Point cloud section data sorting method, device, electronic device and storage medium

Abstract

The present invention provides a data sorting method, device, electronic device and storage medium for a point cloud section. The data sorting method for a point cloud section includes: roughly sorting the data points in a single contour area on the point cloud section to obtain a single contour convex hull; on the single contour convex hull, selecting a convex hull edge that meets the target length as the target convex hull edge, and based on the target convex hull edge, selecting a new convex hull point from the remaining points; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section; inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge; based on the contour distance threshold, selecting data points from the pending data points to form a new point set, and outputting the new point set for sorting; wherein the pending data points are the data points remaining after the new convex hull points are removed from the remaining points. The data sorting method, device, electronic device and storage medium for a point cloud section provided by the present invention can realize the sorting of complex multi-contour data of a point cloud section.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data sorting method, device, electronic equipment and storage medium for a point cloud section. Background Art

[0002] In recent years, obtaining point clouds through 3D laser scanning technology and performing 3D reconstruction has become a research hotspot in the field of reverse engineering. In the process of surface reconstruction of 3D reconstruction, the most important thing is to sort the point cloud section data obtained by segment projection and obtain the outer contour of the point cloud section data. Therefore, sorting the section data is an indispensable step in reverse engineering data preprocessing.

[0003] Point cloud cross-section data can be divided into single contour and multi-contour. Most of the existing research on cross-section data sorting is aimed at single contour, including bidirectional nearest point shrinkage method, sequential connection method, 360-degree scanning method, minimum convex hull method, etc. There are fewer studies on multi-contour, which can be divided into two categories. One is to first divide the multi-contour into single contours by corresponding methods and then sort them separately; the other is to directly sort the multi-contour data. The segmentation of multi-contour data usually requires interactive operations, so the efficiency is often relatively low, and the direct sorting method is often not very applicable and cannot solve the sorting problem of some complex point cloud cross-section multi-contour data.

[0004] The existing direct sorting methods mainly separate and sort by distance and polar coordinates, so they are only applicable to some simple multi-contour cross-section data with relatively smooth contour boundaries and geometric centers inside the contours. The existing point cloud cross-section multi-contour data sorting methods cannot solve the complex multi-contour data sorting problems in the point cloud cross-section data preprocessing in the field of reverse engineering, such as the data sorting when the contour boundaries are jagged and the geometric center is outside the contour. Summary of the invention

[0005] The present invention provides a point cloud section data sorting method, device, electronic device and storage medium, which are used to solve the problem of complex multi-contour data sorting of point cloud sections in the field of reverse engineering that cannot be solved in the prior art, and realize the sorting of complex multi-contour data of point cloud sections.

[0006] In a first aspect, the present invention provides a method for sorting point cloud section data, comprising:

[0007] Roughly sort the data points in the single contour area on the point cloud section to obtain the single contour convex hull;

[0008] On the single contour convex hull, a convex hull edge that meets the target length is selected as a target convex hull edge, and based on the target convex hull edge, a new convex hull point is selected from the remaining points; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section;

[0009] Inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge;

[0010] Based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0011] In one embodiment, selecting a new convex hull point from the remaining points includes:

[0012] Based on the target convex hull edge, a remaining point screening area is obtained, and from the remaining point screening area, the remaining points closest to the target convex hull edge are selected as the new convex hull points.

[0013] In one embodiment, obtaining a remaining point screening area based on the target convex hull edge includes:

[0014] Based on the target convex edge, a circular residual point screening area is obtained; wherein the target convex edge is the diameter of the circular residual point screening area.

[0015] In one embodiment, roughly sorting the data points in the single contour area on the point cloud section to obtain the single contour convex hull includes:

[0016] Based on the target scanning area and the target scanning direction corresponding to the data points of the point cloud section, the data points of the point cloud section are roughly sorted to obtain the single contour convex hull.

[0017] In one embodiment, the step of roughly sorting the data points of the point cloud section based on the target scanning area and the target scanning direction corresponding to the data points of the point cloud section to obtain the single contour convex hull includes:

[0018] Selecting an initial data point in the point cloud section;

[0019] The direction from the current data point to the previous data point is used as the scanning starting direction, and the contour distance threshold is used as the scanning radius. Scanning is performed based on the target scanning direction, and the first scanned data point in the target scanning area corresponding to the scanning radius is used as the next data point.

