CN109697733A - Point searching method and device in point cloud space, computer equipment and storage medium - Google Patents
Point searching method and device in point cloud space, computer equipment and storage medium Download PDFInfo
- Publication number
- CN109697733A CN109697733A CN201811600009.0A CN201811600009A CN109697733A CN 109697733 A CN109697733 A CN 109697733A CN 201811600009 A CN201811600009 A CN 201811600009A CN 109697733 A CN109697733 A CN 109697733A
- Authority
- CN
- China
- Prior art keywords
- point
- cloud
- coordinate
- linear
- space
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 73
- 238000004590 computer program Methods 0.000 claims description 19
- 238000012512 characterization method Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 13
- 230000000694 effects Effects 0.000 description 9
- 238000009877 rendering Methods 0.000 description 9
- 239000007787 solid Substances 0.000 description 4
- 230000015572 biosynthetic process Effects 0.000 description 1
- 210000000746 body region Anatomy 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005498 polishing Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/60—Memory management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/005—General purpose rendering architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Graphics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Processing Or Creating Images (AREA)
Abstract
The application relates to a point searching method and device in a point cloud space, computer equipment and a storage medium. The computer equipment determines a point cloud area according to the coordinates of all points in the point cloud, converts all the points in the point cloud area into a linear data structure and stores the linear data structure in a linear storage space, and then determines a target point in the point cloud in the linear storage space according to a three-dimensional rectangular frame. In the method, the computer equipment stores all points in the point cloud into the linear data structure and then searches for the target point in the linear storage space, so that the searched target point is the linear data structure.
Description
Technical field
This application involves a cloud fields, seek point methods, device, computer equipment more particularly to a kind of cloud space
And storage medium.
Background technique
The point data set for the appearance surfaces that point cloud representation is obtained in reverse-engineering by measuring instrument, expression are
The space coordinate of each sampled point of body surface.With the universal of point cloud acquisition equipment, technique of binocular stereoscopic vision, VR and AR
Development, Point Cloud Processing technology are just becoming one of most promising technology.
In Point Cloud Processing, it is directed not only to the input of front end data, the processing of intermediate data, also relates to aft terminal
The rendering of cloud.It needs first to determine the target zone of rendering when rendering a cloud, and determines the target zone of rendering and then relate to
And to being sought a little in a cloud space.Point cloud space, which is sought, a little to be typically referred to find in the frame of a cuboid in cloud space
The point of point cloud, generally, it is a little to optimize to seek a little with nonlinear data structure that point cloud space, which is sought, but third party library in practice
It is linear data structure that the format of point cloud storage is required when rendering point cloud, nonlinear data structure cannot be stored, so with non-
Linear data structure carries out after seeking a little, then when rendering to a cloud, which can be stored in additional deposit
Store up space.
Therefore, it after above-mentioned use nonlinear data structure is sought a little in a cloud space, is needed when being rendered to a cloud additional
Memory space nonlinear data structure is stored, cause the resource overhead bigger.
Summary of the invention
Based on this, it is necessary to after seeking a little for above-mentioned use nonlinear data structure in a cloud space, carry out a wash with watercolours to cloud
Additional memory space is needed to store nonlinear data structure when dye, the technology for causing resource overhead bigger is asked
Topic, provides a kind of cloud space and seeks point methods, device, computer equipment and storage medium.
In a first aspect, the embodiment of the present invention, which provides a kind of cloud space, seeks point methods, which comprises
Point cloud sector domain is determined according to the coordinate of all the points in described cloud；
All the points in the domain of described cloud sector are converted to linear data structure to be stored in linear memory space；
According to three-dimensional rectangle frame, the target point in described cloud is determined in the linear memory space.
The coordinate according to all the points in described cloud determines point cloud sector domain in one of the embodiments, comprising:
The maximum in described cloud in the maximum value and minimum value and Y-coordinate axle of the X-coordinate axle of all the points is obtained respectively
Value and minimum value；
According in the maximum value of the X-coordinate axle and minimum value and the Y-coordinate axle maximum value and minimum value determine institute
State a cloud sector domain.
It is described in one of the embodiments, all the points in the domain of described cloud sector are converted into linear data structure to be stored in
In linear memory space, comprising:
Described cloud sector domain is divided according to preset length and predetermined width, obtains multiple subregions；
Point in each subregion point is converted to linear data structure to be stored in the linear memory space.
The point by each subregion point is converted to linear data structure and is stored in one of the embodiments,
In the linear memory space, comprising:
Determine that each subregion is right in the linear memory space according to the number of each subregion midpoint cloud point
The regional scope answered；
According to preset order, the point in each subregion is converted into linear data structure and is stored in corresponding region model
In enclosing.
It is described according to three-dimensional rectangle frame in one of the embodiments, the point is determined in the linear memory space
Target point in cloud, comprising:
Obtain the rectangular area that the three-dimensional rectangle frame is mapped on X/Y plane；The X/Y plane characterization X-coordinate axle and Y are sat
The plane that parameter is constituted；
The determining subregion overlapped with the rectangular area, obtains overlapping ranges；
According to the three-dimensional rectangle frame, the target point in described cloud is determined in the overlapping ranges.
It is described according to the three-dimensional rectangle frame in one of the embodiments, the point is determined in the overlapping ranges
Target point in cloud, comprising:
Obtain the coordinate section that the three-dimensional rectangle frame is mapped on Z coordinate axis；
Z coordinate in the overlapping ranges is belonged to the point in the coordinate section, the target point being determined as in described cloud.
