CN110457407B - Method and apparatus for processing point cloud data - Google Patents
Method and apparatus for processing point cloud data Download PDFInfo
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Abstract
The embodiment of the application discloses a method and a device for processing point cloud data. One embodiment of the method comprises: acquiring a road map, and determining map range information representing a range occupied by the road map in a preset map comprising the road map; acquiring target point cloud data, and determining point position information of corresponding points of the target point cloud data in a preset map based on coordinate values included in the target point cloud data; determining whether the position of the corresponding point is located in the road map based on the point position information and the map range information; in response to determining to be located within the road map, determining whether a location of the corresponding point is located within a target area in the road map based on the point location information; in response to determining to be located within the target area, the target point cloud data is deleted. The embodiment improves the accuracy of filtering the point cloud data and improves the flexibility of processing the point cloud data.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a method and a device for processing point cloud data.
Background
Point cloud filtering is an important step in the processing process of three-dimensional point cloud data, and can divide points into ground points and non-ground points (such as buildings, trees and the like). The point cloud filtering has important significance for improving the real-time performance and accuracy of point cloud calculation. The existing point cloud filtering method mainly comprises straight-through filtering, voxel filtering and the like, or clustering point clouds firstly and filtering out point cloud data of specific categories according to an actual application scene.
Disclosure of Invention
The embodiment of the application provides a method and a device for processing point cloud data.
In a first aspect, an embodiment of the present application provides a method for processing point cloud data, the method including: acquiring a road map, and determining map range information representing a range occupied by the road map in a preset map comprising the road map; acquiring target point cloud data, and determining point position information of corresponding points of the target point cloud data in a preset map based on coordinate values included in the target point cloud data; determining whether the position of the corresponding point is located in the road map based on the point position information and the map range information; in response to determining to be located within the road map, determining whether a location of the corresponding point is located within a target area in the road map based on the point location information; in response to determining to be located within the target area, the target point cloud data is deleted.
In some embodiments, determining map range information characterizing a range that a road map occupies in a preset map including the road map comprises: acquiring coordinate information of a road map in a preset map; determining a road map as a grid map consisting of grids with preset sizes; determining a serial number of a grid included in the grid map based on the coordinate information; the determined sequence number is determined as map range information representing a range that the road map occupies in a preset map including the road map.
In some embodiments, determining the point position information of the corresponding point of the target point cloud data in the preset map based on the coordinate value included in the target point cloud data includes: determining the coordinate value of the corresponding point of the target point cloud data in a preset map based on the coordinate value included by the target point cloud data; determining grid serial numbers of the corresponding points in the grid map based on the determined coordinate values and the preset size; and determining the grid serial number as the point position information of the corresponding point of the target point cloud data in a preset map.
In some embodiments, determining whether the location of the corresponding point is located within the road map based on the point location information and the map range information includes: determining whether the grid serial number is included in the serial numbers of the grids included in the grid map; in response to determining, it is determined that the location of the corresponding point is within the road map.
In some embodiments, determining whether the location of the corresponding point is within the target area in the road map based on the point location information includes: determining the serial number of a grid contained in a target area in a road map; and in response to determining that the grid serial number is included in the grid serial numbers included in the target area, determining that the position of the corresponding point is located in the target area.
In some embodiments, the predetermined map is a predetermined three-dimensional point cloud map, and the road map is a map area extracted from the three-dimensional point cloud map and including point clouds within a predetermined coordinate range.
In a second aspect, an embodiment of the present application provides an apparatus for processing point cloud data, the apparatus including: a first acquisition unit configured to acquire a road map and determine map range information representing a range that the road map occupies in a preset map including the road map; a second acquisition unit configured to acquire the target point cloud data and determine point position information of a corresponding point of the target point cloud data in a preset map based on a coordinate value included in the target point cloud data; a first determination unit configured to determine whether a position of a corresponding point is located within a road map based on the point position information and the map range information; a second determination unit configured to determine, in response to determining to be located within the road map, whether a position of the corresponding point is located within a target area in the road map based on the point position information; a deletion unit configured to delete the target point cloud data in response to determining that the target point cloud data is located within the target area.
In some embodiments, the first obtaining unit includes: the acquisition module is configured to acquire coordinate information of a road map in a preset map; a first determination module configured to determine a road map as a grid map composed of grids of a preset size; a second determination module configured to determine a serial number of a grid included in the grid map based on the coordinate information; a third determination module configured to determine the determined sequence number as map range information representing a range occupied by the road map in a preset map including the road map.
In some embodiments, the second acquisition unit comprises: a fourth determining module configured to determine a coordinate value of a corresponding point of the target point cloud data in the preset map based on the coordinate value included in the target point cloud data; a fifth determining module configured to determine a grid serial number of the corresponding point in the grid map based on the determined coordinate value and a preset size; and the sixth determining module is configured to determine the grid serial number as the point position information of the corresponding point of the target point cloud data in the preset map.
In some embodiments, the first determination unit comprises: a seventh determining module configured to determine whether a grid serial number is included in the serial numbers of the grids included in the grid map; an eighth determination module configured to determine, in response to the determining comprising, that the location of the corresponding point is within the road map.
In some embodiments, the second determining unit comprises: a ninth determining module configured to determine a serial number of a grid included in a target area in a road map; and the tenth determining module is configured to determine that the position of the corresponding point is located in the target area in response to determining that the grid serial number is included in the serial numbers of the grids included in the target area.
In some embodiments, the predetermined map is a predetermined three-dimensional point cloud map, and the road map is a map area extracted from the three-dimensional point cloud map and including point clouds within a predetermined coordinate range.
In a third aspect, an embodiment of the present application provides a terminal device, where the terminal device includes: one or more processors; storage means for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method as described in any implementation of the first aspect.