[0020] In one embodiment, the selecting of initial data points in the point cloud section includes:

[0021] In the target coordinate system, a data point with the smallest abscissa or ordinate is selected from the point cloud section as the initial data point.

[0022] In one embodiment, the step of roughly sorting the data points of the point cloud section based on the target scanning area and the target scanning direction corresponding to the data points of the point cloud section to obtain the single contour convex hull further includes:

[0023] When the current data point is the same as the initial data point, the rough sorting of the data points of the point cloud section is terminated.

[0024] In a second aspect, the present invention provides a data sorting device for a point cloud section, comprising:

[0025] A coarse sorting module is used to roughly sort the data points in the single contour area on the point cloud section to obtain the single contour convex hull;

[0026] The new convex hull point search module selects a convex hull edge that meets the target length on the single contour convex hull as a target convex hull edge, and selects a new convex hull point from the remaining points based on the target convex hull edge; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section;

[0027] A fine sorting module, used for inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge;

[0028] The contour segmentation module is used to select data points from the pending data points to form a new point set based on the contour distance threshold, and output the new point set for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0029] In a third aspect, the present invention provides an electronic device, comprising a processor and a memory storing a computer program, wherein the processor implements the steps of any of the above-mentioned point cloud section data sorting methods when executing the computer program.

[0030] In a fourth aspect, the present invention provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, wherein the computer program is used to enable the processor to execute the steps of any one of the above-mentioned point cloud section data sorting methods.

[0031] The data sorting method, device, electronic device and storage medium of the point cloud cross section provided by the present invention first roughly sort the data points in the single contour area on the point cloud cross section to obtain the single contour convex hull, and then insert the new convex hull points between the convex hull points at both ends of the target convex hull edge to perform fine sorting. Finally, when the data points of the point cloud cross section meet the multi-contour condition, data points can be selected from the pending data points based on the contour distance threshold to form a new point set, so as to segment the other contour data points on the point cloud cross section, and the data points in the new point set, that is, the data points of other contours, are sorted to complete the sorting of the multi-contour data points.

[0032] Compared with the existing technical solutions, in the method provided by the present invention, the data within the convex hull of a single contour is first sorted, and then based on the contour distance threshold, the data points of other contours are segmented and then sorted, thereby directly sorting multi-contour data, eliminating interactive operations, and having higher efficiency. At the same time, compared with other direct sorting methods, the method provided by the present invention can handle some complex point cloud section multi-contour data sorting problems, such as situations where the contour boundary is jagged and the geometric center is outside the contour, and has higher applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 It is one of the flow charts of the data sorting method of the point cloud section provided by the present invention;

[0035] Figure 2 is a convex hull construction result graph provided by the present invention;

[0036] Figure 3 is the convex hull iteration result graph provided by the present invention;

[0037] Figure 4 It is the final result image after the convex hull contour separation provided by the present invention;

[0038] Figure 5 This is the second flow chart of the method for sorting point cloud cross-section data provided by the present invention;

[0039] Figure 6 It is a principle block diagram of the data sorting device for point cloud sections provided by the present invention;

[0040] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Combine the following Figure 1-Figure 7 The present invention describes a method, device, electronic device and storage medium for sorting point cloud cross sections.

[0043] The present invention provides a method for sorting data of a point cloud section. Figure 1 As shown, the data sorting method of the point cloud section includes:

[0044] Step 110 , roughly sort the data points in the single contour area on the point cloud section to obtain the single contour convex hull.

[0045] A single contour area is a convex hull contour area. Convex hull is a concept in computational geometry (graphics), which contains the intersection of all convex sets of set X.

[0046] Step 120: On the single contour convex hull, select a convex hull edge that meets the target length as the target convex hull edge, and based on the target convex hull edge, select a new convex hull point from the remaining points; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section.

[0047] It should be noted that the convex hull edge is also the edge of the single-contour convex hull, and the single-contour convex hull is composed of a plurality of convex hull edges connected in sequence.

[0048] It is understandable that on a single contour convex hull, the number of target convex hull edges can be multiple, and multiple new convex hull points can be selected in sequence.

[0049] Step 130: insert the new convex hull point between the convex hull points at both ends of the target convex hull edge.

[0050] After obtaining the new convex hull points through the above, the new convex hull points are sequentially inserted between the convex hull points at both ends of the target convex hull edge to complete an accurate sorting, and then the above steps are continuously executed in a loop until the insertion sorting of all new convex hull points is completed.