In one of the embodiments, in the point that Z coordinate in the overlapping ranges is belonged to the coordinate section, really
It is set to before the target point in described cloud, the method also includes:
Point in the overlapping ranges is ranked up according to the sequence of Z coordinate from small to large.
Second aspect, the embodiment of the present invention provide a kind of cloud space and seek a device, and described device includes:
First determining module determines point cloud sector domain for the coordinate according to all the points in described cloud；
Memory module is stored in linear memory sky for all the points in the domain of described cloud sector to be converted to linear data structure
Between in；
Second determining module, for determining described cloud in the linear memory space according to the three-dimensional rectangle frame
In target point.
The third aspect, the embodiment of the present invention provide a kind of computer equipment, including memory and processor, the memory
It is stored with computer program, the processor is realized shown in above-mentioned first aspect any embodiment when executing the computer program
Point cloud space seek point methods.
Fourth aspect, the embodiment of the present invention provide a kind of computer readable storage medium, are stored thereon with computer program,
The computer program realizes that point methods are sought in point cloud space shown in above-mentioned first aspect any embodiment when being executed by processor.
The embodiment of the present application provides a kind of cloud space and seeks point methods, device, computer equipment and storage medium, computer
Equipment determines point cloud sector domain according to the coordinate of all the points in cloud, and all the points in cloud sector domain are converted to linear data structure
It is stored in linear memory space, then according to three-dimensional rectangle frame, the target point in point cloud is determined in linear memory space.By
In this method, all the points in cloud are first stored as linear data structure by computer equipment, then are found in linear memory space
Target point, so that the target point sought out is a linear data structure, in this way, computer equipment is with linear data structure in point
After cloud space is sought a little, when rendering to a cloud, linear data structure can be stored directly in third party library, without additional
Memory space linear data structure is stored, greatly reduce the expense of extra memory, save resource.
Detailed description of the invention
Fig. 1 is the applied environment figure that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 2 is the flow diagram that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 3 is the flow diagram that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 4 is the flow diagram that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 5 is the flow diagram that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 6 is the flow diagram that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 7 is the flow diagram that point methods are sought in a kind of cloud space that one embodiment provides；
Fig. 8 is the structural block diagram that a device is sought in a kind of cloud space that one embodiment provides；
Fig. 9 is the structural block diagram that a device is sought in a kind of cloud space that one embodiment provides；
Figure 10 is the structural block diagram that a device is sought in a kind of cloud space that one embodiment provides；
Figure 11 is the structural block diagram that a device is sought in a kind of cloud space that one embodiment provides；
Figure 12 is the structural block diagram that a device is sought in a kind of cloud space that one embodiment provides；
Figure 13 is the structural block diagram that a device is sought in a kind of cloud space that one embodiment provides.
Specific embodiment
It is with reference to the accompanying drawings and embodiments, right in order to which the objects, technical solutions and advantages of the application are more clearly understood
The application is further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the application, not
For limiting the application.
Point methods are sought in a kind of cloud space provided by the present application, can be applied in application environment as shown in Figure 1, the meter
Calculating machine equipment can be server, which includes processor, the memory, network interface connected by system bus
And database.Wherein, the processor is for providing calculating and control ability.The memory includes non-volatile memory medium, interior
Memory.The non-volatile memory medium is stored with operating system, computer program and database.The built-in storage is non-volatile
Property storage medium in operating system and computer program operation provide environment.The database is sought a little for storing point cloud space
The data of method.The network interface is used to communicate with external other equipment by network connection.The computer program is processed
To realize that point methods are sought in a kind of cloud space when device executes.
Embodiments herein provides a kind of cloud space and seeks point methods, device, computer equipment and storage medium, it is intended to
It solves after being sought a little in a cloud space using nonlinear data structure, additional memory space is needed to come pair when rendering to cloud
Nonlinear data structure is stored, and the technical problem that resource overhead is bigger is caused.Embodiment will be passed through below and combined attached
Figure specifically carries out specifically to how the technical solution of the technical solution of the application and the application solves above-mentioned technical problem
It is bright.These specific embodiments can be combined with each other below, may be in certain realities for the same or similar concept or process
It applies in example and repeats no more.It should be noted that point methods, executing subject are sought in a kind of cloud space provided in an embodiment of the present invention
For computer equipment, wherein the executing subject can also be that a device is sought in a cloud space, wherein the device can by software,
The mode of hardware or software and hardware combining realizes that some or all of of a determining device is sought in a cloud space.
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.
In one embodiment, Fig. 2 is that point methods are sought in a kind of cloud space provided by the embodiments of the present application, and the present embodiment relates to
And be that computer equipment according to the point in cloud is stored as linear memory structure, and according to three-dimensional rectangle frame, in linear memory
The detailed process of the target point in point cloud is determined in space, as shown in Fig. 2, this method comprises:
S101 determines point cloud sector domain according to the coordinate of all the points in described cloud.
In the present embodiment, point cloud representation is a cloud frame having stored in computer equipment, wherein computer
What is stored when equipment storage point cloud is the coordinate of all the points in a cloud, and when executing this step, computer equipment is directly acquired i.e.
