CN114332291B - Method for extracting outline rule of oblique photography model building - Google Patents
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Abstract
The invention provides a method for extracting outline rules of a tilt photography model building, which comprises the following steps: s1: performing straight line fitting on each point on the existing building contour line in the neighborhood of the set range, and S2: reevaluating classified points belonging to certain line segments, S3: combining two line segments with smaller distance and included angle, weighting each line segment, and setting the point of the line segment with low weight to be competitive by the line segment with high weight; s4: calculating the parallel and vertical relation between the line segments, and finely adjusting the parameters of the line segments to meet the parallel and vertical requirements; s5: and establishing a Delaunay triangle network, and reconstructing an adjacent relation between line segments. The method lays a foundation for reconstructing the three-dimensional model monomer. On one hand, the three-dimensional model monomer generated based on the regular contour lines has a more excellent visual effect; on the other hand, the monomer can be suitable for various spatial analyses, and is helpful for opening up data barriers between the oblique photogrammetry technology and the smart city.
Description
Technical Field
The invention relates to a technology of building extraction, boundary line regularization, monomerization three-dimensional model and live-action three-dimensional, in particular to a method for regenerating a three-dimensional building model boundary based on regularization.
Background
With the popularization of unmanned aerial vehicles, oblique photogrammetry technology is widely applied in the mapping industry. According to the technology, a high-precision three-dimensional model is reconstructed through a plurality of unmanned aerial vehicle aerial images by utilizing Structure of Motion (SFM) and Multi-Stereo (MVS) methods, but the generated triangular mesh model has large quantity of vertexes and high noise. On the other hand, regular building structure extraction can greatly reduce the data volume, and is convenient for management, analysis and visualization.
The triangle network model generated by direct matching of the oblique photography data has lower precision than the point cloud data acquired by directly adopting laser, and the traditional algorithm for extracting the building structure by applying laser scanning has poor effect in processing the oblique photography model.
Therefore, at present, a building monomerization model based on an oblique photography three-dimensional model is mostly produced by adopting a manual modeling mode, namely, manually collecting and editing entity boundaries, and performing geometric modeling, texture mapping and modification on the basis of an original oblique photography three-dimensional model. On the one hand, the modeling mode is low in efficiency; on the other hand, errors in artificial modeling have uncertainty, and data accuracy affects the application range of data to a great extent.
The generation of the three-dimensional model monomer is based on two-dimensional geographic entities, and in the three-dimensional building model, the building outline is the corresponding two-dimensional geographic entity. The unmanned aerial vehicle shooting is completed from top to bottom, and the visibility of the top of the building is higher than that of the bottom due to the existence of mutual shielding. Thus, the top contour of the oblique photography three-dimensional model is more accurate. However, the contour lines at any elevation have the following problems:
(1) Whether the three-dimensional model is top or bottom, the oblique photography has errors all the time, so that the accuracy of the contour line is affected, but the correction on the model is obviously unrealistic;
(2) The building should have a clear parallel vertical relationship, and its contour generation should take this element into account;
(3) The contour line is essentially a series of indiscriminate scattered points, and the regularization is essentially to split the contour line into single line segments, which are in one-to-one correspondence with the vertical surfaces in the three-dimensional model monomers.
Disclosure of Invention
The invention provides a method for extracting outline rules of a tilt photography model building, which overcomes the problems or at least partially solves the problems, takes outline lines of dense points of the building as input, and extracts line segments from the outline lines of the dense points; and regularizing all the line segments by considering the parallel and vertical relations. And finally, establishing a Delaunay triangle network taking line segment endpoints as key nodes and line segment boundaries as constraints, and reconstructing an adjacent relation between line segments to further obtain a closed and regular contour line. The method lays a foundation for reconstructing the three-dimensional model monomer. On one hand, the three-dimensional model monomer generated based on the regular contour lines has a more excellent visual effect; on the other hand, the monomer can be suitable for various spatial analyses, and is helpful for opening up data barriers between the oblique photogrammetry technology and the smart city.
