CN104463893B - The sequence three-dimensional image matching method of prior information conduction - Google Patents
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Abstract
The invention discloses belonging to the sequence 3 D visual image matching process of navigation and a kind of prior information conduction of automatic control technology field.The method carries out left and right mesh dense feature Point matching first to first pair of stereo-picture, then from the beginning of second stereogram, each matching to stereo-picture is matched as guidance information to matching result using previous, the last left and right mesh images match result using current imaging is used as guidance information, to the imaging volume picture of next adjacent view to repeat the above steps all operations, the matching result of all images of whole continuous imaging sequence is obtained.Present invention utilizes the characteristics of field of view of continuous imaging is overlapped, the effect for improving matching accuracy and speed is reached, speed and precision can be greatly improved in fields such as automatic driving vehicle navigation, celestial body surface detector visual spatial attentions, it is ensured that the navigation of view-based access control model image can reliable, stable safe operation with control.
Description
Technical field
The invention belongs to information technology, computer vision, navigation and automatic control technology field, and in particular to a kind of priori
The sequence 3 D visual image matching process of Information Conduction.
Background technology
In the applications such as robot vision, the navigation of vehicle automatic vision, it is imaged by the continuous stereo of different visual angles, is obtained
The image of surrounding scene, processes target measurement and terrain environment in achievable visual field scene by analysis and accurately perceives.This regards
Key issue in feel image processing process is the left and right mesh images match of each three-dimensional imaging, and it is to complete environment sensing, lead
The key link of boat positioning, is that the calculating of the visual field Context aware of view-based access control model puies forward arch data input.The stereogram of continuous imaging
As matching process is faced with the unfavorable factors such as imaging circumstances are complicated, scene is unknown, Auto-matching difficulty is big, is containing visual navigation
The bottleneck problem of successful implementation.Stereo image matching to continuous imaging, at present conventional method is it is not intended that scene content, and
It is, directly using basic disparity estimation to matching per a pair or so mesh images, there is mismatch rate height, time loss length etc. no
Foot.
At present, solution to the problems described above is that the method is for continuous using the matching process based on independent image pair
It is each in imaging that stereo pairs are individually matched, finally by the dense Stereo Matching result COMPREHENSIVE CALCULATING of all stereograms,
Carry out scene target measurement and landform in the visual field to recover, so as to complete environment sensing.To each to space image during the method is usual
It is correlation method images match to matching adopted method.That is, to each point (u, v) in the left figure in the view stereo image of left and right
Matching process be that it is initial position with position identical point (u, v) to be chosen in right figure first, the vertex neighborhood in right figure
Search Corresponding matching point position in interior enough (horizontal direction u-dL～u+dL, vertical direction v-dH～v+dH) on a large scale, it is determined that
Every bit local left figure and right figure carry out relevant matches within the range, retain coefficient correlation fij, finally select the model in right figure
Enclose interior coefficient correlation maximum point as matching result.Based on this, the process of realizing of sequence cubic phase pair is, to continuously into
The each pair stereo-picture of picture repeats with previous to the process of image identical method, completes the left images matching of stereogram, most
The matching of whole sequence of stereoscopic images is completed eventually, each point is calculated by all match points, obtain whole scene objects and survey
Amount and environment sensing.
Using said method, as left and right mesh camera image parallax is big and uncertain, the hunting zone of each pair image needs
Set sufficiently large, therefore matching speed is slower, it is particularly with the three-dimensional dense Stereo Matching demand for building of terrain environment, slow-footed
Shortcoming is more projected.Continuous imaging stereogram is independently matched, and does not introduce adjacent cube picture to directly interrelated
Information, for measuring to the environment of general area to overall multiple pictures, needs all stereo matching results to be integrated into
Used together, matching efficiency is relatively low.
The content of the invention
It is an object of the invention to provide a kind of sequence 3 D visual image matching process of prior information conduction.Using this
Method when each pair image to continuous imaging is matched, can by overlapping region adjacent upper a pair of three-dimensional imagings
With result as prior information, the images match of front left and right view stereo image pair is worked as in guiding, so as to improve whole stereogram sequence
The matching efficiency of row.