It can.Wherein, point cloud sector domain representation point cloud is mapped in the region in the plane of X-coordinate axle and Y-coordinate axle composition.In practical application
In, the coordinate that computer equipment obtains all the points in point cloud determines point cloud sector domain, and illustratively, acquisition modes can be computer
Equipment first determines the coordinate of most marginal position point in point cloud, then determines point cloud sector according to the coordinate of these most marginal position points
Domain, can also be other modes certainly, and the present embodiment does not limit this.
All the points in the domain of described cloud sector are converted to linear data structure and are stored in linear memory space by S102.
Wherein, computer equipment when linear memory space is arranged, implemented by the big small capital in space specific for linear memory
Example and without limitation, can according to the actual situation depending on, as long as the linear memory space can be by the storage of cloud all the points.In reality
In the application of border, based on the point cloud sector domain that computer equipment in above-mentioned S101 step determines, computer equipment will be in the domain of this cloud sector
All the points are converted to linear data structure and are stored in linear memory space, and illustratively, storage mode can be, and computer is set
It is standby successively to store all the points in the domain of this cloud sector in the linear memory space according to the customized sequence of user, it can also be with
Be computer equipment line determines a range according to cloud sector domain in linear memory space, then deposits the point in a cloud sector domain
It stores up in the range of the determination；Its storage mode can also be other modes, and the present embodiment does not limit this.It is understood that
Being computer equipment is stored in linear memory space for all the points in cloud, and the data constituted are linear data structure.
S103 determines the target point in described cloud according to three-dimensional rectangle frame in the linear memory space.
In this step, three-dimensional rectangle frame can also be referred to as cuboid, and expression is that provided by the present application cloud space is sought
The target area of point, the point in the three-dimensional rectangle frame are that the application needs target point in target-seeking cloud.In practical applications,
Based in above-mentioned S102 step, all the points in cloud are stored in formation linear data knot in linear memory space by computer equipment
Structure, computer equipment is according to the three-dimensional rectangle frame, from the target point determined in linear memory space in described cloud, illustratively,
Computer equipment determines that the mode of target point can be, and directly first determines and is located in the three-dimensional rectangle frame in the three-dimensional rectangle frame
Point, these point be it needs to be determined that target point；It can also be that computer equipment first determines that the cloud is vertical in solid space
Then body region determines that three-dimensional rectangle frame and the point cloud part that solid region is overlapped in space, the point in intersection are
It needs to be determined that target point；Certainly other modes be can also be, the present embodiment does not limit this.
Point methods are sought in a kind of cloud space provided in this embodiment, and computer equipment is true according to the coordinate of all the points in cloud
Cloud sector domain is pinpointed, and all the points in cloud sector domain are converted into linear data structure and are stored in linear memory space, then root
According to three-dimensional rectangle frame, the target point in point cloud is determined in linear memory space.Since in this method, computer equipment is first by point
All the points are stored as linear data structure in cloud, then find target point in linear memory space, so that the target point sought out is
One linear data structure, in this way, carrying out wash with watercolours to cloud after computer equipment is sought a little with linear data structure in a cloud space
When dye, linear data structure is stored without additional memory space, the expense of extra memory is greatly reduced, saves
Resource.
For the determination in cloud sector domain, the embodiment of the present application provides a kind of cloud space and seeks point methods, and the embodiment is specific
What is involved is computer equipments according to the detailed process in the determining point cloud sector domain of coordinate of all the points in cloud, as shown in figure 3, above-mentioned
A kind of achievable mode of S101 step includes:
S201 is obtained in described cloud respectively in the maximum value and minimum value and Y-coordinate axle of the X-coordinate axle of all the points
Maximum value and minimum value.
In the present embodiment, computer equipment obtains the maximum value and minimum value of the X-coordinate axle of all the points in some clouds respectively, with
And maximum value and minimum value in Y-coordinate axle, be described some cloud sectors domain representation in above-described embodiment is that a cloud is mapped in XY
Region in plane, therefore, this cloud sector domain can be to put in the maximum value and minimum value and Y-coordinate axle of X-coordinate axle
Maximum value and minimum value determine.
S202, according to the maximum value of the X-coordinate axle and minimum value in the Y-coordinate axle maximum value and minimum value it is true
Fixed described cloud sector domain.
In this step, the point in cloud is put in the maximum value and minimum value of X-coordinate axle based on what is obtained in above-mentioned S201 step
With the maximum value and minimum value in the Y-coordinate axle, computer equipment determines point cloud sector domain.Its method of determination illustratively, can be with
It is set point cloud midpoint the maximum value of X-coordinate axle is maxX, the minimum value in X-coordinate axle is minX, in Y-coordinate axle
Maximum value is maxY, the minimum value in Y-coordinate axle is minY, then computer can be with y1=maxX, y2=minX, x1=
MaxY, x2=minY are boundary, and a long L=maxX-minX is partitioned on X/Y plane, and width is the area of W=maxY-minY
Domain, the region are point cloud sector domain.
Point methods are sought in a kind of cloud space provided in this embodiment, and computer equipment is by the point in cloud in X-coordinate axle
Maximum value and minimum value and Y-coordinate axle on maximum value and minimum value determine a point cloud sector domain, delimited with maximum value and minimum value
Boundary, can effectively guarantee will point cloud in all click and sweep into cloud sector domain.
Based on the above embodiment, the embodiment of the present application provides a kind of cloud space and seeks point methods, which is specifically related to
To be computer equipment be divided into multiple subregions for a cloud sector domain, and by the point storage in all subregion to linear memory space
In detailed process, as shown in figure 4, above-mentioned S102 includes:
S301 divides described cloud sector domain according to preset length and predetermined width, obtains multiple subregions.