According to a first aspect of the present invention, there is provided a method for extracting rules of outline of a tilt camera model building, comprising the steps of:
S1: performing straight line fitting on each point on the existing building contour line in the neighborhood of the set range, so as to obtain a plurality of groups of straight line parameters; determining possible straight lines through voting, and determining points belonging to the same straight line; judging the continuity of the points on the same straight line, dividing the straight line into a plurality of line segments, determining which points form certain line segments, and classifying the points;
S2: re-evaluating the classified points belonging to certain line segments, further adjusting the belonging relation of the classified points, and re-fitting the line segments; judging whether the unclassified points belong to certain line segments or not for the unclassified points which cannot be determined to belong to the line segments; if some points do not belong to any line segment, clustering the points according to positions, and fitting a new line segment;
S3: combining two line segments with smaller distance and included angle, weighting each line segment, and setting the point of the line segment with low weight to be competitive by the line segment with high weight;
s4: calculating the parallel and vertical relation between the line segments, and finely adjusting the parameters of the line segments to meet the parallel and vertical requirements;
S5: the Delaunay triangle network is established, and the adjacency relationship among the line segments is reconstructed, so that the outline of the polygons inside all buildings is a closed and regular building outline.
On the basis of the technical scheme, the invention can also make the following improvements.
Optionally, the step S1 includes: carrying out least square fitting on each point on the existing building contour line in a neighborhood of a certain range, converting the point into straight line parameters rho and theta under polar coordinates, voting on theta, recalculating rho through new theta, voting on rho, dividing the voting into a plurality of sections according to the value range of rho or theta, carrying out subsequent processing on the section with higher score by each point, obtaining a group of straight lines by a voting algorithm, judging whether the straight lines are continuous at each point or not by a given threshold value, and dividing the straight lines into a plurality of line segments.
Optionally, the step S2 includes: for classified points belonging to certain line segments, calculating the distance between the point and the belonging line segment and the adjacent line segment, and if the distance between the point and the adjacent line segment is smaller, changing the belonging relation of the point; for unclassified points which cannot be determined to belong to which line segment, calculating the distance from the point to an adjacent line segment, and if the distance is smaller than a given threshold value, changing the belonged relation of the point; a new line segment is re-fitted to a few points that do not belong to any line segment.
Optionally, in the step S3, if the distance and the included angle between the two line segments are smaller than the given threshold, the two line segments are considered to be combinable, the points of the two line segments are put together, and a new line segment is fitted again.
Optionally, the stability of the line segment is measured by the length of the line segment, the parallel and vertical relationship between the line segments, the fitting accuracy of the line segment, and the number of points of the line segment, and if a point of the line segment with a low weight exists in the adjacent line segment, the point is contended by the line segment with a high weight.
Optionally, the step S5 includes:
s51: establishing a Delaunay triangle network by taking end points of all line segments as vertexes, calculating the lengths of all edges in the Delaunay triangle network, calculating the median, and deleting all edges with the lengths smaller than the median;
s52: if the end points of the two line segments are connected by the edge of the triangular net, an adjacent relation is considered to exist, if the two line segments are parallel, a vertical line segment is generated to connect the parallel line segments, the newly generated line segments can be used for filling the line segments missing in the line segment extraction process, and if the two line segments are not parallel, the line segments are prolonged to be intersected, so that a closed line segment can be generated;
s53: further splitting the line segments into sub-line segments, namely, end points of other line segments do not exist on each line segment, searching the closed graph from the sub-line segments to obtain a plurality of sub-polygons and a large polygon containing all the sub-polygons;
S54: calculating the proportion of points inside the building in the internal points of each sub-polygon, and if the proportion is larger than a given threshold value, considering the polygon as a polygon inside the building;
If the area or boundary length of some polygons is small, there may be no points in the interior or few points, then it is necessary to determine by the length of their common boundary with the adjacent polygons, merge all the polygons in the interior of the building, and calculate its outline to obtain a closed and regular building contour.
The method for extracting the outline rule of the oblique photography model building provided by the invention has the following beneficial effects:
(1) The possible straight line is determined through voting of the points, the initial line segment is determined, and a series of post-processing effectively avoids the influence of wrong connection and noise of the line segment.
(2) Any two line segments can have parallel or vertical relation, and the difficulty of directly screening out unreliable relation by using a fixed threshold value is high. The main direction of the building is calculated first, and parameters of line segments are adjusted based on the main direction, so that the regularization efficiency is improved.
