, 2,3,4, 5) coefficient matrix representing image of conic in nth image, l n (n=1, 2,3,4, 5) represents a coefficient matrix of an image of a principal axis of a conic in the nth image. The curve and its coefficient matrix are denoted by the same letter for simplicity of description herein.
Taking the 1 st image as an example, as shown in FIG. 1, a quadratic curve C and an infinity straight line L on a supporting plane n ∞ Intersecting absolute point I A ，J A The following equation set is satisfied:
absolute point I A ，J A Polar line with respect to conic C, i.e. passing I A ，J A The tangent lines of (2) are respectively marked as L IA ，L JA 。L IA ，L JA Is the infinity point I on the overquadratic curve C A ，J A Is tangent to L IA ，L JA Is the two asymptotes of the conic C. The pole line relationship is as follows:
conic C and absolute point I A ，J A Satisfy equation (1), envelope C of conic C according to dual principle * And asymptote L IA ，L JA The method meets the following conditions:
if matrix C is a reversible matrix, then C * And C -1 Differing by a scaling factor lambda, so that the formula (3) is equivalent to
Absolute point I A ，J A At infinity straight line L ∞ And (3) the following steps:
L ∞ ＝I A ×J A ， (5)
where is x outer product. The principal axis L of the conic C necessarily passes through the center O. The line of the center O about the conic C is an infinity line L ∞ . The pole of principal axis L with respect to conic C is infinity point V ∞ ：
V ∞ ＝C -1 L。 (6)
Infinity point V ∞ At infinity straight line L ∞ The following are mentioned:
V ∞ T L ∞ ＝0。 (7)
according to formula (2), formulas (5) and (7) have:
under projective transformation, image m of absolute point IA1 ，m JA1 Is a pair of conjugate complex points, and the image l of the asymptote IA1 ，l JA1 Is a set of conjugate complex straight lines. Image l with asymptote IA1 ，l JA1 The homogeneous coordinate of (1) IA1 ＝[k 1 -k 2 i k 3 -k 4 i 1] T ，l JA1 ＝[k 1 -k 2 i k 3 -k 4 i 1] T . From the projective invariance, it is obtained from (4):
image c of conic section 1 Image l of principal axis 1 It is known that the vanishing point v is based on the invariance of projection ∞1 Can be obtained by the formula (6):
v ∞1 ＝c 1 -1 l 1 。 (10)
according to the relation between the binding property and the polar line, the projection invariance is satisfied, and the projection invariance is represented by the formula (8)
l IA1 ，l JA1 Is a set of conjugate complex straight lines providing the same real and imaginary constraints, so only l is considered here IA1 Real and imaginary parts of (a) are provided. Obtained by the formulas (9) and (11):
where Re represents the real part and Im represents the imaginary part.
Image c of conic section 1 Image l of principal axis 1 It is known that the vanishing point v can be obtained from (10) ∞1 . Solving equation (12) to obtain the asymptote image l IA1 ，l JA1 。
3. Obtaining absolute point images
Asymptote L IA ，L JA Is an infinity straight line L ∞ Upper absolute point I A ，J A Polar line for conic C. Absolute point image m according to projective invariance IA1 ，m JA1 Image l of asymptote IA1 ，l JA1 The pole line relation is satisfied:
4. restoring the image of vanishing line and conic center
Asymptote L IA ，L JA Two special diameters are intersected at the center O of the quadratic curve. According to the invariance of projection, the image l of the asymptote IA1 ，l JA1 Image o intersecting the center of conic 1 ：
o 1 ＝l IA1 ×l JA1 。 (15)
Image o of the centre of the conic 1 Vanishing line l ∞1 The pole line relation is satisfied:
l ∞1 ＝c 1 o 1 。 (16)
5. obtaining orthogonal vanishing points
Image C of conic C 1 Image l of principal axis 1 It is known that the vanishing point v can be obtained according to the expression (10) ∞1 Asymptotic image l IA1 ，l JA1 Absolute point image m IA1 ，m JA1 Image o of conic center 1 Vanishing line l ∞1 . Image l of main shaft 1 Vanishing line l ∞1 Intersecting with vanishing point v' ∞1 ：
v′ ∞1 ＝l 1 ×l ∞1 。 (17)
Image l of main shaft 1 And vanishing point v ∞1 Satisfies pole line relationship, thus v ∞1 ，v′ ∞1 Is a set of orthogonal vanishing points.