A kind of sequence 3 D visual image matching process of prior information conduction, comprises the steps：
Left and right mesh dense feature Point matching is carried out to first pair of stereo-picture, its matching process is described as：
Carry out feature point extraction on (1) first pair of left and right mesh stereogram respectively, obtain respective set of characteristic points, i.e., it is left
Figure point set and right figure point set；
(2) successively to each point in left figure point setIts homonymy matching point is found in right figure point set, it is determined that side
Method for select right figure on point concentrate withDistance within the specific limits with left figure pointPoint with maximum correlation coefficient, if
The coefficient correlation is then defined as homonymy matching point more than threshold value 0.75, and this operation is carried out to each point, final to obtain left and right
Scheme registering point set of the same name；
(3) to each point to be matched in left figureAt the beginning of the left figure Point matching of the point set of the same name that above-mentioned (2) step determines
Value point rangeIn, detection range withThree nearest match points Determine that condition is：
3 points are not arranged on the same straight line, and its three same place in right figureAlso not same
On one straight line；
(4) affine Transform Model of the to be matched adjacent domain between left and right figure is calculated, it is of the same name by three selected
Point resolves parameter a of affine transformation1～c2, according to affine model parameter, to each point in model area in left figure to be matchedCalculate its primary election match point in right figureComputational methods are given by；
x′R=a1xL+b1yL+c1
y′R=a2xL+b2yL+c2
(5) determine point to be matched in left figureFinal accurate same place in right figure, in the right figure more than
The point that one step is calculatedFor homonymy matching initial value point, it is optimized using least square method, obtains final essence
True match point
(6) repeat above-mentioned (3)～(5) step, obtain all homonymy matching point ranges
From the beginning of second stereogram, to each matching to stereo-picture using it is previous to matching result as leading
Fuse breath is matched, and the process is realized by following steps：
(7) images match of the public domain part that the centering of current picture and adjacent previous stereo pairs are overlapped is calculated,
The step by the adjacent point for being imaged public domain twice from upper one matched image to being above transferred to current image to be matched
To upper, so as to obtain the matching initial value in the region；
(8) present image pair carries out images match with the overlapping region part of last imaging；
(9) images match is carried out with the Non-overlapping Domain of previous imaging in present image；
Left and right mesh images match result using current imaging is used as guidance information, the imaging volume to next adjacent view
As to above-mentioned (7th)～(9) the step all operations of repetition, obtaining the matching result of all images of whole continuous imaging sequence.
The left figure point set is combined intoI=1,2,3...N, right figure point set is combined intoI=1,2,
3...M, figure registering point set of the same name in left and right isI=1,2,3...K.
Beneficial effects of the present invention：Present invention utilizes the characteristics of field of view of continuous imaging is overlapped, based on overlay region
Domain can be converted into principle of the present image to matching result in a front images match result, and previous imaging matching result is used
In this images match process is guided, the effect for improving matching accuracy and speed has been reached.In automatic driving vehicle navigation, day
The fields such as body surface surface detector visual spatial attention can be greatly improved speed and precision, it is ensured that the navigation of view-based access control model image and control energy
Reliable, stable safe operation.
Description of the drawings
Fig. 1 is the schematic diagram of consecutive image twice in sequence three-dimensional imaging；
The left and right mesh images match process of the public domain in first time imaging of double imaging is the figure shows, wherein,The left mesh image and right mesh image of imaging for the first time are represented respectively,The point to be matched on left mesh is represented,Represent point to be matched on left mesh imageThree closest non-colinears registration point,Represent on right mesh image respectively with left figure on Corresponding use
Registration point of the same name, this 3 points also meet non-collinear condition.Represent a left side according to three affine transformations that registration point has determined
Scheme point to be matchedThe point position being transferred in right figure.
The schematic diagram of consecutive image twice in Fig. 2 sequence three-dimensional imagings；
The figure shows it is double in imaging sequences, wherein,The left mesh figure of imaging for the first time is represented respectively
Picture and right mesh image,Represent the left mesh image and right mesh image of second imaging respectively, the left mesh camera of R, T is from first
Rotation and translation matrix of the secondary imaging pose to the position and attitude change of second imaging.P is expressed as a spatial point of picture,Representation space point P is imaged the picture point on left mesh and right mesh image in first time respectively,Represent respectively
Spatial point P is in the picture point being imaged on left mesh and right mesh image for the second time.