(3) The adjacency relation between the line segments is found through the Delaunay triangle network, and a threshold value is not required to be set manually. Even if the line segment is missing, a closed building contour can be obtained.
Drawings
Fig. 1 is a flow chart of a method for extracting outline rules of a tilt camera model building according to an embodiment of the present invention.
Detailed Description
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples. The following examples are illustrative of the invention and are not intended to limit the scope of the invention.
As shown in fig. 1, fig. 1 is a flow chart of a method for extracting outline rules of a tilt photography model building according to an embodiment of the present invention, where the method includes the following steps:
S1: performing straight line fitting on each point on the existing building contour line in the neighborhood of the set range, so as to obtain a plurality of groups of straight line parameters; determining possible straight lines through voting, and determining points belonging to the same straight line; judging the continuity of the points on the same straight line, dividing the straight line into a plurality of line segments, determining which points form certain line segments, and classifying the points;
Specifically, the least square fitting is performed on each point on the existing building contour line in a neighborhood of a certain range, the least square fitting is converted into straight line parameters rho and theta under polar coordinates, the theta is voted firstly, rho is recalculated through the new theta, then rho is voted, the voting is divided into a plurality of sections according to the value range of rho or theta, each point belongs to a certain section, the subsequent processing is performed on the section with higher score, a voting algorithm obtains a group of straight lines, a given threshold value judges whether the straight lines are continuous at each point, and the straight lines are divided into a plurality of line segments.
S2: re-evaluating the classified points belonging to certain line segments, further adjusting the belonging relation of the classified points, and re-fitting the line segments; judging whether the unclassified points belong to certain line segments or not for the unclassified points which cannot be determined to belong to the line segments; if some points do not belong to any line segment, clustering the points according to positions, and fitting a new line segment;
Specifically, for classified points belonging to certain line segments, calculating the distance from the point to the belonging line segment and the adjacent line segment, and if the distance from the point to the adjacent line segment is smaller, changing the belonging relation of the point; for unclassified points which cannot be determined to belong to which line segment, calculating the distance from the point to an adjacent line segment, and if the distance is smaller than a given threshold value, changing the belonged relation of the point; a new line segment is re-fitted to a few points that do not belong to any line segment.
S3: combining two line segments with smaller distance and included angle, weighting each line segment, and setting the point of the line segment with low weight to be competitive by the line segment with high weight;
Specifically, if the distance and the included angle of the two line segments are smaller than the given threshold, the two line segments are considered to be combinable, the points of the two line segments are put together, and a new line segment is fitted again.
S4: calculating the parallel and vertical relation between the line segments, and finely adjusting the parameters of the line segments to meet the parallel and vertical requirements;
The stability of the line segment is measured by the length of the line segment, the parallel and vertical relation between the line segments, the fitting accuracy of the line segment and the number of the points of the line segment, and if the point of the line segment with low weight exists in the adjacent line segment with better weight, the point is contended by the line segment with high weight.
S5: establishing a Delaunay triangle network, reconstructing an adjacent relation among line segments, so that the outline of polygons inside all buildings is a closed and regular building outline;
Comprising the following steps:
s51: establishing a Delaunay triangle network by taking end points of all line segments as vertexes, calculating the lengths of all edges in the Delaunay triangle network, calculating the median, and deleting all edges with the lengths smaller than the median;
s52: if the end points of the two line segments are connected by the edge of the triangular net, an adjacent relation is considered to exist, if the two line segments are parallel, a vertical line segment is generated to connect the parallel line segments, the newly generated line segments can be used for filling the line segments missing in the line segment extraction process, and if the two line segments are not parallel, the line segments are prolonged to be intersected, so that a closed line segment can be generated;
s53: further splitting the line segments into sub-line segments, namely, end points of other line segments do not exist on each line segment, searching the closed graph from the sub-line segments to obtain a plurality of sub-polygons and a large polygon containing all the sub-polygons;
S54: calculating the proportion of points inside the building in the internal points of each sub-polygon, and if the proportion is larger than a given threshold value, considering the polygon as a polygon inside the building;
If the area or boundary length of some polygons is small, there may be no points in the interior or few points, then it is necessary to determine by the length of their common boundary with the adjacent polygons, merge all the polygons in the interior of the building, and calculate its outline to obtain a closed and regular building contour.