6. Determining an image of an absolute conic
5 groups of orthogonal vanishing points can be obtained from 5 images according to the orthogonal vanishing points v ∞i ，v′ ∞i The constraint relation of one to the image omega of the absolute conic can be obtained:
7. solving for pinhole camera internal parameters
According to ω=k -T K -1 And (3) performing Cholesky decomposition and inversion on the image omega of the absolute quadratic curve to obtain an internal parameter matrix K, namely obtaining 5 internal parameters of the camera.
Examples
The invention provides a method for linearly determining parameters in a pinhole camera by using a known quadratic curve of a main shaft in space as a target. The schematic diagram of the template structure adopted by the invention is shown in figure 1. Embodiments of the present invention will be described in more detail below with reference to examples.
1. Fitting image boundaries and target curve equations
5 images of the target are shot by a pinhole camera, the images are read in, pixel coordinates of Edge points of the images of the target are extracted by using Edge functions in Matlab, and a least square method is used for fitting to obtain an equation of an image of a quadratic curve. Here use c n (n=1, 2, …, 5) coefficient matrix representing an image of a conic in the nth image, l n (n=1, 2, …, 5) represents a coefficient matrix of an image of a principal axis of a conic in the nth image, and the result is as follows:
2. solving the principal axis for the image of the pole of the conic and the image of the asymptote
From equation (10), the principal axis can be found with respect to the image v of the pole of the conic ∞1 Coefficient matrix of (c):
similarly, images of the envelope of the absolute points of the other 4 images can be obtained, i.e. their coefficient matrix representation:
asymptotic lines obtainable by equation (12)Image l IA1 ，l JA1 Coefficient matrix of (c):
similarly, the images of the asymptotes of the other 4 images can be obtained, i.e. their coefficient matrix representation:
3. obtaining absolute point images
From (14), an absolute point image m can be obtained I1 ，m J1 Coefficient matrix of (c):
similarly, the images of the absolute points of the other 4 images can be obtained, i.e. their coefficient matrix representation:
4. restoring the image of vanishing line and conic center
From (15) the image o of the conic center can be obtained 1 Coefficient matrix of (c):
similarly, images of the conic centers of the other 4 images can be obtained, i.e. their coefficient matrix representation:
vanishing line l obtainable from (16) ∞1 Coefficient matrix of (c):
similarly, vanishing lines for another 4 images can be obtained, i.e. their coefficient matrix representation:
5. obtaining orthogonal vanishing points
From (17) v ∞1 Orthogonal vanishing point v' ∞1 Coefficient matrix of (c):
similarly, one of the orthogonal vanishing points of the other 4 images can be obtained, i.e. their coefficient matrix representation:
/>
6. determining an image of an absolute conic
Bringing equations (29), (30), (31) (62), (33), (64), (65), (66), (67) and (68) into equation (18) can obtain a linear equation set for ω, and decomposing the equation set SVD can obtain a coefficient matrix for ω, with the following results:
7. solving for pinhole camera internal parameters
According to ω=k -T K -1 K is obtained by Cholesky decomposition of ω in the expression (69) and inversion, and the result is as follows:
the 5 internal parameters of the pinhole camera are respectively: f (f) u ＝849.934190814953，f v ＝900.017406208901，s＝0.192886751110487，u 0 ＝399.978635628115，v 0 ＝299.991507097548
Claims (1)
1. A method for calibrating a camera by utilizing the asymptotic property of a known conic of a principal axis is characterized in that a conic of which the principal axis is known is used as a target; the method comprises the following specific steps: firstly, extracting edge points of a target image from the image, and obtaining a quadratic curve image equation and an image equation of a main shaft by using least square fitting; solving an image of a principal axis about a pole of the quadratic curve and an image of an asymptote by utilizing the characteristic that an polar line of the absolute point about the quadratic curve, namely a tangent