The overlapping region of the double imagings of Fig. 3 is imaged the matching process schematic diagram of left and right mesh image at second；
The left and right mesh images match process of the public domain in second imaging of double imaging is the figure shows, wherein,The left mesh image and right mesh image of second imaging are represented respectively,The point to be matched on left mesh is represented,Represent point to be matched on left mesh imageThree closest non-colinears registration point,Represent on right mesh image respectively with left figure on It is corresponding to use same
Name registration point, this 3 points also meet non-collinear condition,Represent left figure according to three affine transformations that registration point has determined
Point to be matchedThe point position being transferred in right figure.
The Non-overlapping Domain of the double imagings of Fig. 4 is imaged the matching process schematic diagram of left and right mesh image at second；
The left and right mesh images match process of the Non-overlapping Domain in second imaging of double imaging is the figure shows, its
In,The left mesh image and right mesh image of second imaging are represented respectively,The point to be matched on left mesh is represented,Represent point to be matched on left mesh imageThree closest non-colinears registration point,Represent on right mesh image respectively with left figure onRelatively
Using registration point of the same name, this 3 points also meet non-collinear condition,Represent according to the aforementioned three affine changes that registration point determines
Left figure of changing commanders point to be matchedThe point position being transferred in right figure.
Specific embodiment
The present invention will be further described with specific embodiment below in conjunction with the accompanying drawings.
Embodiment 1
For being imaged with overlapping covered continuous stereo, overlapping region scene can in adjacent stereogram
It is imaged simultaneously, based on this, in each left and right mesh image Stereo matching of continuous stereo picture pair, according to overlapping region therein
In the matching result completed by an adjacent upper stereo pairs, and the kinematic parameter between image pair, but estimate this
Matching result of a little overlapping regions in current stereogram, believes using this estimated information as the guiding of current stereo matching
Breath, such that it is able to improve the matching efficiency and precision of stereo pairs, here it is the Stereo image matching of prior information guiding
General principle.
Specifically, in the imaging sequences of prior information guiding, left and right mesh image is can be described as to solid matching method：
The first step：Left and right mesh dense feature Point matching is carried out based on coefficient correlation to first pair of stereo-picture, which matched
Journey is described as：
Carry out feature point extraction on (1) first pair of left and right mesh stereogram respectively, obtain respective set of characteristic pointsI=1,2,3...N,I=1,2,3...M；
(2) successively to left figure point setI=1, each point in 2,3...NIn right figure seti
=1, its homonymy matching point is found in 2,3...M, determine method for select right figure on point concentrate withDistance is within the specific limits
With left figure pointPoint with maximum correlation coefficient, is defined as homonymy matching point if the coefficient correlation is more than certain threshold value.
This operation, the final of the same name registering point set for obtaining left and right figure are carried out to each pointI=1,2,
3...K；
(3) to each point in left figureThe same place determined in above-mentioned (2) step is concentratedi
=1,2, the 3...K points to left figure to be matched, in matching initial value point rangeIn, detection range withThree nearest matchings
PointDetermine that condition is：3 points are not arranged on the same straight line, and its three in right figure
Same placeAlso not on the same line；
(4) affine Transform Model of the to be matched adjacent domain between left and right figure is calculated, it is of the same name by three selected
Point resolves parameter a of affine transformation1～c2, according to affine model parameter, to each point in model area in left figure to be matchedCalculate its primary election match point in right figureComputational methods are given by：
x′R=a1xL+b1yL+c1
y′R=a2xL+b2yL+c2
(5) determine point to be matched in left figureFinal accurate same place in right figure, in the right figure more than
The point that one step is calculatedFor homonymy matching initial value point, it is optimized using least square method, is obtained final
Accurately mate pointAs shown in Figure 1；
(6) repeat above-mentioned (3)～(5) step, obtain all homonymy matching point ranges
Second step：From the beginning of second stereogram, to each matching to stereo-picture using previous to matching knot
Fruit is matched as guidance information, and the process is realized by following steps：
(7) images match of the public domain part that the centering of current picture and adjacent previous stereo pairs are overlapped is calculated,
The step by the adjacent point for being imaged public domain twice from upper one matched image to being above transferred to current image to be matched
To upper, so as to obtain the matching initial value in the region.
