CN104574333B - LIDAR point cloud methods under model line constraint - Google Patents

LIDAR point cloud methods under model line constraint Download PDF

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CN104574333B
CN104574333B CN201510005364.3A CN201510005364A CN104574333B CN 104574333 B CN104574333 B CN 104574333B CN 201510005364 A CN201510005364 A CN 201510005364A CN 104574333 B CN104574333 B CN 104574333B
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straight line
model
lidar point
line
spliced
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CN104574333A (en
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盛庆红
肖晖
张斌
柳建锋
王惠南
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Suzhou Zhongketianqi Remote Sensing Technology Co ltd
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Nanjing University of Aeronautics and Astronautics
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Abstract

The present invention discloses a kind of LIDAR point cloud methods under model line constraint, belongs to Surveying Science and Technology field.Homonymous line is extracted respectively on the LIDAR point clouds of datum station and survey station to be spliced；Set up model straight line of the same name；Set up model straight line collinearity condition equation so that model straight line scaling to be spliced, rotation and translation are overlapped to benchmark model straight line；Resolve splicing parameter.The present invention carries out LIDAR point clouds using model straight line, has given full play to the geometrical constraint of straight line, can strengthen the geometry intensity of three-dimensional model, so as to improve the precision of LIDAR point clouds.

Description

LIDAR point cloud methods under model line constraint
Technical field：
LIDAR point cloud methods under model line constraint of the present invention, are related to photogrammetric technology field, belong to mapping The combination technology of technical field and image processing field.
Background technology：
LIDAR is the important means of city space acquisition of information, because city space target complexity is higher, LIDAR points Cloud collection is usually required with different view to be scanned extraterrestrial target, then neighboring stations point cloud is spliced, so as to realize To the expressed intact of extraterrestrial target.According to primitive, joining method mainly uses same place between LIDAR point clouds and of the same name Line.Complete corresponding point feature of the same name is not present between point cloud actually to be spliced, this causes same place merging features algorithm essence Degree is difficult to be guaranteed.Generally, straight line is senior geometric feature description symbol in LIDAR point clouds, relative to point, straight line With stronger geometry topological and geometrical constraint, higher splicing precision can be obtained.Joining method based on straight line primitive The general closest end points of the same name with homonymous line, then solves according to the terminal point information of line correspondence and splices parameter, but due to Complete corresponding point feature of the same name is not present between point cloud, the feature primitive used in this way is remained as a little, splices precision It is low.Therefore, the geometric topo-relationship between the linear feature and straight line of LIDAR point clouds is made full use of, to high-precision LIDAR points cloud Splicing has important actual application value.
The content of the invention：
The present invention provides a kind of LIDAR point cloud methods under model line constraint, its by datum station with it is to be spliced Homonymous line on the LIDAR point clouds of survey station respectively constitutes the topological structure of an entirety, establishes model straight line collinear condition Equation.
The present invention is adopted the following technical scheme that：A kind of LIDAR point cloud methods under model line constraint, it is included such as Lower step
Step A：Homonymous line is extracted respectively on the LIDAR point clouds of datum station and survey station to be spliced；
Step B：By the homonymous line in step A, model straight line of the same name is set up；
Step C：Set up model straight line collinearity condition equation so that model straight line to be spliced scaling, rotation and translation to Benchmark model straight line is overlapped；
Step D：Calculate splicing parameter.