Wherein, the data depending on preset length and predetermined width may each be according to the actual situation, it is assumed for example that the cloud
A length of L, the width W in region can be then set to sqrt (L) with the preset length of all subregion, and predetermined width is set to sqrt (W), this
Embodiment does not limit this.It in practical applications, is sqrt (L) with preset length, predetermined width is meter for sqrt (W)
It calculates machine equipment and a cloud sector domain is divided by multiple subregions according to preset length and preset width, obtained all subregion
Length is sqrt (L), and width is sqrt (W).It should be noted that computer equipment is drawn with preset length and predetermined width
When the domain of branch cloud sector, if be divided into finally, remaining length or short of width can be toward area outside polishing, to protect
The size for demonstrate,proving all subregions is identical.
Point in each subregion point is converted to linear data structure and is stored in the linear memory space by S302
In.
In this step, based on multiple subregions obtained in above-mentioned S301 step, computer equipment will be in all subregion point
Point be converted to linear data structure and be stored in linear memory space, storage mode can be computer equipment for each sub-district
Domain midpoint successively stores in the linear memory space, is also possible to other modes, and the present embodiment does not limit this.
Optionally, as shown in figure 5, a kind of achievable mode of the S302 step includes:
S401 determines each subregion in the linear memory space according to the number of each subregion midpoint cloud point
In corresponding regional scope.
In the present embodiment, computer equipment first determines the number of all subregion midpoint cloud point, according to all subregion midpoint cloud
The number of point determines all subregion corresponding regional scope in linear memory space.Illustratively, setup algorithm machine equipment divides
Subregion out is 4, and the number at each subregion midpoint is successively 8,5,3,16, then all subregion is linearly being deposited
Corresponding regional scope is 1-8,9-13,14-16,17-32 in storage.The wherein number of the subregion and all subregion midpoint
Number be for example, the present embodiment does not limit this.
S402, according to preset order, by the point in each subregion be converted to linear data structure be stored in it is corresponding
In regional scope.
Wherein, the sequence depending on preset order indicates user according to the actual situation, for example, being the number according to all subregion
Size is ranked up, or is sequentially ranked up with other, and the present embodiment does not limit this.In this step, computer is set
It is standby that the point in all subregion is converted into linear data structure and is stored in corresponding regional scope according to preset order, continue
By all subregion midpoint in above-mentioned S401 step in linear memory for corresponding regional scope, then its storage mode can be with
It is that the point in all subregion is successively stored in and linearly deposits according to the sequence of above-mentioned determining corresponding region range by computer equipment
It stores up in space.
Point methods are sought in a kind of cloud space provided in this embodiment, and computer equipment is drawn according to preset length and predetermined width
Branch cloud sector domain is multiple subregions, and the point in each region point is converted to linear data structure and is stored in linear memory space
In, it when due to storage is stored in linear memory space with the number at all subregion midpoint and according to preset order, in this way, making
It is linear data structure after all points store in the domain of invocation point cloud sector, to ensure that the subsequent point sought also is linear data
Structure.
Several embodiments are provided below to computer equipment according to three-dimensional rectangle frame, point cloud is determined in linear memory space
In the detailed process of target point be illustrated.
In one embodiment, the embodiment of the present application provides a kind of cloud space and seeks point methods, and the present embodiment is specifically related to
Be that computer equipment first determines that three-dimensional rectangle is mapped in the rectangular area on X/Y plane and above-described embodiment all subregion and hands over
Folded range determines the detailed process of the target point in point cloud further according to the overlapping ranges and three-dimensional rectangle frame, as shown in fig. 6, on
Stating S103 step includes:
S501 obtains the rectangular area that the three-dimensional rectangle frame is mapped on X/Y plane；The X/Y plane characterizes X-coordinate axle
The plane constituted with Y-coordinate axle.
In the present embodiment, computer equipment obtains three-dimensional rectangle frame and is mapped in the rectangular area on X/Y plane, wherein the XY
Plane characterizes the plane that X-coordinate axle and Y-coordinate axle are constituted, it is to be understood that three-dimensional rectangle frame is a three-dimensional cuboid, then
It is a two-dimensional surface region that it, which is mapped in the rectangular area on X/Y plane,.
S502, the determining subregion overlapped with the rectangular area, obtains overlapping ranges.
It is a two-dimensional surface on X/Y plane based on the rectangular area that in above-mentioned S501 step, computer equipment is determined
Region, and above-mentioned all subregion is also the two-dimensional surface region on X/Y plane, then computer equipment determines and the rectangular area
Overlapping subregion obtains an overlapping ranges, the point in subregion that wherein overlapping ranges characterization is overlapped with rectangular area
Range in linear memory space, then computer equipment can be according to the mode that overlapping subregion obtains overlapping ranges,
Computer equipment is that the range of the overlapping subregion in linear memory space is determined as the overlapping ranges.
S503 determines the target point in described cloud according to the three-dimensional rectangle frame in the overlapping ranges.
In this step, computer equipment determines the side of the target point in point cloud according to three-dimensional rectangle frame in overlapping ranges
Formula illustratively can be and first pass through overlapping ranges and obtain point in the overlapping ranges in the region of solid space, then obtaining should
The part that overlapping ranges midpoint is intersected in the region of solid space with three-dimensional rectangle frame, it can determine the part midpoint of the intersection
Cloud point is target point.Certain method of determination can also be other modes, and the present embodiment does not limit this.