line passing through the absolute point, is an asymptote; the asymptote and the absolute point meet the polar line relation about the quadratic curve, and the projection invariance is combined to obtain an absolute point image so as to recover the vanishing line; the relationship between the center of the quadratic curve and the infinity straight line about the quadratic curve meets the polar line, and the image of the center of the quadratic curve is obtained by combining the invariance of the projective; the image of the principal axis intersects with the vanishing line at the vanishing point, and forms a group of orthogonal vanishing points with the image of the pole of the principal axis about the quadratic curve; then 5 images are used for obtaining 5 groups of orthogonal vanishing points, so that parameters in the pinhole camera are solved by utilizing the image constraint of the orthogonal vanishing points and the absolute quadratic curve;
(1) Solving the principal axis for the image of the pole of the conic and the image of the asymptote
Setting the projection of a secondary curve C known by any principal axis L in the space as C; establishing a world coordinate system O by taking the center O of a quadratic curve C as an origin w -x w y w z w Wherein the supporting plane pi where the conic C is located is limited to O w x w y w A plane; then uses the camera optical center O c Establishing a camera coordinate system O as an origin c -x c y c z c Wherein the image plane pi and O c x c y c Planes are parallel; then the arbitrary point X on the conic C and the image point X on the conic image C satisfy x=k [ r|t]X, wherein R and t are each the camera coordinate system O c -x c y c z c And world coordinate system O w -x w y w z w A rotation matrix and a translation vector therebetween; by O c The internal reference matrix of the camera which is the optical center isWherein [ u ] 0 v 0 1] T Is the homogeneous coordinate of the main point of the camera, s is the inclination factor, f u And f v Is a scale factor; wherein f u ，f v ，s，u 0 ，v 0 5 internal parameters for the camera; here use c n Where n=1, 2,3,4,5, a coefficient matrix representing an image of a conic in the nth image, l n Where n=1, 2,3,4,5 represents a coefficient matrix of an image of a principal axis of a conic in the nth image; for simplicity of description herein, the same letter is used to represent the curve and its coefficient matrix;
due to c n Is an image of a conic, l n Is an image of the principal axis; determining the image of the pole of the conic and the image l of the asymptote based on the nature of the conic asymptote IA ，l JA ；
(2) Obtaining absolute point images
Because the asymptote and absolute point relate to the quadratic orderThe curve meets the polar line relation and combines with the projective invariance to obtain an absolute point image m IA ，m JA ；
(3) Restoring the image of vanishing line and conic center
The asymptote is two special diameters of the quadratic curve, and intersects with the center of the quadratic curve, and combines with the projective invariance to obtain an image o of the center of the quadratic curve; the secondary curve center and the infinity straight line meet the polar line relation about the secondary curve, so the vanishing line l is restored by combining the projective invariance ∞ ；
(4) Obtaining orthogonal vanishing points
The principal axis image intersects with the vanishing line at vanishing point v' ∞ Pole v of secondary curve with main axis ∞ Constitute a set of orthogonal vanishing points.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210768188.9A CN115147498B (en) | 2022-06-30 | 2022-06-30 | Method for calibrating camera by utilizing asymptote property of known conic of main shaft |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210768188.9A CN115147498B (en) | 2022-06-30 | 2022-06-30 | Method for calibrating camera by utilizing asymptote property of known conic of main shaft |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115147498A CN115147498A (en) | 2022-10-04 |
| CN115147498B true CN115147498B (en) | 2024-03-22 |
Family
ID=83409725
