CN107610228A - Curved surface increment topology rebuilding method based on massive point cloud - Google Patents
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Abstract
It is an object of the invention to provide a kind of curved surface increment topology rebuilding method based on massive point cloud, belong to product reverse-engineering field, using the strategy of wavefront expansion, pass through the steps such as the expansion of wavefront ring, division, the elimination of overlapping dough sheet, partial reconstruction process is propagated to the adjacent domain of each sampling point, interpolation is obtained in the two-dimentional oriented manifold grid surface of sampling point set, realizes the increment topology rebuilding of whole sampling point set；During curved surface partial reconstruction; the Delaunay grid cutting algorithms of the Cocone algorithms and two-dimensional projection's point set that are based respectively on regional area rebuild the sharpened areas and flat site of curved surface, and wherein regional area rebuilds the correctness on the border of surface mesh by a small amount of auxiliary sampling point protection outside region.This method has higher reconstruction efficiency, suitable for closing the reconstruction with non-close mass cloud data, and in the case where sampling density meets the requirements, grid surface and the original surface topological isomorphism of reconstruction.
Description
Technical field
The present invention provides a kind of curved surface increment topology rebuilding method based on massive point cloud, available for rebuilding large-scale point cloud
Data, belong to product reverse-engineering field.
Background technology
Curve reestablishing technology is widely used in the fields such as reverse-engineering, medical image and virtual reality, particularly in automobile
In the industrial processes such as manufacture, Aero-Space, the reconstruction precision on complicated surface in kind will directly affect the production of final products
Quality.The development of three-dimensional scanning device so that the intensive cloud data for obtaining reflection object minutia becomes a reality, but these
The usual data volume of sampling point set is big and topology information lacks, for example, scattered point cloud data obtained by laser scanner up to million grades very
To hundred million grades.How the mass cloud data obtained using scanning efficiently rebuilds high-precision original surface, recovers its topological adjacency
Relation, the hot issue studied both at home and abroad always is in recent years.
Existing curve reestablishing method is broadly divided into based on implicit surface approximating method, incremental expansion method and Delaunay nets
Lattice filter method.Implicit surface approximating method mainly has the zero of the propositions such as Hoppe by using implicit surface fitting data point
Contour surface method, the Poisson algorithm for reconstructing proposed on the basis of zero contour surface method, and the radial direction base of global implicit surface fitting
Function method.The method of implicit surface fitting has the key property that can be fused into smooth surface automatically, and continuity and morphotropism
It is good, suitable for describing the object with smooth complex appearance.But such algorithm obtains grid surface in a manner of approaching sampling point set,
It is difficult to retain the characteristic information of object and is not suitable for the reconstruction of non-close curved surface.
The general principle of incremental expansion method is：A seed triangle is constructed first, it is then continuous according to certain criterion
The new point of selection is added to construct new triangle and update wavefront ring, and triangle grows and finished at the end of traveling through a little, just
The triangle gridding for approaching original surface can be obtained after the optimization of beginning subdivision.The key of such algorithm is new point addition rule really
Fixed, main representative has Ball Pivoting methods and G2S criterions.Incremental expansion class algorithm Space-time Complexity is low, can handle big
Scale cloud data, but higher is required to sampling condition, the characteristic area or sampling changed greatly in seamed edge iso-curvature is uneven
Easily there is hole and long and narrow tri patch etc. in even place.
Amenta et al. be based on Delaunay Triangulation and its antithesis Voronoi diagram successively propose Crust algorithms and
Cocone algorithms, and prove that both algorithms reconstructed results and original surface topology under conditions of smooth surface sampling is met are same
Structure, and converge to original surface with the increase output result of sampling density.Crust algorithms and Cocone algorithm reconstructed results
Correctness has theoretical guarantee, but high based on global Delaunay Triangulation Space-time Complexity, it is difficult to rebuilds large-scale point
Cloud data.Dey etc. then exists《Localized Cocone surface reconstruction》(Computers&
Graphics, 2011,35 (3)：A kind of Localized based on localized Delaunay triangulation is proposed in 483-491)
Cocone algorithms.The algorithm is split using Octree to sampling point set, and the sample then included to each child node should
Rebuild with Cocone algorithms, the processing to fairly large cloud data can be achieved.But split to sampling point set is rough
To child node in a large amount of cloud datas for including, its Cocone process of reconstruction is still quite time-consuming, limits whole body reconstruction efficiency
Lifting.
The content of the invention
It is an object of the invention to provide a kind of curved surface increment topology rebuilding method based on massive point cloud, takes into account reconstruction effect
Rate is with rebuilding curved surface topology accuracy.Its technical scheme is：
A kind of curved surface increment topology rebuilding method based on massive point cloud, it is characterised in that step is followed successively by：(1) R* tree structures are utilized
Build input point set S spatial index and be free point by sampling point state initialization in S.(2) it is maximum to choose x coordinate value in point set S
Sampling point p0As initial point.(3) p is asked for0Fractional sample λ (p0) and partial reconstruction is carried out to the sample, obtain original reconstruction
Grid D (λ (p0)).(4) D (λ (p are extracted0)) wavefront ring and by it to λ (p0) least square fitting tangent plane projection.Adjust
Whole subpoint connection order is allowed to and p0Normal direction meet right-handed helix criterion, and then determine wavefront ring ring, and by D (λ
(p0)) be added to and rebuild in patch grids set Q.(5) wavefront loop chain table is traveled through, obtains the wavefront of first non-border sampling point mark
Point pr.If prIt is not present, performs (9), otherwise performs (6).(6) p is asked forrK neighborhood point sets, rejecting be wherein labeled as saturation point
Sampling point.If remaining point set is sky, by prLabeled as boundary point, perform (8)；Otherwise remaining point set is expanded and will be expanded
Point set is as wavefront fractional sample λ (p after increasingr).(7) to λ (pr) partial reconstruction is carried out, by the wave-front reconstruction grid D (λ of acquisition
(pr)) be added in Q, wavefront ring is then updated according to the expansion of document [8] medium wave front ring, splitting method.(8) (5) are repeated extremely
(7).(9) counterweight builds patch grids set Q and carries out normal direction unification processing, and curve reestablishing is completed.
The described curved surface increment topology rebuilding algorithm based on massive point cloud, it is characterised in that fractional sample in step (3)
The process of asking for is：(1) first k is carried out to sampling point pηNeighborhood search, gained neighbour's point set is as initial local sample λ (p). (2)
K is carried out to p againζNeighborhood search, obtain(3) any point is extractedIfThen λ (p) ← λ
(p)∪{pi}.Partial reconstruction is carried out to fractional sample to concretely comprise the following steps：(1) λ (p) reference planes F is built.(2) λ is calculated
(p) in sampling point to reference planes F distances root mean squareN is sampling point quantity in λ (p).If dRMSLess than threshold
It value ω, then can determine that λ (p) is coplanar, perform (3)；Otherwise (4) are performed.(3) λ (p) is projected to plane F, projection point set is carried out
Two-dimentional Delaunay subdivisions, and determine that annexation, output are cutd open between each sampling point in original fractional sample λ (p) according to subdivision result
The partial reconstruction grid divided, partial reconstruction are completed.(4) three-dimensional Delaunay subdivisions are carried out to λ (p), obtains tri patch set
D (λ (p)) simultaneously obtains corresponding Voronoi diagram V (λ (p)).(5) to each sampling point in λ (p), Voronoi where it is obtained
Limit in unit, the vector n of sampling point to limitpNormal vector as the point.(6) to any dough sheet T in D (λ (p))iCarry out
Cocone is detected, if detection is not by by TiDeleted from D (λ (p)), otherwise without any operation.(7) to passing through inspection
The tri patch set D (λ (p)) looked into, make further manifold extraction, and export partial reconstruction grid, partial reconstruction is completed.
In above-mentioned steps (6), to dough sheet TiCocone detection algorithms it is as follows：(1) T is detectediWith the presence or absence of auxiliary in summit
Help a little, if in the presence of the dough sheet does not pass through detection, EP (end of program).Otherwise step (2) is performed.(2) dough sheet T is obtainediAntithesis
The end points v on Voronoi sides1、v2.To any summit pj, solve vectorial pjv1And pjv2With pjThe normal direction n of plane where pointpjFolder
Angle θ1And θ2, wherein θ1←∠(pjv1,npj), θ2←∠(pjv2,npj).(3) θ is calculated1And θ2With point pjCocone regions
Whether occur simultaneously is empty.If TiAny summit result of calculation is not sky, then the dough sheet is detected by Cocone, otherwise TiDo not pass through.
When building reference planes F to λ (p), if λ (p) is the fractional sample obtained first, F can take the sample by appointing
In not conllinear 3 points determine, otherwise F is built according to the specific sampling point p and its normal direction for obtaining the sample.
The present invention compared with prior art, has advantages below：
(1) the curved surface regional area by finely dividing is rebuild using classical Cocone algorithms and projection subdivision algorithm, and be based on
Wavefront expansion algorithm realizes that the increment of whole sampling point set is rebuild, and finally gives two-dimentional oriented manifold grid.In partial reconstruction mistake
The Delaunay mesh generation results of a small amount of local sampling point are relied only in journey.Avoid global three-dimensional Delaunay mesh generations band
The high complexity issue come, significantly improves reconstruction efficiency, suitable for the processing of mass cloud data；
(2) during incremental expansion, curved surface is that the modes such as the expansion based on partial reconstruction and wavefront ring, division progressively extend
Reconstruction forms, and point cloud boundary region sampling point can be realized and preferably rebuild effect, is applicable to rebuild closing and non-close is bent
Face；
(3) by kη、kζReasonable value is able to ensure that in fractional sample that any sampling point is respectively provided with complete Voronoi adjoint points,
So that the correctness of partial reconstruction result is ensured, overlapping dough sheet is then eliminated during incremental expansion, realization is entirely adopted
The correct reconstruction of sampling point collection.When point set S is sampled in a smooth surface Σ, sampling density meets ε-sampling sampling requests
When, this paper algorithms rebuild grid Q topological isomorphisms in original surface Σ.
Brief description of the drawings
Fig. 1 is the program implementation process figure of the curved surface increment topology rebuilding method of the invention based on massive point cloud；
Fig. 2 is sampling point Voronoi neighborhoods point set and k neighborhood point set schematic diagram in kind；
Fig. 3 is partial reconstruction schematic diagram；
Fig. 4 is a cloud incremental expansion process schematic；
Fig. 5 is Venus sampled datas in embodiment one；
Fig. 6 is that Venus sampled datas rebuild design sketch in embodiment one；
Fig. 7 is Happy Buddha sampled datas in embodiment two；
Fig. 8 is that Happy Buddha sampled datas rebuild design sketch in embodiment two.
Embodiment
Below in conjunction with the accompanying drawings and embodiment the invention will be further described.
Fig. 1 is the curved surface increment topology rebuilding method program implementation process figure of the invention based on massive point cloud, according to curved surface
Local flat degree, the curved surface regional area finely divided, and base are rebuild using classical Cocone algorithms and projection subdivision algorithm
The partial reconstruction process is extended into whole sampling point set in wavefront expansion algorithm, eliminates overlapping dough sheet in this course, most
Interpolation is obtained eventually in the two-dimentional oriented manifold grid of sampling point set.
If sampling point set is S, fractional sample λ (p) is S a subset, after carrying out Delaunay Triangulation to λ (p)
The partial reconstruction dough sheet collection of acquisition is combined into D (λ (p)).For any point p in partial reconstruction sample λ (p), it is in S
Voronoi neighborhoods point set is NV(p), k neighborhoods point set is Nk(p).Point p NV(p) it is difficult to directly obtain, but for uniform sampling
Point set, can suitably choose k values so thatAs shown in Figure 2.When p is located at λ (p) local boundary region,
Its k neighborhoods point is concentratedAnd q ∈ Nk(p),To ensure to carry out any point p in Cocone process of reconstruction to λ (p)
Normal direction can correctly estimate, need to original fractional sample λ (p) border sampling point moderately expand.λ (p) will be expanded herein
And the sampling point added is referred to as auxiliary magnet.During partial reconstruction, to make the normal direction of each sampling point in λ (p) correctly to estimate
Meter, need to ensure forIts Nk(p) it is present in the fractional sample after amplification.By specific sampling point p k neighborhoods point
Collection is used as fractional sample λ (p), and the addition of its auxiliary magnet can be by expanding to realize to the appropriateness of p neighborhood point sets hunting zone.If
kηRequired neighborhood point set quantity, k during to obtain λ (p)ζFor field point set quantity in auxiliary magnet adding procedure, fractional sample amplification
Idiographic flow it is as follows：(1) first k is carried out to sampling point pηNeighborhood search, gained neighbour's point set is as initial local sample λ (p).
(2) k is carried out to p againζNeighborhood search, obtain(3) any point is extractedIfThen λ (p) ←
λ(p)∪{pi}。
After the fractional sample for obtaining amplification, to carry out partial reconstruction, Delaunay Triangulation is carried out to the sample first,
And only retain the dough sheet that three summits are free of auxiliary magnet in Cocone detecting steps, it can obtain satisfactory Cocone triangles
Dough sheet set, it is the two-dimentional oriented manifold grid of exportable part that manifold extraction operation is then carried out to dough sheet set.
But during partial reconstruction, the fractional sample of acquisition is likely to occur coplanar situation, i.e. space three-dimensional point set
The sampling point on two dimensional surface is deteriorated to, leads to not carry out the calculating of Voronoi limits to fractional sample and Cocone is rebuild.This
When, reconstructed results can be obtained by the way of subdivision is projected to the partial points collection.Therefore, for fractional sample λ (p), its part
It is as follows to rebuild flow：(1) λ (p) reference planes F is built.(2) sampling point is calculated in λ (p) to the root mean square of reference planes F distancesN is sampling point quantity in λ (p).If dRMSIt less than threshold value ω, then can determine that λ (p) is coplanar, perform (3)；It is no
Then perform (4).(3) λ (p) is projected to plane F, two-dimentional Delaunay subdivisions is carried out to projection point set, and according to subdivision result
Annexation between each sampling point is determined in original fractional sample λ (p), exports the partial reconstruction grid of subdivision, partial reconstruction is completed.
(4) three-dimensional Delaunay subdivisions are carried out to λ (p), obtains tri patch set D (λ (p)) and obtain corresponding Voronoi diagram V (λ
(p)).(5) to each sampling point in λ (p), the limit in Voronoi units where obtaining it, the vector n of sampling point to limitp
Normal vector as the point.(6) to any dough sheet T in D (λ (p))iCocone detections are carried out, if detection is not by by TiFrom D
Deleted in (λ (p)), otherwise without any operation.(7) to the tri patch set D (λ (p)) by inspection, make further
Manifold is extracted, and exports partial reconstruction grid, and partial reconstruction is completed.
In above-mentioned steps (6), to dough sheet TiCocone detection algorithms concretely comprise the following steps：(1) T is detectediIn summit whether
Auxiliary magnet be present, if in the presence of the dough sheet does not pass through detection, EP (end of program).Otherwise step (2) is performed.(2) dough sheet T is obtainediIt is right
The end points v on even Voronoi sides1、v2.To any summit pj, solve vectorial pjv1And pjv2With pjThe normal direction n of plane where pointpj's
Angle theta1And θ2, wherein θ1←∠(pjv1,npj),θ2←∠(pjv2,npj).(3) θ is calculated1And θ2With point pjCocone regions
Common factor whether be empty.If TiAny summit result of calculation is not sky, then the dough sheet is detected by Cocone, otherwise TiDo not lead to
Cross.Fractional sample λ (p) partial reconstruction effect is as shown in Figure 3.
The correctness of partial reconstruction result is ensure that based on auxiliary magnet addition, can increment by the expansion and division of wavefront ring
Rebuild whole sampling point set.It is the sampling point in filtering reconstruction regions in increment process of reconstruction, rower need to be entered to sampling point state
Note.Difference in stage according to residing for sampling point during this, saturation point, free point, wavefront point and boundary point can be classified as, wherein
Free point is the sampling point of non-reconstruction regions, and saturation point is the sampling point in reconstruction regions.Extraction reconstruction regions border as ripple
Front ring, using the point on wavefront ring as wavefront point.When wavefront ring, which expands to, rebuilds surface boundary, wavefront point is converted into border
Point.In addition, for mass cloud data, efficiency is obtained for lifting fractional sample, R* trees can be used as spatial index.To sum up institute
State, the entire flow of curved surface increment topology rebuilding algorithm is as follows：(1) point set S spatial index is inputted and by S using R* trees structure
Middle sampling point state initialization is free point.(2) the sampling point p that x coordinate value is maximum in point set S is chosen0As initial point.(3) ask for
p0Fractional sample λ (p0) and partial reconstruction is carried out to the sample, obtain original reconstruction grid D (λ (p0)).(4) D (λ are extracted
(p0)) wavefront ring and by it to λ (p0) least square fitting tangent plane projection.Adjustment subpoint connection order be allowed to
p0Normal direction meet right-handed helix criterion, and then determine wavefront ring ring, and by D (λ (p0)) be added to and rebuild patch grids set
In Q.(5) wavefront loop chain table is traveled through, obtains the wavefront point p of first non-border sampling point markr.If prIt is not present, performs (9) otherwise
Perform (6).(6) p is asked forrK neighborhood point sets, reject wherein be labeled as saturation point sampling point.If remaining point set is sky, by pr
Labeled as boundary point, perform (8)；Otherwise point set is as wavefront fractional sample λ after being expanded and being expanded to remaining point set
(pr).(7) to λ (pr) partial reconstruction is carried out, by the wave-front reconstruction grid D (λ (p of acquisitionr)) be added in Q, then according to document
[8] expansion of medium wave front ring, splitting method renewal wavefront ring.(8) (5) to (7) are repeated.(9) counterweight builds patch grids set Q
Normal direction unification processing is carried out, curve reestablishing is completed.