Point methods are sought in a kind of cloud space provided in this embodiment, and it is flat that computer equipment acquisition three-dimensional rectangle frame is mapped in XY
Rectangular area on face obtains overlapping ranges according to the subregion overlapped with the rectangular area.According to three-dimensional rectangle frame, handing over
The target point in point cloud is determined in folded range, what is indicated due to the overlapping ranges is range in linear memory space, according to three
The target point that is further determined that out in overlapping ranges of dimension rectangle frame be also stored in linear memory space to get the mesh arrived
Punctuate is a linear data structure, after computer equipment is sought a little with linear data structure in a cloud space, to point Yun Jinhang
When rendering, linear data structure is stored without additional memory space, greatly reduces the expense of extra memory, is saved
Resource.
In one embodiment, the embodiment of the present application provides the target point in the determining point cloud of another computer equipment
Mode, as shown in fig. 7, what is involved is computer equipments to be mapped in coordinate on Z coordinate axis according to three-dimensional rectangle frame for the embodiment
Section determines the detailed process of target point from overlapping ranges, then a kind of achievable mode of S503 step includes:
S601 obtains the coordinate section that the three-dimensional rectangle frame is mapped on Z coordinate axis.
In the present embodiment, computer equipment obtains three-dimensional rectangle frame and is mapped in the coordinate section on Z coordinate axis, wherein the seat
Mark section of the height for the three-dimensional rectangle frame that section obtains on Z coordinate axis.
Z coordinate in the overlapping ranges is belonged to the point in the coordinate section, the target being determined as in described cloud by S602
Point.
The three-dimensional rectangle frame determined based on above-mentioned S601 step is mapped in the coordinate section on Z coordinate axis, computer equipment
From in overlapping ranges determine point cloud in target point when, can be computer equipment first obtain overlapping ranges midpoint all Z sit
Mark, from the point belonged in the coordinate section that above-mentioned three-dimensional rectangle frame is mapped on Z coordinate axis is determined in the Z coordinate, then by this
The target point that a little points are determined as in a cloud.
Optionally, the method also includes: by the point in the overlapping ranges according to Z coordinate from small to large sequence progress
Sequence.In the point that Z coordinate in overlapping ranges is belonged to coordinate section, it is determined as before the target point in a cloud, computer equipment
Z coordinate in overlapping ranges can be ranked up, obtained from overlapping ranges Z coordinate belong to the point in coordinate section directly according to
Sequence obtains, and substantially increases computer equipment and obtains the speed that Z coordinate in overlapping ranges belongs to the point in coordinate section, to mention
High computer equipment determines the efficiency of the target point in point cloud.
Point methods are sought in a kind of cloud space provided in this embodiment, and computer equipment obtains three-dimensional rectangle frame and is mapped in Z seat
Z coordinate in overlapping ranges, is belonged to the point in coordinate section by the coordinate section on parameter, the target point being determined as in a cloud, due to
What the overlapping ranges indicated is the range in linear memory space, and the coordinate area on Z coordinate axis is mapped according to three-dimensional rectangle frame
Between, it is one to get the target point arrived that the target point determined in overlapping ranges, which is also stored in linear memory space,
Linear data structure, thus after computer equipment is sought a little with linear data structure in a cloud space, when being rendered to a cloud,
Linear data structure is stored without additional memory space, the expense of extra memory is greatly reduced, saves resource.
It should be understood that although each step in the flow chart of Fig. 2-7 is successively shown according to the instruction of arrow,
These steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly stating otherwise herein, these steps
Execution there is no stringent sequences to limit, these steps can execute in other order.Moreover, at least one in Fig. 2-7
Part steps may include that perhaps these sub-steps of multiple stages or stage are not necessarily in synchronization to multiple sub-steps
Completion is executed, but can be executed at different times, the execution sequence in these sub-steps or stage is also not necessarily successively
It carries out, but can be at least part of the sub-step or stage of other steps or other steps in turn or alternately
It executes.