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210768188.9A Active CN115147498B (en) | 2022-06-30 | 2022-06-30 | Method for calibrating camera by utilizing asymptote property of known conic of main shaft |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115147498B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108921904A (en) * | 2018-07-13 | 2018-11-30 | 云南大学 | Utilize the method for the property of single ball and asymptote calibration pinhole camera |
| CN109035342A (en) * | 2018-07-13 | 2018-12-18 | 云南大学 | Utilize the method for straight line and circular point polar curve calibration parabolic catadioptric video camera |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130259403A1 (en) * | 2012-04-03 | 2013-10-03 | Oluwatosin Osinusi | Flexible easy-to-use system and method of automatically inserting a photorealistic view of a two or three dimensional object into an image using a cd,dvd or blu-ray disc |
-
2022
- 2022-06-30 CN CN202210768188.9A patent/CN115147498B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108921904A (en) * | 2018-07-13 | 2018-11-30 | 云南大学 | Utilize the method for the property of single ball and asymptote calibration pinhole camera |
| CN109035342A (en) * | 2018-07-13 | 2018-12-18 | 云南大学 | Utilize the method for straight line and circular point polar curve calibration parabolic catadioptric video camera |
Non-Patent Citations (1)
| Title |
|---|
| 基于一组对应消失线的度量重建;祝海江, 吴福朝;软件学报;20040530(第05期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115147498A (en) | 2022-10-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110853100B (en) | Structured scene vision SLAM method based on improved point-line characteristics | |
| CN106919944B (en) | ORB algorithm-based large-view-angle image rapid identification method | |
| Zhang et al. | Vision-based pose estimation for textureless space objects by contour points matching | |
| CN107886546B (en) | Method for calibrating parabolic catadioptric camera by utilizing spherical image and public autocolar triangle | |
| CN109405835B (en) | Relative pose measurement method based on non-cooperative target straight line and circular monocular image | |
| CN109325983A (en) | Parabolic catadioptric video camera is demarcated about the linear matter of entelechy using infinite point | |
| CN108921904B (en) | Method for calibrating pinhole camera by using properties of single ball and asymptote | |
| CN115147498B (en) | Method for calibrating camera by utilizing asymptote property of known conic of main shaft | |
| CN117372244A (en) | Large scene feature stereo matching method based on two-dimensional array representation | |
| CN110148183B (en) | Method, storage medium, and system for calibrating a camera using sphere and pole lines | |
| CN109035342B (en) | Method for calibrating parabolic catadioptric camera by using one straight line and circular ring point polar line | |
| CN109360247B (en) | Common autocolar and orthogonal vanishing point calibration parabolic camera for single ball | |
| CN112418250A (en) | Optimized matching method for complex 3D point cloud | |
| CN114581515A (en) | Multi-camera calibration parameter optimization method based on optimal path conversion | |
| CN107958468B (en) | Method for calibrating central catadioptric camera by three balls with different spatial positions | |
| CN113345033B (en) | Method and system for calibrating internal parameters of central catadioptric camera | |
| CN111429522B (en) | Method and system for calibrating camera by using common pole polar line property of coplanar circles | |
| CN113610926B (en) | Camera calibration method based on vanishing point orthogonality | |
| CN109272558B (en) | Method for calibrating pinhole camera by using common free-pole triangle and circular ring points of separating circles | |
| CN109191528B (en) | Method for calibrating pinhole camera by using properties of spherical image and circular ring point polar line | |
| Zhang | Binocular Stereo Vision | |
| Liang et al. | An integrated camera parameters calibration approach for robotic monocular vision guidance | |
| CN109934879B (en) | Method for calibrating parabolic catadioptric camera by utilizing ball and public autocolar triangle | |
| CN109064519B (en) | Method for calibrating parabolic catadioptric camera by using one linear and circular asymptote line | |
| CN111223149A (en) | Method for calibrating camera internal parameters based on properties of two separation circles with same radius |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |