CN104050661A - Method for adjusting accuracy of area scanning three-dimensional measuring system in real time - Google Patents

Abstract

The invention discloses a method for adjusting the accuracy of an area scanning three-dimensional measuring system in real time. The method includes the steps that first, whether the accuracy of the area scanning three-dimensional measuring system meets the requirement or not can be determined by judging whether the internal and external parameters of a camera meet the current working condition requirement, if the internal and external parameters of the camera meet the current working condition requirement, measuring continues, otherwise, a Levenberg-Marquardt algorithm is used for optimizing the internal and external parameters of the camera, so that the average value of objective functions is made to be minimum, and at the moment, the internal and external parameters of the camera are considered to be optimal; afterwards, whether the average value of the objective functions is smaller than an error threshold value or not is judged, if yes, the optimized internal and external parameters of the camera are used for measuring continuously, and if not, a user is prompted to conduct calibration again. By the adoption of the method, self testing of the accuracy and automatic optimizing of the parameters of the camera can be conducted in real time in an on-line mode, and under the condition that repeated calibration is avoided, the average value of reprojection errors of the camera can be kept at the pixel of about 0.0028 for more than twenty days.

Description

The method of real-time adjustment of face scanning three-dimensional measurement system accuracy

Technical field

The invention belongs to face scanning three-dimensional measurement technical field, more specifically, relate to the method for real-time adjustment of a kind of scanning three-dimensional measurement system accuracy.

Background technology

Camera inner parameter and calibrating external parameters precision are the keys of three-dimension measuring system, and due to the complicacy of working environment, camera internal and external parameter is affected by environment and constantly change, and its precision has a strong impact on and restricting the precision of face scanning three-dimensional measurement result.At present, face scanning three-dimensional measurement system is more and more wider in the application in the fields such as industrial accuracy detection, the manufacture of increasing material, cultural relic digitalization, medical treatment, 3D photograph, yet owing to being subject to the impact that in the course of work, camera internal and external parameter changes, face scanning three-dimensional measurement system in use needs frequently to carry out parameter calibration, and operating process is loaded down with trivial details.

Owing to being subject to the impact of heat effect in environment temperature, the course of work, can there is temperature and float in camera associated components, and fixedly the support of double camera can be owing to being subject to heat effect to produce thermal strain; Vibrations in the course of work, change fixing, Support Position also can make fixed support produce microdeformation; The parts such as the screw of fixed camera are loosening in vibration processes, can cause that two camera fixed positions change; The variation of air humidity also can cause camera inner parameter and external parameter generation respective change.These subtle change all can produce significant impact by scanning three-dimensional measurement system such precision optics equipment in opposite, have had a strong impact on the precision of three-dimensional reconstruction result.

In order to reach accuracy requirement, except guaranteeing that when demarcating calibration result reaches certain accuracy requirement, the also constantly variation of camera internal and external parameter in monitoring process, and carry out certain correction and compensation.Traditional method is, carries out at set intervals system accuracy monitoring, if precision cannot meet the demands, again demarcates.Yet due to accuracy monitoring, calibration process complexity, consuming time, and cannot carry out online, this has had a strong impact on the work efficiency of face scanning three-dimensional measurement system; In addition, owing to lacking corresponding self-sensing method and mechanism, user cannot know that when the measurement result precision of face scanning three-dimensional measurement system has exceeded permissible error threshold value, require user must possess relevant speciality attainment and abundant practical experience, to when carrying out the demarcation again of camera, challenge has been proposed.

Summary of the invention

Above defect or Improvement requirement for prior art, the invention provides the method for real-time adjustment of a kind of scanning three-dimensional measurement system accuracy, can effectively solve face scanning three-dimensional measurement system accuracy detection difficult, repeat to demarcate problem frequently, automatically whether coincidence measurement requirement of the precision of detection faces scanning three-dimensional measurement system, real-time optimization correlation parameter makes face scanning three-dimensional measurement system keep suitable precision, reduces and again demarcates number of times.

For achieving the above object, according to one aspect of the present invention, the method for real-time adjustment of a kind of scanning three-dimensional measurement system accuracy is provided, described scanning three-dimensional measurement system comprises projector, first camera and second camera, it is characterized in that, comprise the steps:

(1), to first camera and second camera, all vertically using multifrequency heterodyne approach solution to obtain mutually phase diagram with horizontal direction;

(2) on the phase diagram of first camera, divide virtual grid and choose sampled point, then according to phase value constraint, carry out phase matching, find the corresponding point on the phase diagram of second camera;

(3) give up the Mismatching point on the first camera plane of delineation;

(4) the residue sampled point on the calculating first camera plane of delineation, to the mean value of the distance of corresponding polar curve, if it is less than error threshold e, continues to measure, and elapsed time T, returns to step (1); Otherwise execution step (5), wherein, T is the time interval of system accuracy monitoring, and the polar curve of described correspondence refers to residue sampled point on the first camera plane of delineation corresponding point on second camera phase diagram corresponding polar curve on the plane of delineation of first camera;

(5) utilize Levenberg-Marquardt algorithm, make residue sampled point on the first camera plane of delineation reach minimum to the mean value of the distance of corresponding polar curve, to optimize first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras;

(6) judging whether residue sampled point on the first camera plane of delineation is less than error threshold e to the mean value of the distance of corresponding polar curve, is by the first camera inner parameter matrix K after optimizing _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras continue to measure, elapsed time T, returns to step (1); Otherwise prompting user re-starts demarcation.

Preferably, described step (1) is specially: with the sinusoidal grating image of projector projection level, to testee, the image that uses multifrequency heterodyne approach to obtain two cameras is separated phase, obtains respectively the phase diagram that phase value along continuous straight runs increases progressively; With the vertical sinusoidal grating image of projector projection, to testee, the image that uses multifrequency heterodyne approach to obtain two cameras is separated phase, obtains respectively the phase diagram that phase value vertically increases progressively.

Preferably, described step (2) further comprises the steps: that (2-1) divides virtual grid and obtain m * n angle point as sampled point on one of them phase diagram F1 of first camera, and wherein, m, n are integer; (2-2), for any one the sampled point P1 on F1, in the phase diagram S1 identical with F1 direction of second camera, find a curve L1 identical with this phase value; (2-3) on another phase diagram F2 of first camera, find the some P2 identical with P1 pixel coordinate; (2-4) in another phase diagram S2 of second camera, find the curve L2 identical with P2 phase value; (2-5) pixel coordinate apart from mean value point corresponding with sampled point P1 and P2 on S1 and S2 of the pixel coordinate of two points of minimum using pixel coordinate on L1 and L2, obtains P1 and the P2 corresponding point on S1 and S2; (2-6) repeat above-mentioned steps (2-2) to (2-5), obtain all sampled points on first camera phase diagram corresponding point on second camera phase diagram.

Preferably, described step (3) further comprises the steps: that (3-1) is according to polar curve geometrical principle, corresponding point for each sampled point on the first camera plane of delineation on second camera phase diagram, calculate its polar curve l corresponding on the plane of delineation of first camera ₁, l ₂..., l _i..., l _{m * n}, wherein, i is integer and 1≤i≤(m * n), x _rifor the homogeneous pixel coordinate of corresponding point, K _r ^-Tfor second camera inner parameter matrix K _rcontrary transposition, for first camera inner parameter matrix K _lcontrary; (3-2) all sampled points that calculate on the first camera plane of delineation arrive corresponding polar curve l ₁, l ₂..., l _i..., l _{m * n}distance d ₁, d ₂..., d _i..., d _{m * n}; (3-3) calculate d ₁, d ₂..., d _i..., d _{m * n}average value mu and standard deviation sigma; (3-4) by d _i≤ (μ-1.96 σ) or d _isampled point on the first camera plane of delineation of>=(μ+1.96 σ) correspondence is given up.

Preferably, described step (5) further comprises the steps: that (5-1) builds the homogeneous pixel coordinate x ' with the residue sampled point on the first camera plane of delineation _ljpixel coordinate x ' with point corresponding with residue sampled point on the first camera plane of delineation on the second camera plane of delineation _rjfor independent variable, with first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras be undetermined coefficient, the Nonlinear System of Equations that the residue sampled point of take on the first camera plane of delineation is objective function to the distance of corresponding polar curve; (5-2) utilize Levenberg-Marquardt algorithm to make the mean value of the objective function in Nonlinear System of Equations reach minimum, to optimize first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras.

In general, the above technical scheme of conceiving by the present invention compared with prior art, first by judging whether camera internal and external parameter meets the requirement of work at present state and determine whether the precision of face scanning three-dimensional measurement system meets the requirements, if camera internal and external parameter meets the requirement of work at present state, continue to measure, otherwise utilize Levenberg-Marquardt algorithm to be optimized camera internal and external parameter, make the mean value of objective function minimum, now think that camera internal and external parameter is optimum; Whether the mean value that then judges objective function is less than error threshold, be with the camera internal and external parameter after optimizing, to continue to measure, otherwise prompting user re-starts demarcation.This method can be carried out precision in real time, online from detecting and camera parameter Automatic Optimal, in the situation that not repeating to demarcate, can make the re-projection error mean value of camera remain on 0.0028 pixel left and right and reach more than 20 days.