In one embodiment, as shown in figure 8, providing a kind of cloud space seeks a device, described device includes: first
Determining module 10, memory module 11 and the second determining module 12, in which:
First determining module 10 determines point cloud sector domain for the coordinate according to all the points in described cloud；
Memory module 11 is stored in linear memory for all the points in the domain of described cloud sector to be converted to linear data structure
In space；
Second determining module 12, for being determined in described cloud in the linear memory space according to three-dimensional rectangle frame
Target point.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
In one embodiment, as shown in figure 9, providing a kind of cloud space seeks a device, above-mentioned first determining module
10 include: first acquisition unit 101 and the first determination unit 102, in which:
First acquisition unit 101, for obtaining the maximum value and minimum of the X-coordinate axle of all the points in described cloud respectively
Value and maximum value and minimum value in Y-coordinate axle；
First determination unit 102, in the maximum value and minimum value and the Y-coordinate axle according to the X-coordinate axle
Maximum value and minimum value determine described cloud sector domain.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
In one embodiment, as shown in Figure 10, it provides a kind of cloud space and seeks a device, above-mentioned memory module 11 is wrapped
It includes: division unit 111 and storage unit 112, in which:
Division unit 111 obtains multiple sub-districts for dividing described cloud sector domain according to preset length and predetermined width
Domain；
Storage unit 112 is stored in the line for the point in each subregion point to be converted to linear data structure
In property memory space.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
In one embodiment, as shown in figure 11, it provides a kind of cloud space and seeks a device, said memory cells 112
Comprise determining that subelement 1121 and storing sub-units 1122, in which:
Subelement 1121 is determined, for determining each subregion in institute according to the number of each subregion midpoint cloud point
State corresponding regional scope in linear memory space；
Storing sub-units 1122, for according to preset order, the point in each subregion to be converted to linear data knot
Structure is stored in corresponding regional scope.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
In one embodiment, as shown in figure 12, it provides a kind of cloud space and seeks a device, above-mentioned second determining module
12 include: second acquisition unit 121, the second determination unit 122, third determination unit 123, wherein
Second acquisition unit 121, the rectangular area being mapped on X/Y plane for obtaining the three-dimensional rectangle frame；The XY
Plane characterizes the plane that X-coordinate axle and Y-coordinate axle are constituted；
Second determination unit 122 obtains overlapping ranges for the determining subregion overlapped with the rectangular area；
Third determination unit 123, for being determined in described cloud in the overlapping ranges according to the three-dimensional rectangle frame
Target point.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
In one embodiment, as shown in figure 13, it provides a kind of cloud space and seeks a device, above-mentioned third determination unit
123 include: to obtain subelement 1231 and determining subelement 1232, wherein
Obtain subelement 1231, the coordinate section being mapped on Z coordinate axis for obtaining the three-dimensional rectangle frame；
It determines subelement 1232, for Z coordinate in the overlapping ranges to be belonged to the point in the coordinate section, is determined as institute
State the target point in a cloud.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
In one embodiment, it provides a kind of cloud space and seeks a device, further include sorting module, be used for the friendship
Point in folded range is ranked up according to the sequence of Z coordinate from small to large.
A device is sought in a kind of cloud space provided by the above embodiment, and implementing principle and technical effect and the above method are real
It is similar to apply example, details are not described herein.
The specific restriction for seeking a device about cloud space may refer to the limit that point methods are sought above for cloud space
Fixed, details are not described herein.Above-mentioned cloud space seek the modules in a device can fully or partially through software, hardware and its
Combination is to realize.Above-mentioned each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also be with
It is stored in the memory in computer equipment in a software form, in order to which processor calls the above modules of execution corresponding
Operation.
In one embodiment, a kind of computer equipment is provided, which can be terminal, internal structure
Figure can be as shown in Figure 1 above.The computer equipment include by system bus connect processor, memory, network interface,
Display screen and input unit.Wherein, the processor of the computer equipment is for providing calculating and control ability.The computer equipment
Memory include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system and calculating
Machine program.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.It should
The network interface of computer equipment is used to communicate with external terminal by network connection.The computer program is executed by processor
When to realize that point methods are sought in a kind of cloud space.The display screen of the computer equipment can be liquid crystal display or electric ink
Display screen, the input unit of the computer equipment can be the touch layer covered on display screen, be also possible to outside computer equipment
Key, trace ball or the Trackpad being arranged on shell can also be external keyboard, Trackpad or mouse etc..
It will be understood by those skilled in the art that structure shown in above-mentioned Fig. 1, only portion relevant to application scheme
The block diagram of separation structure does not constitute the restriction for the computer equipment being applied thereon to application scheme, specific computer
Equipment may include perhaps combining certain components or with different component cloth than more or fewer components as shown in the figure
It sets.
In one embodiment, a kind of computer equipment, including memory and processor are provided, is stored in memory
Computer program, the processor perform the steps of when executing computer program
Point cloud sector domain is determined according to the coordinate of all the points in described cloud；
All the points in the domain of described cloud sector are converted to linear data structure to be stored in linear memory space；
According to three-dimensional rectangle frame, the target point in described cloud is determined in the linear memory space.
A kind of computer equipment provided by the above embodiment, implementing principle and technical effect and above method embodiment class
Seemingly, details are not described herein.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of when being executed by processor
Point cloud sector domain is determined according to the coordinate of all the points in described cloud；
All the points in the domain of described cloud sector are converted to linear data structure to be stored in linear memory space；
According to three-dimensional rectangle frame, the target point in described cloud is determined in the linear memory space.
A kind of computer readable storage medium provided by the above embodiment is standby, implementing principle and technical effect and above-mentioned side
Method embodiment is similar, and details are not described herein.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
Each technical characteristic of above embodiments can be combined arbitrarily, for simplicity of description, not to above-described embodiment
In each technical characteristic it is all possible combination be all described, as long as however, the combination of these technical characteristics be not present lance
Shield all should be considered as described in this specification.
The several embodiments of the application above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the concept of this application, various modifications and improvements can be made, these belong to the protection of the application
Range.Therefore, the scope of protection shall be subject to the appended claims for the application patent.
Claims (10)
1. point methods are sought in a kind of cloud space, which is characterized in that the described method includes:
Point cloud sector domain is determined according to the coordinate of all the points in described cloud；
All the points in the domain of described cloud sector are converted to linear data structure to be stored in linear memory space；
According to three-dimensional rectangle frame, the target point in described cloud is determined in the linear memory space.
2. the method according to claim 1, wherein the coordinate according to all the points in described cloud determines a little
Cloud sector domain, comprising:
Obtain respectively maximum value in described cloud in the maximum value and minimum value and Y-coordinate axle of the X-coordinate axle of all the points and
Minimum value；
According in the maximum value of the X-coordinate axle and minimum value and the Y-coordinate axle maximum value and minimum value determine the point
Cloud sector domain.