It can be understood that, in this embodiment, a series of building boundary line segments are obtained by using the dense point contour lines of the existing building as input and using a dense point extraction algorithm with a certain topological relation. And according to the internal parallel and vertical relations of the building, the angles of the initial boundary line segments are adjusted, the adjacent relation between the line segments is established, and the uncertain line segments are eliminated through strategies such as competition combination, so that a closed and regular building contour line is obtained.
In one possible embodiment, the embodiment can be divided into the following three processes:
The line segment extraction process comprises the following steps:
(1) And carrying out least square fitting on each point on the existing building contour line in a neighborhood of a certain range, and converting the least square fitting into linear parameters rho and theta under polar coordinates. Voting is carried out on theta, rho is recalculated through new theta, and then voting is carried out on rho. The voting is to divide the voting into a plurality of sections according to the value range of rho or theta, each point belongs to a certain section, and the section with higher score is subjected to subsequent processing. A group of straight lines can be obtained through the voting algorithm, a given threshold value is used for judging whether the straight lines are continuous at each point, and the straight lines can be divided into a plurality of line segments.
(2) For classified points belonging to certain line segments, the distance between the point and the belonging line segment and the adjacent line segment is calculated, and if the distance between the point and the adjacent line segment is smaller, the belonging relation of the point is changed. For unclassified points which cannot be determined to belong to which line segment, the distance from the point to the adjacent line segment is calculated, and if the distance is smaller than a given threshold value, the belonged relation of the point is changed. For a few points that do not belong to any line segment, these points either belong to a very fine line segment. For these clusters of points, each class can be re-fitted with a new line segment.
(3) If the distance and the included angle of the two line segments are smaller than the given threshold value, the two line segments are considered to be combinable. The points of the two line segments are put together and a new line segment is re-fitted.
(4) Four parameters were used: the stability of the line segments is measured by the length of the line segments, the parallel and vertical relationship between the line segments, the fitting accuracy of the line segments and the number of points of the line segments. For a point of a low weight line segment, if there is a better weighted line segment in its neighborhood, the point is contended for the past by a high weight line segment.
Regularization process:
(1) The angles of most line segments are in parallel or perpendicular relation to the main direction of the building, in other words, knowing the angles of all line segments, the optimal main direction can be calculated. The degree of stability of the line segments should also be taken into account when calculating the main direction, i.e. a more stable line segment should make a greater contribution to the determination of the main direction.
(2) After the principal direction is calculated, a given threshold value determines whether each line segment is parallel or perpendicular to the principal direction. After the line segments related to the main direction are screened out, the main direction is recalculated, and then the parameters of the line segments are adjusted.
Closing:
(1) And establishing a Delaunay triangle network by taking the end points of all the line segments as vertexes. And calculating the lengths of all edges in the triangular net, calculating the median, and deleting all edges with the lengths smaller than the median.
(2) An adjacency is considered to exist if the end points of the two line segments are connected by an edge of the triangle mesh. If the two line segments are parallel, a vertical line segment is generated to connect the parallel line segments. The newly generated line segment can be used for filling the missing line segment in the line segment extraction process. If the two line segments are not parallel, the line segments are lengthened to meet. Thereby, a closed line segment can be generated.
(3) The line segments are further split into sub-line segments, i.e. no end points of other line segments are present on each line segment. The closed figure is searched from the sub-line segments, several sub-polygons are obtained, and one large polygon containing all the sub-polygons.
(4) For each sub-polygon, the proportion of points inside the building among the points inside the sub-polygon is calculated. If greater than a given threshold, the polygon is considered to be a polygon inside the building. If the area or boundary length of some polygons is small, there may be no points inside, or few points, then a determination is made by the length of their common boundary with the adjacent polygon. And merging polygons inside all buildings, and calculating the outline of the polygons to obtain a closed and regular building outline.