Accompanying drawing explanation

Fig. 1 is the method for real-time adjustment process flow diagram of the face scanning three-dimensional measurement system accuracy of the embodiment of the present invention;

Fig. 2 is the method flow diagram that finds the corresponding point of first camera phase diagram up-sampling point on second camera phase diagram;

Fig. 3 is the schematic diagram that finds the corresponding point of first camera phase diagram up-sampling point on second camera phase diagram, wherein, (a) phase diagram that the phase value along continuous straight runs of first camera increases progressively, (b) phase diagram that the phase value along continuous straight runs of second camera increases progressively, (c) phase diagram that the phase value of first camera vertically increases progressively, the phase diagram that (d) phase value of second camera vertically increases progressively.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.In addition,, in each embodiment of described the present invention, involved technical characterictic just can not combine mutually as long as do not form each other conflict.

In the method for real-time adjustment of the face scanning three-dimensional measurement system accuracy of the embodiment of the present invention, face scanning three-dimensional measurement system comprises projector, first camera and second camera.As shown in Figure 1, the method specifically comprises the steps:

(1), to first camera and second camera, all vertically using multifrequency heterodyne approach solution to obtain mutually phase diagram with horizontal direction.

Particularly, with the sinusoidal grating image of projector projection level, to testee, the image that uses multifrequency heterodyne approach to obtain two cameras is separated phase, obtains respectively the phase diagram that phase value along continuous straight runs increases progressively; With the vertical sinusoidal grating image of projector projection, to testee, the image that uses multifrequency heterodyne approach to obtain two cameras is separated phase, obtains respectively the phase diagram that phase value vertically increases progressively.Preferably, sinusoidal grating image is 3 groups of totally 12 width.

(2) on the phase diagram of first camera, divide virtual grid and choose sampled point, then according to phase value constraint, carry out phase matching, find the corresponding point on the phase diagram of second camera.

As shown in Figures 2 and 3, further comprise the steps:

(2-1) on one of them phase diagram F1 of first camera, divide virtual grid and obtain m * n angle point as sampled point.Wherein, m, n are integer, preferably, m, n >=8, the value of m and n should be large as far as possible, but too conference causes counting yield to decline, and m * n is advisable in 100 left and right.

(2-2), for any one the sampled point P1 on F1, in the phase diagram S1 identical with F1 direction of second camera, find a curve L1 identical with this phase value.

(2-3) on another phase diagram F2 of first camera, find the some P2 identical with P1 pixel coordinate.

(2-4) in another phase diagram S2 of second camera, find the curve L2 identical with P2 phase value.

(2-5) ideally, curve L1 goes up with L2 the corresponding point that the identical point of pixel coordinate is P1 (or P2), but owing to there being error, two curves are not necessarily continuous.Therefore, traversal L1 and L2, obtain the upper pixel coordinate of L1 and L2 apart from two points of minimum, using the mean value of the pixel coordinate of these two points as S1 with the pixel coordinate of the upper point corresponding with sampled point P1 and P2 of S2, thereby obtain P1 and the corresponding point of P2 on S1 and S2.

(2-6) repeat above-mentioned steps (2-2) to (2-5), obtain all sampled points on first camera phase diagram corresponding point on second camera phase diagram.

(3) use Principle of Statistics, give up the Mismatching point on the first camera plane of delineation.

Further comprise the steps:

(3-1), according to polar curve geometrical principle, the corresponding point for each sampled point on the first camera plane of delineation on second camera phase diagram, calculate its polar curve l corresponding on the plane of delineation of first camera ₁, l ₂..., l _i..., l _{m * n}, wherein, i is integer and 1≤i≤(m * n), l _ifor:

$l_i=x_{\mathrm{ri}}{K}_r^{-T}{\mathrm{SRK}}_l^{-1}$

Wherein, x _rifor the homogeneous pixel coordinate of corresponding point, K _r ^-Tfor second camera inner parameter matrix K _rcontrary transposition, S is the antisymmetric matrix corresponding to position relationship translation vector of two cameras, R is the position relationship rotation matrix of two cameras, for first camera inner parameter matrix K _lcontrary.