As shown in figure 4, in increment process of reconstruction, the Local grid of wavefront expansion generation can be complete with reconstruction regions grid
Whole splicing so that final grid surface is still two-dimensional manifold structure.
Major parameter has ω, k needed for context of methodsηWithWherein ω is the floating-point house in the coplanar detection process of fractional sample
Enter error, should be determined based on specifically used data type and algorithm running environment.Parameter kη,It can be selected according to a cloud density
Take.The point cloud model being evenly distributed for sampling density, it is proposed that kηWithValue is 25 and 40 respectively, and non-for sampling density
Equally distributed point cloud model, it can suitably increase partial reconstruction sample size, it is proposed that kηWithValue is 35 and 55 respectively.
Embodiment one：To Venus point cloud models shown in Fig. 5, curved surface increment topology rebuilding is carried out using methods described herein.
Fig. 5 models are non-close point cloud, and Fig. 6 is that context of methods rebuilds effect.By observing Fig. 6, context of methods can be weighed preferably
Borderline region is built, suitable for the reconstruction of non-close curved surface.
Embodiment two：To the models of Happy Buddha shown in Fig. 7, curved surface increment topology weight is carried out using methods described herein
Build.Fig. 7 institutes representation model is enclosed point cloud, but sampling point skewness region and Curvature varying large area be present.Fig. 8 is herein
Method rebuilds effect.By observing Fig. 8, sharp features region and sampling point skewness region can be correctly rebuild herein.
The above described is only a preferred embodiment of the present invention, being not the limitation for making other forms to the present invention, appoint
What those skilled in the art changed or be modified as possibly also with the technology contents of the disclosure above equivalent variations etc.
Imitate embodiment.But it is every without departing from technical solution of the present invention content, the technical spirit according to the present invention is to above example institute
Any simple modification, equivalent variations and the remodeling made, still fall within the protection domain of technical solution of the present invention.
Claims (3)
1. a kind of curved surface increment topology rebuilding method based on massive point cloud, it is characterised in that step is followed successively by：(1) R* is utilized
Tree structure inputs point set S spatial index and is free point by sampling point state initialization in S；(2) x coordinate value in point set S is chosen
Maximum sampling point p0As initial point；(3) p is asked for0Fractional sample λ (p0) and partial reconstruction is carried out to the sample, obtain initial
Rebuild grid D (λ (p0))；(4) D (λ (p are extracted0)) wavefront ring and by it to λ (p0) least square fitting tangent plane throw
Shadow, adjustment subpoint connection order is allowed to and p0Normal direction meet right-handed helix criterion, and then determine wavefront ring ring, and by D
(λ(p0)) be added to and rebuild in patch grids set Q；(5) wavefront loop chain table is traveled through, obtains the ripple of first non-border sampling point mark
Preceding point prIf prIt is not present, performs (9), otherwise performs (6)；(6) p is asked forrK neighborhood point sets, rejecting be wherein labeled as saturation
The sampling point of point, if remaining point set is sky, by prLabeled as boundary point, perform (8)；Otherwise remaining point set is expanded and incited somebody to action
Point set is as wavefront fractional sample λ (p after amplificationr)；(7) to λ (pr) partial reconstruction is carried out, by the wave-front reconstruction grid D (λ of acquisition
(pr)) be added in Q, wavefront ring is then updated according to the expansion of document [8] medium wave front ring, splitting method；(8) (5) are repeated extremely
(7)；(9) counterweight builds patch grids set Q and carries out normal direction unification processing, and curve reestablishing is completed.