In the foregoing embodiments, the descriptions of the embodiments are focused on, and for those portions of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. The method for extracting the outline rule of the oblique photography model building is characterized by comprising the following steps of:
S1: performing straight line fitting on each point on the existing building contour line in the neighborhood of the set range, so as to obtain a plurality of groups of straight line parameters; determining possible straight lines through voting, and determining points belonging to the same straight line; judging the continuity of the points on the same straight line, dividing the straight line into a plurality of line segments, determining which points form certain line segments, and classifying the points;
S2: re-evaluating the classified points belonging to certain line segments, further adjusting the belonging relation of the classified points, and re-fitting the line segments; judging whether the unclassified points belong to certain line segments or not for the unclassified points which cannot be determined to belong to the line segments; if some points do not belong to any line segment, clustering the points according to positions, and fitting a new line segment;
S3: combining two line segments with smaller distance and included angle, weighting each line segment, and setting the point of the line segment with low weight to be competitive by the line segment with high weight;
s4: calculating the parallel and vertical relation between the line segments, and finely adjusting the parameters of the line segments to meet the parallel and vertical requirements;
S5: the Delaunay triangle network is established, and the adjacency relationship among the line segments is reconstructed, so that the outline of the polygons inside all buildings is a closed and regular building outline.
2. The method for extracting the outline rule of the oblique photography model building according to claim 1, wherein the step S1 comprises: carrying out least square fitting on each point on the existing building contour line in a neighborhood of a certain range, converting the point into straight line parameters rho and theta under polar coordinates, voting on theta, recalculating rho through new theta, voting on rho, dividing the voting into a plurality of sections according to the value range of rho or theta, carrying out subsequent processing on the section with higher score by each point, obtaining a group of straight lines by a voting algorithm, judging whether the straight lines are continuous at each point or not by a given threshold value, and dividing the straight lines into a plurality of line segments.
3. The method for extracting the outline rule of the oblique photography model building according to claim 1, wherein the step S2 comprises: for classified points belonging to certain line segments, calculating the distance between the point and the belonging line segment and the adjacent line segment, and if the distance between the point and the adjacent line segment is smaller, changing the belonging relation of the point; for unclassified points which cannot be determined to belong to which line segment, calculating the distance from the point to an adjacent line segment, and if the distance is smaller than a given threshold value, changing the belonged relation of the point; a new line segment is re-fitted to a few points that do not belong to any line segment.
4. The method according to claim 1, wherein in the step S3, if the distance and the included angle between the two line segments are smaller than the given threshold, the two line segments are considered to be combinable, the points of the two line segments are put together, and a new line segment is fitted again.
5. The method for extracting the outline rule of a tilt camera model building according to claim 4, wherein the stability of the line segment is measured by the length of the line segment, the parallel and vertical relationship between the line segments, the fitting accuracy of the line segment, and the number of points of the line segment, and for a point of a low weight line segment, if a line segment with better weight exists in its neighboring line segments, the point is contended for the past by a line segment with higher weight.
6. The method for extracting the outline rule of the oblique photography model building according to claim 1, wherein the step S5 comprises:
s51: establishing a Delaunay triangle network by taking end points of all line segments as vertexes, calculating the lengths of all edges in the Delaunay triangle network, calculating the median, and deleting all edges with the lengths smaller than the median;
s52: if the end points of the two line segments are connected by the edge of the triangular net, an adjacent relation is considered to exist, if the two line segments are parallel, a vertical line segment is generated to connect the parallel line segments, the newly generated line segments can be used for filling the line segments missing in the line segment extraction process, and if the two line segments are not parallel, the line segments are prolonged to be intersected, so that a closed line segment can be generated;
s53: further splitting the line segments into sub-line segments, namely, end points of other line segments do not exist on each line segment, searching the closed graph from the sub-line segments to obtain a plurality of sub-polygons and a large polygon containing all the sub-polygons;
S54: calculating the proportion of points inside the building in the internal points of each sub-polygon, and if the proportion is larger than a given threshold value, considering the polygon as a polygon inside the building;
If the area or boundary length of some polygons is small, there may be no points in the interior or few points, then it is necessary to determine by the length of their common boundary with the adjacent polygons, merge all the polygons in the interior of the building, and calculate its outline to obtain a closed and regular building contour.
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