(3-2) all sampled points that calculate on the first camera plane of delineation arrive corresponding polar curve l ₁, l ₂..., l _i..., l _{m * n}distance d ₁, d ₂..., d _i..., d _{m * n}.

(3-3) calculate d ₁, d ₂..., d _i..., d _{m * n}average value mu and standard deviation sigma.

(3-4) d under normal circumstances, _inormal Distribution, because normal distyribution function is:

$f\left(x\right)=\frac{1}{\mathrm{\σ}\sqrt{2\mathrm{\π}}}\·e^{\frac{{(x-\mathrm{\μ})}^2}{2{\mathrm{\σ}}^2}}$

F (x) is at interval (μ-1.96 σ of transverse axis, μ+1.96 σ) area surrounding with x axle in is 95.449974%, 95.449974% sampled point drops on transverse axis interval (μ-1.96 σ to the distance of corresponding polar curve, μ+1.96 σ) in, therefore as (μ-1.96 σ) <d _i< (μ+1.96 σ), can think and have 95.449974% probability to find correct corresponding point; Work as d _inot in this interval, i.e. d _i≤ (μ-1.96 σ) or d _iduring>=(μ+1.96 σ), because the correct probability mating is less than 5%, we think wrong match point, and sampled point corresponding with it on the first camera plane of delineation is given up.

(4) the residue sampled point on the calculating first camera plane of delineation, to the mean value of the distance of corresponding polar curve, if it is less than error threshold e, continues to measure, and elapsed time T, returns to step (1); Otherwise execution step (5), wherein, T is the time interval of system accuracy monitoring.

E is an empirical value, and the too little meeting of e value causes too much unnecessary repeated optimization and repeat demarcating, and e value too conference affects measuring accuracy, and for example, for powerscan series scanning device, can get e is 0.003 pixel.T is also an empirical value, gets T=0.5 hour during general firm start, and follow-up desirable 3 to 10 hours, depending on working environment, environment was more complicated, and T value is less.

(5) utilize Levenberg-Marquardt algorithm, optimize first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras, make residue sampled point on the first camera plane of delineation reach minimum to the mean value of the distance of corresponding polar curve.

Further comprise following sub-step:

(5-1) build the homogeneous pixel coordinate x ' with the residue sampled point on the first camera plane of delineation _ljpixel coordinate x ' with point corresponding with residue sampled point on the first camera plane of delineation on the second camera plane of delineation _rjfor independent variable, with first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras be undetermined coefficient, the Nonlinear System of Equations that the residue sampled point of take on the first camera plane of delineation is objective function to the distance of corresponding polar curve:

d′ ₁＝F(K _l,K _r,R,S,x′ _l1,x′ _r1)

d′ ₂＝F(K _l,K _r,R,S,x′ _l2,x′ _r2)

…

d′ _j＝F(K _l,K _r,R,S,x′ _lj,x′ _rj)

…

d′ _k＝F(K _l,K _r,R,S,x′ _lk,x′ _rk)

Wherein, k is the residue total number of sample points on the first camera plane of delineation, and j is integer and 1≤j≤k.

(5-2) utilize Levenberg-Marquardt algorithm to first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras be optimized, and makes objective function d ' ₁, d ' ₂..., d ' _j..., d ' _kmean value reach minimum.

(6) judging whether residue sampled point on the first camera plane of delineation is less than error threshold e to the mean value of the distance of corresponding polar curve, is by the first camera inner parameter matrix K after optimizing _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras continue to measure, elapsed time T, returns to step (1); Otherwise prompting user re-starts demarcation.

Those skilled in the art will readily understand; the foregoing is only preferred embodiment of the present invention; not in order to limit the present invention, all any modifications of doing within the spirit and principles in the present invention, be equal to and replace and improvement etc., within all should being included in protection scope of the present invention.

Claims (5)

1. a method of real-time adjustment for face scanning three-dimensional measurement system accuracy, described scanning three-dimensional measurement system comprises projector, first camera and second camera, it is characterized in that, comprises the steps:

(1), to first camera and second camera, all vertically using multifrequency heterodyne approach solution to obtain mutually phase diagram with horizontal direction;

(2) on the phase diagram of first camera, divide virtual grid and choose sampled point, then according to phase value constraint, carry out phase matching, find the corresponding point on the phase diagram of second camera;

(3) give up the Mismatching point on the first camera plane of delineation;