[0051] Step 140: based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0052] It should be noted that step 140 is performed when the data points of the point cloud section meet the multi-contour condition.

[0053] The data points selected from the pending data points are also contour points, and the contour points are pending data points whose distances from the single contour convex hull are greater than the contour distance threshold.

[0054] It can be understood that the contour distance threshold can be set by oneself, which represents the distance between two different contour data points, and the contour is also the convex hull contour.

[0055] When there are multiple contours on the point cloud section, the data points of the multiple contours can be processed separately, and the data points contained in one of the single contours can be roughly sorted.

[0056] The new point set is output for sorting, and based on the data points of the new point set, steps 110, 120, 130 and 140 are continued to be executed to sort the data points of the new point set.

[0057] The data points of the point cloud section meet the multi-contour conditions, including:

[0058] After the data points corresponding to a single contour convex hull are sorted, the distance between each pending data point on the point cloud section and each convex hull point on the single contour convex hull is calculated. For a single pending point, the maximum distance value between the pending point and each convex hull point on the single contour convex hull is selected. If the maximum distance value is greater than the contour separation threshold, it is determined that the pending point belongs to another contour, which is called a contour point. If there are multiple contour points, it can be determined that the data points of the point cloud section meet the multi-contour condition.

[0059] The sorting of the data points corresponding to the single contour convex hull is completed. If each convex hull edge of the single contour convex hull does not meet the target length, or there are no remaining points in the remaining point screening area, it is determined that the sorting of the data points corresponding to the single contour convex hull is completed.

[0060] In some embodiments, selecting a new convex hull point from the remaining points includes:

[0061] Based on the target convex hull edge, a remaining point screening area is obtained, and from the remaining point screening area, the remaining points closest to the target convex hull edge are selected as new convex hull points.

[0062] In some embodiments, based on the target convex edge, obtaining the remaining point screening area includes:

[0063] Based on the target convex hull edge, a circular residual point screening area is obtained; wherein the target convex hull edge is the diameter of the circular residual point screening area.

[0064] In some embodiments, roughly sorting the data points in the single contour region on the point cloud section to obtain the single contour convex hull includes:

[0065] Based on the target scanning area and target scanning direction corresponding to the data points of the point cloud section, the data points of the point cloud section are roughly sorted to obtain the single contour convex hull.

[0066] The single contour convex hull obtained through this step still has a large error compared with the actual result, so it can only be called a rough sorting.

[0067] It can be understood that there are multiple data points on the point cloud cross section, and the target scanning areas and target scanning directions of different data points are different.

[0068] After determining a data point, based on the target scanning area of ​​the data point, scan in the target scanning direction, such as clockwise or counterclockwise, and place the first scanned data point as the last data point. Repeat this action to obtain a sort of multiple data points. After connecting the sorted multiple data points in sequence, a single contour convex hull is obtained.

[0069] In some embodiments, based on the target scanning area and the target scanning direction corresponding to the data points of the point cloud section, the data points of the point cloud section are roughly sorted to obtain a single contour convex hull, including:

[0070] Select the initial data point in the point cloud section;

[0071] The direction from the current data point to the previous data point is used as the scanning starting direction, and the contour distance threshold is used as the scanning radius. Scanning is performed based on the target scanning direction, and the first scanned data point in the target scanning area corresponding to the scanning radius is used as the next data point. Therefore, based on the contour distance threshold, a single contour area can be determined.

[0072] It should be noted that, by using the contour distance threshold as the scanning radius for scanning, it can be ensured that the scanned data points belong to the same single contour as the current data points.

[0073] It can be understood that the target scanning area corresponding to the scanning radius is a circular area with the current data point as the origin and the distance between the current data point and the previous data point as the radius.

[0074] In some embodiments, selecting an initial data point in a point cloud section includes:

[0075] In the target coordinate system, select the data point with the smallest horizontal or vertical coordinate from the point cloud section as the initial data point.

[0076] In some embodiments, based on the target scanning area and the target scanning direction corresponding to the data points of the point cloud section, the data points of the point cloud section are roughly sorted to obtain a single contour convex hull, further comprising:

[0077] When the current data point is the same as the initial data point, the rough sorting of the data points of the point cloud section is ended.