Further, the method for building up of model straight line is in the step B：
Step (B-1)：Any straight line l in model straight line is obtained on the LIDAR point clouds of survey station to be spliced, by it It is expressed as：L=[the M of 0 M N O 00 N0 O0], wherein, (M, N, O) and (M0,N0,O0) be respectively l direction vector and square to Amount；
Step (B-2)：According to step (B-1) method, appointing in model straight line is obtained on the LIDAR point clouds of datum station Anticipate straight line l ', is denoted as：L '=[the M ' of 0 M ' N ' O ' 00 N′0 O′0], wherein, (M ', N ', O ') and (M '0, N′0,O′0) be respectively l ' direction vector and square vector.
Further, the step C comprises the following steps
(C-1)：Model straight line collinearity condition equation is set up, i.e., spliced model straight line and corresponding datum station LIDAR point clouds straight line is overlapped
In formula, λ is zooming parameter；I is 4 dimension unit matrixs；Q=[q1 q2 q3 q4 q01 q02 q03 q04]；0 is 4 dimensions 0 Matrix；q-1For the inverse of q；
(C-2)：It is determined that splicing initial parameter value
q1=λ=1, q2=q3=q4=q01=q02=q03=q04=0；
(C-3)：The l ' on formula (1) equation left side is moved on on the right of equation, then expansion is obtained
(C-4)：Formula (2) is expanded to first order with Taylor's formula in q and λ：
In formula：
a11=2Mq1+2Oq3-2Nq4 a12=2Mq2+2Nq3+2Oq4
a13=2Oq1+2Nq2-2Mq3 a14=-2Nq1+2Oq2-2Mq4
a15=a16=a17=a18=a19=0
a21=2Nq1-2Oq2+2Mq4 a22=-2Nq2-2Oq1+2Mq3
a23=2Nq3+2Oq4+2Mq2 a24=-2Nq4+2Oq3+2Mq1
a25=a26=a27=a28=a29=0
a31=2Oq1+2Nq2-2Mq3 a32=-2Oq2+2Nq1+2Mq4
a33=2Nq4-2Oq3-2Mq1 a34=2Oq4+2Nq3+2Mq2
a35=a36=a37=a38=a39=0
a41=2Mq01+2λM0q1-2Nq04-2λN0q4+2Oq03+2λO0q3
a42=+2Mq02+2λM0q2-2Nq03+2λN0q3+2Oq04+2λO0q4
a43=-2Mq03-2λM0q3+2Nq02+2λN0q2+2Oq01+2λO0q1
a44=-2Mq04-2λM0q4-2Nq01-2λN0q1+2Oq02+2λO0q2
a45=a11,a46=a12,a47=a13,a48=a14
a51=2Mq04+2λM0q4+2Nq01+2λN0q1-2Oq02-2λO0q2
a52=2Mq03+2λM0q3-2Nq02-2λN0q2-2Oq01-2λO0q1
a53=2Mq02+2λM0q2+2Nq03+2λN0q3+2Oq04+2λO0q4
a54=2Mq01+2λM0q1-2Nq04-2λN0q4+2Oq03+2λO0q3
a55=a21,a56=a22,a57=a23,a58=a24
a61=-2Mq03-2λM0q3+2Nq02+2λN0q2+2Oq01+2λO0q1
a62=2Mq04+2λM0q4+2Nq01+2λN0q1-2Oq02-2λO0q2
a63=-2Mq01-2λM0q1+2Nq04+2λN0q4-2Oq03-2λO0q3
a64=2Mq02+2λM0q2+2Nq03+2λN0q3+2Oq04+2λO0q4
a65=a31,a66=a32,a67=a33,a68=a34
F10,F20,F30,F40,F50,F60Respectively q and λ approximation substitutes into the F that formula (3) is obtained1~F6Approximation； dq1, dq2, dq3, dq4, dq01, dq02, dq03, dq04, d λ are respectively the correction of each splicing parameter.
The present invention has the advantages that：LIDAR point cloud methods and tradition under model line constraint of the present invention The point cloud methods of the LIDAR based on straight line compare, zooming parameter Unified Solution can have been given full play to the geometry of straight line about Shu Xing, can strengthen the geometry intensity of three-dimensional model, so as to improve the precision of LIDAR point clouds.
Embodiment：
LIDAR point cloud methods under model line constraint of the present invention comprise the following steps：
Step A：Homonymous line is extracted respectively on the LIDAR point clouds of datum station and survey station to be spliced；
Step B：By the homonymous line in step A, model straight line of the same name is set up；
Step C：Set up model straight line collinearity condition equation so that model straight line to be spliced scaling, rotation and translation to Benchmark model straight line is overlapped；
Step D：Calculate splicing parameter.
Wherein：The method for building up of model straight line is in step B：
Step (B-1)：Any straight line l in model straight line is obtained on the LIDAR point clouds of survey station to be spliced, by it It is expressed as：L=[the M of 0 M N O 00 N0 O0], wherein, (M, N, O) and (M0,N0,O0) be respectively l direction vector and square to Amount；
Step (B-2)：According to step (B-1) method, appointing in model straight line is obtained on the LIDAR point clouds of datum station Anticipate straight line l ', is denoted as：L '=[the M ' of 0 M ' N ' O ' 00 N′0 O′0], wherein, (M ', N ', O ') and (M '0, N′0,O′0) be respectively l ' direction vector and square vector.
Wherein step step C is as follows：
(C-1)：Model straight line collinearity condition equation is set up, i.e., spliced model straight line and corresponding datum station LIDAR point clouds straight line is overlapped：
In formula, λ is zooming parameter；I is 4 dimension unit matrixs；Q=[q1 q2 q3 q4 q01 q02 q03 q04]；0 is 4 dimensions 0 Matrix；q-1For the inverse of q.
(C-2)：It is determined that splicing initial parameter value.