(4) the residue sampled point on the calculating first camera plane of delineation, to the mean value of the distance of corresponding polar curve, if it is less than error threshold e, continues to measure, and elapsed time T, returns to step (1); Otherwise execution step (5), wherein, T is the time interval of system accuracy monitoring, and the polar curve of described correspondence refers to residue sampled point on the first camera plane of delineation corresponding point on second camera phase diagram corresponding polar curve on the plane of delineation of first camera;

(5) utilize Levenberg-Marquardt algorithm, make residue sampled point on the first camera plane of delineation reach minimum to the mean value of the distance of corresponding polar curve, to optimize first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras;

(6) judging whether residue sampled point on the first camera plane of delineation is less than error threshold e to the mean value of the distance of corresponding polar curve, is by the first camera inner parameter matrix K after optimizing _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras continue to measure, elapsed time T, returns to step (1); Otherwise prompting user re-starts demarcation.

2. the method for real-time adjustment of as claimed in claim 1 scanning three-dimensional measurement system accuracy, it is characterized in that, described step (1) is specially: use the sinusoidal grating image of projector projection level to testee, the image that uses multifrequency heterodyne approach to obtain two cameras is separated phase, obtains respectively the phase diagram that phase value along continuous straight runs increases progressively; With the vertical sinusoidal grating image of projector projection, to testee, the image that uses multifrequency heterodyne approach to obtain two cameras is separated phase, obtains respectively the phase diagram that phase value vertically increases progressively.

3. the method for real-time adjustment of as claimed in claim 1 or 2 scanning three-dimensional measurement system accuracy, is characterized in that, described step (2) further comprises the steps:

(2-1) on one of them phase diagram F1 of first camera, divide virtual grid and obtain m * n angle point as sampled point, wherein, m, n are integer;

(2-2), for any one the sampled point P1 on F1, in the phase diagram S1 identical with F1 direction of second camera, find a curve L1 identical with this phase value;

(2-3) on another phase diagram F2 of first camera, find the some P2 identical with P1 pixel coordinate;

(2-4) in another phase diagram S2 of second camera, find the curve L2 identical with P2 phase value;

(2-5) pixel coordinate apart from mean value point corresponding with sampled point P1 and P2 on S1 and S2 of the pixel coordinate of two points of minimum using pixel coordinate on L1 and L2, obtains P1 and the P2 corresponding point on S1 and S2;

(2-6) repeat above-mentioned steps (2-2) to (2-5), obtain all sampled points on first camera phase diagram corresponding point on second camera phase diagram.

4. the method for real-time adjustment of face scanning three-dimensional measurement system accuracy as claimed any one in claims 1 to 3, is characterized in that, described step (3) further comprises the steps:

(3-1), according to polar curve geometrical principle, the corresponding point for each sampled point on the first camera plane of delineation on second camera phase diagram, calculate its polar curve l corresponding on the plane of delineation of first camera ₁, l ₂..., l _i..., l _{m * n}, wherein, i is integer and 1≤i≤(m * n), x _rifor the homogeneous pixel coordinate of corresponding point, K _r ^-Tfor second camera inner parameter matrix K _rcontrary transposition, for first camera inner parameter matrix K _lcontrary;

(3-2) all sampled points that calculate on the first camera plane of delineation arrive corresponding polar curve l ₁, l ₂..., l _i..., l _{m * n}distance d ₁, d ₂..., d _i..., d _{m * n};

(3-3) calculate d ₁, d ₂..., d _i..., d _{m * n}average value mu and standard deviation sigma;

(3-4) by d _i≤ (μ-1.96 σ) or d _isampled point on the first camera plane of delineation of>=(μ+1.96 σ) correspondence is given up.

5. the method for real-time adjustment of as claimed in claim 1 scanning three-dimensional measurement system accuracy, is characterized in that, described step (5) further comprises the steps:

(5-1) build the homogeneous pixel coordinate x ' with the residue sampled point on the first camera plane of delineation _ljpixel coordinate x ' with point corresponding with residue sampled point on the first camera plane of delineation on the second camera plane of delineation _rjfor independent variable, with first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras be undetermined coefficient, the Nonlinear System of Equations that the residue sampled point of take on the first camera plane of delineation is objective function to the distance of corresponding polar curve;

(5-2) utilize Levenberg-Marquardt algorithm to make the mean value of the objective function in Nonlinear System of Equations reach minimum, to optimize first camera inner parameter matrix K _l, second camera inner parameter matrix K _r, the antisymmetric matrix S corresponding to position relationship translation vector of two cameras and the position relationship rotation matrix R of two cameras.