3. method according to claim 1 or 2, which is characterized in that described to be converted to all the points in the domain of described cloud sector
Linear data structure is stored in linear memory space, comprising:
Described cloud sector domain is divided according to preset length and predetermined width, obtains multiple subregions；
Point in each subregion point is converted to linear data structure to be stored in the linear memory space.
4. according to the method described in claim 3, it is characterized in that, the point by each subregion point is converted to linearly
Data structure is stored in the linear memory space, comprising:
Determine that each subregion is corresponding in the linear memory space according to the number of each subregion midpoint cloud point
Regional scope；
According to preset order, the point in each subregion is converted into linear data structure and is stored in corresponding regional scope
In.
5. empty in the linear memory the method according to claim 1, wherein described according to three-dimensional rectangle frame
Between target point in described cloud of middle determination, comprising:
Obtain the rectangular area that the three-dimensional rectangle frame is mapped on X/Y plane；The X/Y plane characterization X-coordinate axle and Y-coordinate axle
The plane of composition；
The determining subregion overlapped with the rectangular area, obtains overlapping ranges；
According to the three-dimensional rectangle frame, the target point in described cloud is determined in the overlapping ranges.
6. according to the method described in claim 5, it is characterized in that, described according to the three-dimensional rectangle frame, in the overlapping model
Enclose the target point in described cloud of determination, comprising:
Obtain the coordinate section that the three-dimensional rectangle frame is mapped on Z coordinate axis；
Z coordinate in the overlapping ranges is belonged to the point in the coordinate section, the target point being determined as in described cloud.
7. according to the method described in claim 6, it is characterized in that, it is described Z coordinate in the overlapping ranges belonged to it is described
The point in coordinate section, is determined as before the target point in described cloud, the method also includes:
Point in the overlapping ranges is ranked up according to the sequence of Z coordinate from small to large.
8. a device is sought in a kind of cloud space, which is characterized in that described device includes:
First determining module determines point cloud sector domain for the coordinate according to all the points in described cloud；
Memory module is stored in linear memory space for all the points in the domain of described cloud sector to be converted to linear data structure
In；
Second determining module, for being determined in described cloud in the linear memory space according to the three-dimensional rectangle frame
Target point.
9. a kind of computer equipment, including memory and processor, the memory are stored with computer program, feature exists
In the step of processor realizes any one of claims 1 to 7 the method when executing the computer program.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
The step of method described in any one of claims 1 to 7 is realized when being executed by processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811600009.0A CN109697733A (en) | 2018-12-26 | 2018-12-26 | Point searching method and device in point cloud space, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811600009.0A CN109697733A (en) | 2018-12-26 | 2018-12-26 | Point searching method and device in point cloud space, computer equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109697733A true CN109697733A (en) | 2019-04-30 |
Family
ID=66232848
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811600009.0A Pending CN109697733A (en) | 2018-12-26 | 2018-12-26 | Point searching method and device in point cloud space, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109697733A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113269897A (en) * | 2021-07-19 | 2021-08-17 | 深圳市信润富联数字科技有限公司 | Method, device and equipment for acquiring surface point cloud and storage medium |
| CN113836095A (en) * | 2021-09-26 | 2021-12-24 | 广州极飞科技股份有限公司 | Point cloud data storage method and device, storage medium and electronic equipment |
| WO2022017147A1 (en) * | 2020-07-22 | 2022-01-27 | 上海商汤临港智能科技有限公司 | Point cloud data processing method and apparatus, radar apparatus, electronic device, and computer readable storage medium |
| CN115857836A (en) * | 2023-02-10 | 2023-03-28 | 中南大学湘雅医院 | Information storage method and device based on big data |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103489224A (en) * | 2013-10-12 | 2014-01-01 | 厦门大学 | Interactive three-dimensional point cloud color editing method |
| CN103745459A (en) * | 2013-12-26 | 2014-04-23 | 西安交通大学 | Detection method of an unstructured point cloud feature point and extraction method thereof |
| US8982118B2 (en) * | 2011-11-22 | 2015-03-17 | Raytheon Company | Structure discovery in a point cloud |
| CN104731984A (en) * | 2015-04-22 | 2015-06-24 | 山东理工大学 | Incremental clustering optimization solution method for splitting problems of overflow nodes of R trees |
| US9300841B2 (en) * | 2012-06-25 | 2016-03-29 | Yoldas Askan | Method of generating a smooth image from point cloud data |
| CN106095968A (en) * | 2016-06-20 | 2016-11-09 | 山东理工大学 | The R tree-like position multiple target node split method of n dimension massive point cloud |
| CN106156281A (en) * | 2016-06-25 | 2016-11-23 | 南京理工大学 | Arest neighbors point set method for quickly retrieving based on Hash Cube spatial level partition structure |
| CN106530380A (en) * | 2016-09-20 | 2017-03-22 | 长安大学 | Ground point cloud segmentation method based on three-dimensional laser radar |