q1=λ=1, q2=q3=q4=q01=q02=q03=q04=0.
(C-3)：The l ' on formula (1) equation left side is moved on on the right of equation, then expansion is obtained：
(C-4)：Formula (2) is expanded to first order with Taylor's formula in q and λ：
In formula：
a11=2Mq1+2Oq3-2Nq4 a12=2Mq2+2Nq3+2Oq4
a13=2Oq1+2Nq2-2Mq3 a14=-2Nq1+2Oq2-2Mq4
a15=a16=a17=a18=a19=0
a21=2Nq1-2Oq2+2Mq4 a22=-2Nq2-2Oq1+2Mq3
a23=2Nq3+2Oq4+2Mq2 a24=-2Nq4+2Oq3+2Mq1
a25=a26=a27=a28=a29=0
a31=2Oq1+2Nq2-2Mq3 a32=-2Oq2+2Nq1+2Mq4
a33=2Nq4-2Oq3-2Mq1 a34=2Oq4+2Nq3+2Mq2
a35=a36=a37=a38=a39=0
a41=2Mq01+2λM0q1-2Nq04-2λN0q4+2Oq03+2λO0q3
a42=+2Mq02+2λM0q2-2Nq03+2λN0q3+2Oq04+2λO0q4
a43=-2Mq03-2λM0q3+2Nq02+2λN0q2+2Oq01+2λO0q1
a44=-2Mq04-2λM0q4-2Nq01-2λN0q1+2Oq02+2λO0q2
a45=a11,a46=a12,a47=a13,a48=a14
a51=2Mq04+2λM0q4+2Nq01+2λN0q1-2Oq02-2λO0q2
a52=2Mq03+2λM0q3-2Nq02-2λN0q2-2Oq01-2λO0q1
a53=2Mq02+2λM0q2+2Nq03+2λN0q3+2Oq04+2λO0q4
a54=2Mq01+2λM0q1-2Nq04-2λN0q4+2Oq03+2λO0q3
a55=a21,a56=a22,a57=a23,a58=a24
a61=-2Mq03-2λM0q3+2Nq02+2λN0q2+2Oq01+2λO0q1
a62=2Mq04+2λM0q4+2Nq01+2λN0q1-2Oq02-2λO0q2
a63=-2Mq01-2λM0q1+2Nq04+2λN0q4-2Oq03-2λO0q3
a64=2Mq02+2λM0q2+2Nq03+2λN0q3+2Oq04+2λO0q4
a65=a31,a66=a32,a67=a33,a68=a34
F10,F20,F30,F40,F50,F60Respectively q and λ approximation substitutes into the F that formula (3) is obtained1~F6Approximation； dq1, dq2, dq3, dq4, dq01, dq02, dq03, dq04, d λ are respectively the correction of each splicing parameter.
(C-5)：Row write error equation and method, solve normal equation.
V=AX+F (4)
Wherein：
V=[v1,v2,v3,v4,v5,v6]T
X=[dq1 dq2 dq3 dq4 dq01 dq02 dq03 dq04 dλ]T
F=[F10 F20 F30 F40 F50 F60]T
Have n in hypothesized model straight line to homonymous line, to each pair homonymous line can one formula (4) of row error equation.
(C-6)：According to the principle of least square, obtain：
X=- (ATA)-1ATF (5)
X is the correction of splicing parameter undetermined.
(C-7)：Update splicing parameter.
It is near as new splicing parameter with the splicing parameter correction sum for splicing parameter approximation with last iteration is calculated Like value, the X=[dq obtained when solution1 dq2 dq3 dq4 dq01 dq02 dq03 dq04 dλ]TLess than setting 10-6Shi Jixu is walked Suddenly (C-7)；Otherwise return to step (C-3).
(C-8)：Calculate splicing parameter.
Final splicing parameter is substituted into below equation (6), formula (7) and formula (8), to splicing parameter.
The translation parameters formula of splicing is as follows：
The rotational transformation matrix M formula of splicing are as follows：
The rotation parameter formula of splicing is as follows：
In formula, Mi,j(i=1,2,3, j=1,2,3) representing matrix M3,3The i-th row jth row element.
Illustrate the LIDAR points cloud side under model line constraint of the present invention below by a specific embodiment Method：
Certain the building object point cloud collected according to the LMS-Z420 series of ground LIDAR devices of Austrian Riegl companies LIDAR point clouds are carried out, scanner type is pulsed, and laser emission frequency is 27000 points per second, and range is 2m- 1000m, scanning accuracy is 10mm (100 meters of distances is interior), and sweep speed is that vertical direction 1-20 lines are per second, 0.01 ° of horizontal direction ~15 ° are per second, scanning angle be 0 °~80 ° of vertical direction, 0 °~360 ° of horizontal direction, angular resolution is vertical direction 0.002 °, 0.0025 ° of horizontal direction.4 straight lines are respectively extracted from the LIDAR point clouds of datum station and survey station to be spliced respectively, Direction vector and the square vector of datum station homonymous line are as shown in table 1, the direction vector and square of survey station homonymous line subject to registration It is vectorial as shown in table 2, l1With l '1、l2With l '2、l3With l '3、l4With l '4Straight line respectively of the same name.
The survey station model straight line subject to registration of table 1
The datum station model straight line of table 2
Model straight line in Tables 1 and 2, using the joining method of the present invention, can solve splicing parameter：XS= 23.011m, YSFor 29.391m, ZSFor -2.317m,For 12.593 °, ω is 1.063 °, and κ is 28.898 °, λ=0.9998.Spell Precision is connect for 2.0mm, the requirement of high-precision three-dimensional mapping has been reached.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, some improvement can also be made under the premise without departing from the principles of the invention, and these improvement also should be regarded as the present invention's Protection domain.