1) calculate the locus coordinate put on adjacent upper a pair of stereo-pictures.If upper stereogram imaging region overhead
Between point P, which in the left and right mesh image picture point of first time three-dimensional imaging is respectivelyWithCan be solved according to three-dimensional intersection empty
Between coordinate P, formula is forward intersection method, that is, solve following collinearity equation, the secondly coordinates of wherein X for spatial point P,
ML、MRThe respectively projection matrix of left and right camera.
2) calculate corresponding picture point of spatial point P in the left and right mesh image of second adjacent imagingWithCalculate public
Formula is following projection equations, and in formula, (x, y) represents picpointed coordinate, and K represents the Intrinsic Matrix of camera, and R, T represent generation respectively
Boundary's coordinate is tied to the spin matrix and translation matrix of camera coordinates system, coordinate, and (X, Y, Z) representation space point is in world coordinate system
Coordinate value.
3) repeat 1), 2) all picture points on the upper stereo-pictureIn current stereogram
Corresponding points all calculate and finish, obtain matching point rangeI=1,2,3...N.
4) according to the transfer point range for calculatingWith the membership of the left and right mesh image of current stereo-picture
Determine the matching initial value point set on present image.Determination methods are, for a certain registering same placeIn figure
If asFall within it is current as to left figure in, and, its same placeFall within it is current as to right figure in, then the point
For the public domain for overlapping, public domain provides the matching initial value of current stereo-pictureI=1,2,
3...M, as shown in Figure 2.
(8) present image pair carries out images match with the overlapping region part of last imaging
1) point to left figure to be matchedIn matching initial value point rangeIn, detection range withNearest three
With pointDetermine that condition is：3 points are not arranged on the same straight line, and its in right figure three
Individual same placeAlso not on the same line.
2) affine Transform Model of the to be matched adjacent domain between left and right figure is calculated, it is of the same name by three selected
Point resolves parameter a of affine transformation1～c2, according to affine model parameter, to each point in model area in left figure to be matchedCalculate its primary election match point in right figureComputational methods are given by：
x′R=a1xL+b1yL+c1
y′R=a2xL+b2yL+c2
3) determine point to be matched in left figureFinal accurate same place in right figure, in the right figure more than
The point that one step is calculatedFor homonymy matching initial value point, it is optimized using least square method, is obtained final
Accurately mate pointAs shown in Figure 3.
4) repetition it is above-mentioned 1)～3) step, obtain all homonymy matching point ranges
(9) images match is carried out with the Non-overlapping Domain of previous imaging in present image
1) in left figure Non-overlapping Domain point to be matchedPoint range is matchedIn, search for left figure
OnWith three closest match pointsDetermine that condition is：3 points in same
On straight line, and its three same place in right figureAlso not on the same line.
2) affine Transform Model of the to be matched adjacent domain between left and right figure is calculated, according to what is selected in (1) step
Three same places resolve parameter a of affine transformation1～c2, using affine model parameter, to every in model area in left figure to be matched
Individual pointCalculate its primary election match point in right figureComputational methods are given by：
3) determine point to be matched in left figureFinal accurate same place in right figure, method is in right figure
With the point that previous step is calculatedFor homonymy matching initial value point, it is optimized using least square method, is obtained most
Whole accurately mate pointAs shown in Figure 4.
4) repetition it is above-mentioned 1)～3) step, obtain all homonymy matching point ranges
The overlapping region of comprehensive (9th) step and above-mentioned steps 4) the Non-overlapping Domain matching result that obtains, obtain current
The final whole matching results of image.
3rd step：Using the current left and right mesh images match result being imaged as guidance information, to next adjacent view
Imaging volume picture obtains the matching result of all images of whole continuous imaging sequence to repeating (7)～(9) step all operations.