| US20180074755A1 (en) * | 2016-09-13 | 2018-03-15 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Data processing method and apparatus |
| CN109074660A (en) * | 2015-12-31 | 2018-12-21 | Ml 荷兰公司 | The method and system of monocular camera real-time three-dimensional capture and immediate feedback |
-
2018
- 2018-12-26 CN CN201811600009.0A patent/CN109697733A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8982118B2 (en) * | 2011-11-22 | 2015-03-17 | Raytheon Company | Structure discovery in a point cloud |
| US9300841B2 (en) * | 2012-06-25 | 2016-03-29 | Yoldas Askan | Method of generating a smooth image from point cloud data |
| US20160292829A1 (en) * | 2012-06-25 | 2016-10-06 | Yoldas Askan | Method of generating a smooth image from point cloud data |
| CN103489224A (en) * | 2013-10-12 | 2014-01-01 | 厦门大学 | Interactive three-dimensional point cloud color editing method |
| CN103745459A (en) * | 2013-12-26 | 2014-04-23 | 西安交通大学 | Detection method of an unstructured point cloud feature point and extraction method thereof |
| CN104731984A (en) * | 2015-04-22 | 2015-06-24 | 山东理工大学 | Incremental clustering optimization solution method for splitting problems of overflow nodes of R trees |
| CN109074660A (en) * | 2015-12-31 | 2018-12-21 | Ml 荷兰公司 | The method and system of monocular camera real-time three-dimensional capture and immediate feedback |
| CN106095968A (en) * | 2016-06-20 | 2016-11-09 | 山东理工大学 | The R tree-like position multiple target node split method of n dimension massive point cloud |
| CN106156281A (en) * | 2016-06-25 | 2016-11-23 | 南京理工大学 | Arest neighbors point set method for quickly retrieving based on Hash Cube spatial level partition structure |
| US20180074755A1 (en) * | 2016-09-13 | 2018-03-15 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Data processing method and apparatus |
| CN106530380A (en) * | 2016-09-20 | 2017-03-22 | 长安大学 | Ground point cloud segmentation method based on three-dimensional laser radar |
Non-Patent Citations (7)
| Title |
|---|
| CHUNKANG ZHANG, XUESHENG ZHAO: ""A Rasterizing Massive LiDAR Points Cloud Algorithm Based on Triangle Driver"", 《IEEE》 * |
| 周胜川: ""大规模城市场景图形图像混合建模与视觉无损渲染技术 "", 《万方》 * |
| 唐林: ""三维点云数据精简与压缩的研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 张会霞: ""三维激光扫描点云数据组织与可视化研究"", 《中国博士学位论文全文数据库 信息科技辑》 * |
| 李建松等: "《地理信息系统原理》", 31 January 2015, 武汉大学出版社 * |
| 王雷: ""海量三维激光点云数据的组织与可视化研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 陆锋等: ""一种基于Hilbert排列码的GIS空间索引方法"", 《计算机辅助设计与图形学学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022017147A1 (en) * | 2020-07-22 | 2022-01-27 | 上海商汤临港智能科技有限公司 | Point cloud data processing method and apparatus, radar apparatus, electronic device, and computer readable storage medium |
| CN113269897A (en) * | 2021-07-19 | 2021-08-17 | 深圳市信润富联数字科技有限公司 | Method, device and equipment for acquiring surface point cloud and storage medium |
| CN113269897B (en) * | 2021-07-19 | 2021-11-09 | 深圳市信润富联数字科技有限公司 | Method, device and equipment for acquiring surface point cloud and storage medium |
| CN113836095A (en) * | 2021-09-26 | 2021-12-24 | 广州极飞科技股份有限公司 | Point cloud data storage method and device, storage medium and electronic equipment |
| CN115857836A (en) * | 2023-02-10 | 2023-03-28 | 中南大学湘雅医院 | Information storage method and device based on big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106651987B (en) | Paths planning method and device | |
| CN109697733A (en) | Point searching method and device in point cloud space, computer equipment and storage medium | |
| CN110221722B (en) | Picture processing method, electronic device and storage medium | |
| CN111192352B (en) | Map rendering method, map rendering device, computer equipment and storage medium | |
| US20230338842A1 (en) | Rendering processing method and electronic device | |
| CN110390679A (en) | Image processing method, computer equipment and readable storage medium storing program for executing | |
| CN104142776A (en) | Icon processing method and device | |
| CN112583620A (en) | Network topology map generation method and device, electronic equipment and storage medium | |
| KR20130097886A (en) | Apparatus and method for rendering | |
| CN109407955B (en) | User interface interaction method, computer device and computer readable storage medium | |
| CN104991695A (en) | Information processing method and electronic equipment | |
| CN105989075A (en) | Method, device and system for displaying image by browser | |
| CN110378948B (en) | 3D model reconstruction method and device and electronic equipment | |
| CN108986031B (en) | Image processing method, device, computer equipment and storage medium | |
| CN113724364B (en) | Setting method and device for realizing shielding and rendering-free body by utilizing polygons | |
| US20150229848A1 (en) | Method and system for generating an image including optically zoomed and digitally zoomed regions | |
| CN104777981A (en) | Information fast sharing method and device | |
| CN107038176B (en) | Method, device and equipment for rendering web graph page | |
| Rüegg et al. | Using one-dimensional compaction for smaller graph drawings | |
| CN114022518A (en) | Method, device, equipment and medium for acquiring optical flow information of image | |
| CN116527908B (en) | Motion field estimation method, motion field estimation device, computer device and storage medium | |
| WO2024067202A1 (en) | Image extension method and apparatus, storage medium, and electronic device | |
| CN113436325B (en) | Image processing method and device, electronic equipment and storage medium | |
| CN115658351B (en) | 2D copying method, device, electronic equipment and computer readable storage medium | |
| US9978117B2 (en) | Semiconductor apparatus and high speed image data processing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190430 |
|
| RJ01 | Rejection of invention patent application after publication |