Claims (2)

1. a kind of LIDAR point cloud methods under model line constraint, it is characterised in that：Comprise the following steps
Step A：Homonymous line is extracted respectively on the LIDAR point clouds of datum station and survey station to be spliced；
Step B：By the homonymous line in step A, model straight line of the same name is set up；
Step C：Set up model straight line collinearity condition equation so that model straight line scaling to be spliced, rotation and translation are arrived and benchmark Model straight line is overlapped；
Step D：Calculate splicing parameter；
The step C comprises the following steps
(C-1)：Set up model straight line collinearity condition equation, i.e., the LIDAR of spliced model straight line and corresponding datum station Point cloud straight line is overlapped：
In formula, l is any straight line in the model straight line obtained on the LIDAR point clouds of survey station to be spliced；Surveyed on the basis of l ' Any straight line in the model straight line obtained on the LIDAR point clouds stood；λ is zooming parameter；I is 4 dimension unit matrixs；Q= [q1 q2 q3 q4 q01 q02 q03 q04]；0 is 40 matrixes of dimension；q-1For the inverse of q；
(C-2)：It is determined that splicing initial parameter value
q1=λ=1, q2=q3=q4=q01=q02=q03=q04=0；
(C-3)：The l ' on formula (1) equation left side is moved on on the right of equation, then expansion is obtained
(M, N, O) and (M0, N0, O0) be respectively l direction vector and square vector；(M ', N ', O ') and (M '0, N '0, O '0) respectively Direction vector and square vector for l '；
(C-4)：Formula (2) is expanded to first order with Taylor's formula in q and λ：
In formula：
F10, F20, F30, F40, F50, F60Respectively q and λ approximation substitutes into the F that formula (3) is obtained1~F6Approximation；dq1, dq2, dq3, dq4, dq01, dq02, dq03, dq04, d λ are respectively the correction of each splicing parameter.
2. the LIDAR point cloud methods under model line constraint as claimed in claim 1, it is characterised in that：The step B The method for building up of middle model straight line is：
Step (B-1)：Any straight line l in model straight line is obtained on the LIDAR point clouds of survey station to be spliced, is represented For：L=[the M of 0 M N O 00 N0 O0], wherein, (M, N, O) and (M0, N0, O0) be respectively l direction vector and square vector；
Step (B-2)：According to step (B-1) method, obtain any one in model straight line on the LIDAR point clouds of datum station Bar straight line l ', is denoted as：L '=[the M ' of 0 M ' N ' O ' 00 N′0 O′0], wherein, (M ', N ', O ') and (M '0, N '0, O′0) be respectively l ' direction vector and square vector.
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