Claims (2)
1. the sequence 3 D visual image matching process that a kind of prior information is conducted, it is characterised in that comprise the steps：
Left and right mesh image dense feature Point matching is carried out to first pair of stereo-picture, its matching process is described as：
Carry out feature point extraction on (1) first pair of left and right mesh stereogram respectively, obtain respective set of characteristic points, i.e. left figure point
Set and right figure point set；
(2) successively to each point in left figure point setIts homonymy matching point is found in right figure point set, the method for determination is
Select right figure on point concentrate withDistance within the specific limits with left figure pointPoint with maximum correlation coefficient, if the phase
Relation number is then defined as homonymy matching point more than threshold value 0.75, and this operation is carried out to each point, and final acquisition left and right figure is same
The registering point set of name；The certain limit is set smaller than 30 pixels；
(3) to each point to be matched in left figureIn the point set left figure matching initial value point range of the same name that above-mentioned (2) step determinesIn, detection range withThree nearest match pointsDetermine that condition is：3 points do not exist
On same straight line, and its three same place in right figure Also not on the same line；
(4) affine Transform Model of the to be matched adjacent domain between left and right figure, three selected by above-mentioned (3) step are calculated
Individual same place resolves parameter a of affine transformation1～c2, according to affine model parameter, 3 points determined to (3) in left figure to be matched
Each point in regionCalculate its primary election match point in right figureComputational methods are by following formula
Be given；
x′R=a1xL+b1yL+c1
y′R=a2xL+b2yL+c2
(5) determine point to be matched in left figureFinal accurate same place in right figure, with previous step in right figure
The point of calculatingFor homonymy matching initial value point, it is optimized using least square method, obtains final accurate
With point
(6) repeat above-mentioned (3)～(5) step, obtain all homonymy matching point ranges
From the beginning of second stereogram, each matching to stereo-picture is believed as guiding to matching result using previous
Breath is matched, and the process is realized by following steps：
(7) images match of the public domain part that the centering of current picture and adjacent previous stereo pairs are overlapped, the step are calculated
It is rapid by the adjacent point for being imaged public domain twice from upper one matched image to being above transferred to current image to be matched to upper,
So as to obtain the matching initial value in the region, concrete mode is：
1) calculate the locus coordinate of point P on adjacent upper a pair of stereo-pictures；
2) corresponding picture point of spatial point P in the left and right mesh image of second adjacent imaging is calculated according to projection equationWith
3) repeat 1), 2) all picture points on the upper stereo-pictureCorrespondence in current stereogram
Point is all calculated and is finished, and obtains matching point range
4) according to the transfer point range for calculatingDetermine with the membership of the left and right mesh image of current stereo-picture
Matching initial value point set on present image；
(8) present image pair carries out images match with the overlapping region part of last imaging；
(9) images match is carried out with the Non-overlapping Domain of previous imaging in present image；
Left and right mesh images match result using current imaging is used as guidance information, the imaging volume picture pair to next adjacent view
Above-mentioned (7th)～(9) the step all operations of repetition, obtain the matching result of all images of whole continuous imaging sequence.
2. the sequence 3 D visual image matching process that a kind of prior information is conducted according to claim 1, it is characterised in that
The left figure point set is combined intoRight figure point set is combined intoLeft and right
Scheming registering point set of the same name is
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2192546A1 (en) * | 2008-12-01 | 2010-06-02 | Nederlandse Organisatie voor toegepast-natuurwetenschappelijk Onderzoek TNO | Method for recognizing objects in a set of images recorded by one or more cameras |
| CN102506757A (en) * | 2011-10-10 | 2012-06-20 | 南京航空航天大学 | Self-positioning method of binocular stereo measuring system in multiple-visual angle measurement |
| CN103927739A (en) * | 2014-01-10 | 2014-07-16 | 北京航天飞行控制中心 | Patroller positioning method based on spliced images |
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| US7773799B2 (en) * | 2004-04-02 | 2010-08-10 | The Boeing Company | Method for automatic stereo measurement of a point of interest in a scene |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2192546A1 (en) * | 2008-12-01 | 2010-06-02 | Nederlandse Organisatie voor toegepast-natuurwetenschappelijk Onderzoek TNO | Method for recognizing objects in a set of images recorded by one or more cameras |
| CN102506757A (en) * | 2011-10-10 | 2012-06-20 | 南京航空航天大学 | Self-positioning method of binocular stereo measuring system in multiple-visual angle measurement |
| CN103927739A (en) * | 2014-01-10 | 2014-07-16 | 北京航天飞行控制中心 | Patroller positioning method based on spliced images |
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