2. the curved surface increment topology rebuilding method according to claim 1 based on massive point cloud, it is characterised in that：In step
(3) in, fractional sample needs to add auxiliary magnet during asking for, and specific method is：(1) first k is carried out to sampling point pηNeighborhood search,
Gained neighbour's point set is as initial local sample λ (p)；(2) k is carried out to p againζNeighborhood search, obtain(3) extract
Any pointIfThen λ (p) ← λ (p) ∪ { pi}；In above-mentioned fractional sample amplification procedure, it is added to
Sampling point in λ (p) is auxiliary magnet.
3. the curved surface increment topology rebuilding method according to claim 1 based on massive point cloud, it is characterised in that step (3)
In, it is right respectively from three-dimensional Delaunay mesh generation algorithms and two-dimensional projection's subdivision algorithm according to curved surface local flat degree
The smooth region of sharp features regional peace carries out partial reconstruction, and specific method is：(1) λ (p) reference planes F is built；(2) λ is calculated
(p) in sampling point to reference planes F distances root mean squareN is sampling point quantity in λ (p), if dRMSLess than threshold
It value ω, then can determine that λ (p) is coplanar, perform (3)；Otherwise (4) are performed；(3) λ (p) is projected to plane F, projection point set is carried out
Two-dimentional Delaunay subdivisions, and determine that annexation, output are cutd open between each sampling point in original fractional sample λ (p) according to subdivision result
The partial reconstruction grid divided, partial reconstruction are completed；(4) three-dimensional Delaunay subdivisions are carried out to λ (p), obtains tri patch set D
(λ (p)) and obtain corresponding Voronoi diagram V (λ (p))；(5) to each sampling point in λ (p), Voronoi where it is obtained
Limit in unit, the vector n of sampling point to limitpNormal vector as the point；(6) to any dough sheet T in D (λ (p))iCarry out
Cocone is detected, if detection is not by by TiDeleted from D (λ (p)), otherwise without any operation；(7) to passing through inspection
The tri patch set D (λ (p)) looked into, make further manifold extraction, and export partial reconstruction grid, partial reconstruction is completed；
In step (6), to dough sheet TiCocone detection algorithms it is as follows：(1) T is detectediIt whether there is auxiliary magnet in summit, if in the presence of,
The dough sheet by detection, EP (end of program), does not otherwise perform step (2)；(2) dough sheet T is obtainediThe end points v on antithesis Voronoi sides1、
v2, to any summit pj, solve vectorial pjv1And pjv2With point pjThe normal direction n of place planepjAngle theta1And θ2, wherein θ1←∠
(pjv1,npj), θ2←∠(pjv2,npj)；(3) θ is calculated1And θ2With point pjThe common factor in Cocone regions whether be empty, if TiAppoint
One summit result of calculation is not sky, then the dough sheet is detected by Cocone, otherwise TiDo not pass through；Reference planes are built to λ (p)
During F, if λ (p) is the fractional sample obtained first, F can take not conllinear in the sample 3 points to determine by appointing, otherwise root
F is built according to the specific sampling point p and its normal direction that obtain the sample.
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| CN108898673A (en) * | 2018-06-13 | 2018-11-27 | 东莞时谛智能科技有限公司 | A kind of reconstruct foot triangle grid model processing method and system |
| CN108876834A (en) * | 2018-06-19 | 2018-11-23 | 山东理工大学 | The curved surface sample normal direction transmission method of multilayer Riemann's constraint diagram |
| CN109636913A (en) * | 2018-12-04 | 2019-04-16 | 山东理工大学 | Triangle gridding increment topology joining method based on Delaunay subdivision |
| CN110021041A (en) * | 2019-03-01 | 2019-07-16 | 浙江大学 | Unmanned scene progressive mesh structural remodeling method based on binocular camera |
| CN112669463A (en) * | 2020-12-25 | 2021-04-16 | 河南信大融通信息科技有限公司 | Method for reconstructing curved surface of three-dimensional point cloud, computer device and computer-readable storage medium |
| CN112669463B (en) * | 2020-12-25 | 2022-02-15 | 河南信大融通信息科技有限公司 | Method for reconstructing curved surface of three-dimensional point cloud, computer device and computer-readable storage medium |
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