[0078] It can be understood that to achieve the data point sorting of the single contour convex hull, we must first determine a distance threshold D that can separate the contours according to the data on the cross section, and then complete the construction of the convex hull according to the distance threshold D. The schematic diagram of the convex hull construction is as follows Figure 2 As shown, the specific steps are as follows:

[0079] 1. Select the initial data point. Among all the data points on the point cloud section, the data point with the smallest horizontal or vertical coordinate must be a point on the convex hull, denoted as P0.

[0080] 2. Take P0 as the center point, the positive semi-axis direction of the horizontal coordinate as the initial direction, the distance threshold D as the radius, and scan in the counterclockwise direction. The first data point scanned is the next data point (this data point is also a convex hull point), which is recorded as the current point P i .

[0081] 3. Set the current data point P i The previous data point is denoted as P i-1 , with P i is the center point, P i P i-1 is the initial direction, the distance threshold D is the radius, and the scan is performed counterclockwise. The first data point scanned is the next data point (this data point is also a convex hull point), which is recorded as the new current data point P i .

[0082] 4. Determine the current data point P i Is the coordinate of the initial data point P0 the same? If so, the convex hull of the single contour is constructed; otherwise, go to step 3.

[0083] Furthermore, the single contour convex hull still has a large error compared with the actual result, so it can only be called a rough sort. The precise sorting depends on the convex hull iteration. The iterated convex hull is as follows: Figure 3 As shown, first you need to enter the iteration threshold d, which is the basis for whether the convex hull continues to iterate. The specific steps are as follows:

[0084] Select a convex hull edge on the single contour convex hull, calculate whether the length of the edge is greater than the iteration threshold, if greater, determine that the convex hull edge meets the target length, then search for the remaining points in the circular area with the midpoint of the edge as the center point and the side length as the diameter (i.e., the remaining point screening area), select the point closest to the edge from the remaining points as the new convex hull point, and insert it between the two endpoints of the edge, and finally calculate the next convex hull edge of the single contour convex hull, until all convex hull edges are calculated, which is the first iteration.

[0085] Continue to iterate the convex hull edges until the length of each convex hull edge on the convex hull is less than the iteration threshold, that is, all convex hull edges do not meet the target length, or there are no remaining points in the circular area corresponding to the convex hull edge, and finally obtain the accurate sorting result of the single contour.

[0086] The contour points in the remaining points are stored in a new point set, and a new round of convex hull construction, convex hull iteration and contour separation is performed on the new point set until there are no new contour points in the remaining points. At this point, the cross-section multi-contour data sorting is completed. The result is as follows Figure 4 shown.

[0087] The method provided by the present invention assumes that there are n points on a plane, and the minimum convex hull is the convex polygon with the smallest area that contains all the points on the plane. The method provided by the present invention can be divided into three parts: convex hull construction, convex hull iteration, and contour separation. Convex hull construction and convex hull iteration respectively realize the rough sorting and precise sorting of a single contour in the point cloud cross-section data. Contour separation is responsible for judging whether there is another contour in the remaining points after the single contour is sorted. If so, the loop starts. The overall process of the method is as follows: Figure 5 shown.

[0088] To summarize, the data sorting method for the point cloud section provided by the present invention first roughly sorts the data points in the single contour area on the point cloud section to obtain the single contour convex hull, and then inserts the new convex hull points between the convex hull points at both ends of the target convex hull edge for fine sorting. Finally, when the data points of the point cloud section meet the multi-contour conditions, data points can be selected from the pending data points based on the contour distance threshold to form a new point set, thereby realizing the segmentation of other contour data points on the point cloud section, and sorting the data points in the new point set, that is, the data points of other contours, to complete the sorting of multi-contour data points.

[0089] Compared with the existing technical solutions, in the method provided by the present invention, the data within the convex hull of a single contour is first sorted, and then based on the contour distance threshold, the data points of other contours are segmented and then sorted, thereby directly sorting multi-contour data, eliminating interactive operations, and having higher efficiency. At the same time, compared with other direct sorting methods, the method provided by the present invention can handle some complex point cloud section multi-contour data sorting problems, such as situations where the contour boundary is jagged and the geometric center is outside the contour, and has higher applicability.

[0090] The data sorting device for point cloud sections provided by the present invention is described below. The data sorting device for point cloud sections described below and the data sorting method for point cloud sections described above can correspond to each other.

[0091] like Figure 6 As shown, the data sorting device 600 for point cloud sections includes: a rough sorting module 610 , a new convex hull point searching module 620 , a fine sorting module 630 and a contour segmentation module 640 .

[0092] The rough sorting module 610 is used to roughly sort the data points in the single contour area on the point cloud section to obtain the single contour convex hull.

[0093] The new convex hull point search module 620 selects a convex hull edge that meets the target length on the single contour convex hull as the target convex hull edge, and selects new convex hull points from the remaining points based on the target convex hull edge; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section.

[0094] The fine sorting module 630 is used to insert the new convex hull point between the convex hull points at both ends of the target convex hull edge.

[0095] The contour segmentation module 640 is used to select data points from the pending data points to form a new point set based on the contour distance threshold, and output the new point set for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0096] It should be noted that when the contour segmentation module 640 sorts the data points in the new point set, the new point set is input into the coarse sorting module 610, and the coarse sorting module 610, the new convex hull point search module 620, the fine sorting module 630 and the contour segmentation module 640 continue to sort the data points in the new point set.

[0097] In some embodiments, the new convex hull point search module 620 is further used to obtain a remaining point screening area based on the target convex hull edge, and select the remaining points closest to the target convex hull edge from the remaining point screening area as new convex hull points.

[0098] In some embodiments, the new convex hull point search module 620 is further used to obtain a circular remaining point screening area based on a target convex hull edge; wherein the target convex hull edge is the diameter of the circular remaining point screening area.

[0099] In some embodiments, the rough sorting module 610 is further used to roughly sort the data points of the point cloud section based on the target scanning area and the target scanning direction corresponding to the data points of the point cloud section to obtain a single contour convex hull.

[0100] In some embodiments, the coarse sorting module 610 includes: an initial point determination unit and a scanning unit.

[0101] The initial point determination unit is used to select initial data points in the point cloud section.

[0102] The scanning unit is used to use the direction from the current data point to the previous data point as the scanning starting direction, and the contour distance threshold as the scanning radius, scan based on the target scanning direction, and use the first scanned data point in the target scanning area corresponding to the scanning radius as the next data point.

[0103] In some embodiments, the initial point determination unit is further used to select a data point with the smallest horizontal coordinate or vertical coordinate from the point cloud cross section in the target coordinate system as the initial data point.

[0104] In some embodiments, the coarse sorting module 610 further includes: a sorting end unit.

[0105] The sorting end unit is used to end the rough sorting of the data points of the point cloud section when the current data point is the same as the initial data point.

[0106] The electronic device and storage medium provided by the present invention are described below. The electronic device and storage medium described below and the data sorting method of the point cloud section described above can be referred to each other.

[0107] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730 and a communication bus 740, wherein the processor 710, the communication interface 720 and the memory 730 communicate with each other through the communication bus 740. The processor 710 may call a computer program in the memory 730 to execute the steps of the data sorting method of the point cloud section, for example, including:

[0108] Step 110, roughly sorting the data points in the single contour area on the point cloud section to obtain the single contour convex hull;

[0109] Step 120: On the single contour convex hull, select a convex hull edge that meets the target length as the target convex hull edge, and select a new convex hull point from the remaining points based on the target convex hull edge; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section;

[0110] Step 130, inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge;

[0111] Step 140: based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0112] In addition, the logic instructions in the above-mentioned memory 30 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0113] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, when the program instructions are executed by a computer, the computer can execute the data sorting method of the point cloud section provided by the above methods, the method comprising:

[0114] Step 110, roughly sorting the data points in the single contour area on the point cloud section to obtain the single contour convex hull;

[0115] Step 120: On the single contour convex hull, select a convex hull edge that meets the target length as the target convex hull edge, and select a new convex hull point from the remaining points based on the target convex hull edge; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section;

[0116] Step 130, inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge;

[0117] Step 140: based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0118] On the other hand, an embodiment of the present application further provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, wherein the computer program is used to enable the processor to execute the methods provided in the above embodiments, for example, including:

[0119] Step 110, roughly sorting the data points in the single contour area on the point cloud section to obtain the single contour convex hull;

[0120] Step 120: On the single contour convex hull, select a convex hull edge that meets the target length as the target convex hull edge, and select a new convex hull point from the remaining points based on the target convex hull edge; wherein the remaining points are the data points remaining after the single contour convex hull is removed from the point cloud section;

[0121] Step 130, inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge;

[0122] Step 140: based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points.

[0123] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.

[0124] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0125] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for sorting point cloud cross-section data, characterized in that: include: Roughly sort the data points in a single contour area on the point cloud section to obtain the single contour convex hull; On the single contour convex hull, selecting a convex hull edge that meets the target length as a target convex hull edge, and selecting a new convex hull point from the remaining points based on the target convex hull edge; Inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge; Based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points; the data points selected from the pending data points are the pending data points whose distance from the single contour convex hull is greater than the contour distance threshold; Based on the data points in the new point set, for the next single contour area on the point cloud section, the step of roughly sorting the data points in a single contour area on the point cloud section to obtain the single contour convex hull is performed, and based on the contour distance threshold, data points are selected from the pending data points to form a new point set, and the new point set is output for sorting, until all contour data points on the point cloud section are sorted.

2. The data sorting method of point cloud cross section according to claim 1, characterized in that: The step of selecting a new convex hull point from the remaining points comprises: Based on the target convex hull edge, a remaining point screening area is obtained, and from the remaining point screening area, the remaining points closest to the target convex hull edge are selected as the new convex hull points.

3. The data sorting method of point cloud cross section according to claim 2, characterized in that: The obtaining of the remaining point screening area based on the target convex hull edge includes: Based on the target convex edge, a circular residual point screening area is obtained; wherein the target convex edge is the diameter of the circular residual point screening area.

4. The method for sorting point cloud cross-section data according to any one of claims 1 to 3, characterized in that: The method of roughly sorting the data points in a single contour area on the point cloud section to obtain the single contour convex hull includes: Based on the target scanning area and the target scanning direction corresponding to the data points in a single contour area on the point cloud section, the data points in a single contour area on the point cloud section are roughly sorted to obtain the single contour convex hull.

5. The method for sorting point cloud cross-section data according to claim 4, characterized in that: The step of roughly sorting the data points in a single contour area on the point cloud section based on the target scanning area and the target scanning direction corresponding to the data points in a single contour area on the point cloud section to obtain the single contour convex hull comprises: Selecting initial data points in a single contour area on the point cloud cross section; The direction from the current data point to the previous data point is used as the scanning starting direction, and the contour distance threshold is used as the scanning radius. Scanning is performed based on the target scanning direction, and the first scanned data point in the target scanning area corresponding to the scanning radius is used as the next data point.

6. The method for sorting point cloud cross-section data according to claim 5, characterized in that: The selecting of initial data points in a single contour area on the point cloud section comprises: In the target coordinate system, a data point with the smallest abscissa or ordinate is selected from a single contour area on the point cloud section as the initial data point.

7. The method for sorting point cloud cross-section data according to claim 5, characterized in that: The step of roughly sorting the data points within a single contour area on the point cloud section based on the target scanning area and the target scanning direction corresponding to the data points within a single contour area on the point cloud section to obtain the single contour convex hull further includes: When the current data point is the same as the initial data point, the rough sorting of the data points of the point cloud section is terminated.

8. A data sorting device for point cloud sections, characterized in that: include: A coarse sorting module is used to roughly sort the data points in a single contour area on the point cloud section to obtain the single contour convex hull; A new convex hull point search module is used to select a convex hull edge that meets the target length on the single contour convex hull as a target convex hull edge, and select a new convex hull point from the remaining points based on the target convex hull edge; A fine sorting module, used for inserting the new convex hull point between the convex hull points at both ends of the target convex hull edge; A contour segmentation module, for selecting data points from pending data points to form a new point set based on a contour distance threshold, and outputting the new point set for sorting; wherein the pending data points are the data points remaining after removing the new convex hull points from the remaining points; the data points selected from the pending data points are pending data points whose distance from the single contour convex hull is greater than the contour distance threshold; The data points in the new point set are input into the coarse sorting module, and the coarse sorting module, the new convex hull point search module, the fine sorting module and the contour segmentation module are used in sequence to continue sorting the data points in the new point set until all contour data points on the point cloud section are sorted.

9. An electronic device comprising a processor and a memory storing a computer program, characterized in that: When the processor executes the computer program, the steps of the point cloud section data sorting method according to any one of claims 1 to 7 are implemented.

10. A processor-readable storage medium, characterized in that: The processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the steps of the point cloud section data sorting method according to any one of claims 1 to 7.

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