In a fourth aspect, the present application provides a computer-readable medium, on which a computer program is stored, which, when executed by a processor, implements the method as described in any implementation manner of the first aspect.
According to the method and the device for processing the point cloud data, the map range information representing the position of the road map in the preset map and the point position information of the target point cloud data are analyzed, whether the corresponding point of the target point cloud data in the preset map is located in the target area of the road map is determined, and if the corresponding point of the target point cloud data in the preset map is located in the target area, the target point cloud data are deleted, so that the accuracy of filtering the point cloud data is improved, and the flexibility of processing the point cloud data is improved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of a method for processing point cloud data according to the present application;
FIG. 3 is a schematic diagram of one application scenario of a method for processing point cloud data according to the present application;
FIG. 4 is a flow diagram of yet another embodiment of a method for processing point cloud data according to the present application;
FIG. 5 is an exemplary schematic diagram of a grid map for a method of processing point cloud data according to the present application;
FIG. 6 is a schematic diagram of an arrangement of an embodiment of an apparatus for processing point cloud data according to the present application;
fig. 7 is a schematic structural diagram of a computer system suitable for implementing a terminal device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 illustrates an exemplary system architecture 100 to which the method for processing point cloud data or the apparatus for processing point cloud data of embodiments of the present application may be applied.
As shown in fig. 1, system architecture 100 may include a vehicle 101, a network 102, and a server 103. The vehicle 101 is provided with a point cloud data acquisition device 1011 (such as a laser radar, a stereo camera, etc.) and a terminal device 1012 (such as a vehicle-mounted computer, a navigator, etc.), and the point cloud data acquisition device 1011 and the terminal device 1012 establish communication connection in a wired or wireless manner. Network 102 is the medium used to provide communication links between terminal devices 1012 and server 103.
A user may use terminal device 1012 to interact with server 103 over network 102 to receive or send messages and the like. Various communication client applications, such as an electronic map application, a data processing application, and the like, may be installed on the terminal device 1012.
The terminal device 1012 may be hardware or software. When the terminal device 1012 is hardware, it may be various electronic devices having a display screen and supporting electronic map display, including but not limited to a car computer, a navigator, a smart phone, a tablet computer, a laptop portable computer, and the like. When the terminal device 1012 is software, it can be installed in the electronic devices listed above. It may be implemented as multiple pieces of software or software modules (e.g., software or software modules used to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 103 may be a server that provides various services, such as a background map server that provides support for an electronic map displayed on the terminal device 1012. The background map server may provide various types of electronic maps (e.g., two-dimensional planar maps, three-dimensional point cloud maps, etc.) for the terminal device 1012.
It should be noted that the method for processing point cloud data provided by the embodiment of the present application is generally executed by the terminal device 1012, and accordingly, the apparatus for processing point cloud data is generally disposed in the terminal device 1012.
The server 103 may be hardware or software. When the server 103 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 103 is software, it may be implemented as multiple pieces of software or software modules (e.g., software or software modules for providing distributed services) or as a single piece of software or software module. And is not particularly limited herein.
It should be understood that the number of vehicles, point cloud data collection devices, terminal devices, networks, and servers in fig. 1 are merely illustrative. Any number of vehicles, point cloud data acquisition devices, terminal devices, networks, and servers may be present as desired. The system architecture 100 may not include the server 103 in the event that the electronic map required by the terminal device does not need to be obtained from a remote location.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for processing point cloud data in accordance with the present application is shown. The method for processing point cloud data comprises the following steps:
In the present embodiment, an execution subject (e.g., a terminal device shown in fig. 1) of the method for processing point cloud data may acquire a road map from a remote place or a local place through a wired connection manner or a wireless connection manner, and determine map range information representing a range occupied by the road map in a preset map including the road map. The road map may be included in a preset map. The preset map may be an electronic map that the execution subject previously obtained from a remote location (e.g., the server shown in fig. 1) or from a local location. As an example, the electronic map may be used for navigation, and the road map may be a navigation image displayed in real time on the display screen of the execution subject, the navigation image including an image of a road. It should be noted that the preset map may be a three-dimensional map or a two-dimensional map.
In this implementation, the map range information may include coordinates of each corner point of the road map. For example, the map range information is "(x 0, y0), (x1, y1), (x2, y2), (x3, y 3)", where (x0, y0) is the lower left-hand coordinate of the road map, (x1, y1) is the lower right-hand coordinate of the road map, (x2, y2) is the upper left-hand coordinate of the road map, and (x3, y3) is the upper right-hand coordinate of the road map. It should be understood that when the preset map is a three-dimensional map, the coordinates of the respective points in the above-described map range information may not include coordinates on the coordinate axis representing the height.
Optionally, the map range information may further include coordinates of one of the corner points of the road map and a length and a width of the road map. For example, the map range information may be "(x 0, y0), L, W", where (x0, y0) is the lower left corner coordinate of the road map, L is the lateral length of the road map, and W is the longitudinal width of the road map.
In some optional implementations of the embodiment, the preset map may be a preset three-dimensional point cloud map, and accordingly, the road map may be a map area extracted from the three-dimensional point cloud map and including point clouds in a preset coordinate range. As an example, the point cloud data may include three-dimensional coordinate values (x, y, z), where the three-dimensional coordinate values are coordinate values of corresponding points of the point cloud data in a preset map in a preset three-dimensional rectangular coordinate system, and the preset coordinate range may be a preset height (i.e., z value) range, and the point cloud data in the height range may be used for characterizing a road. The road map may be a rectangular area containing projected points of corresponding points of the point cloud data within the height range on a plane composed of the x-axis and the y-axis in the three-dimensional point cloud map.
In this embodiment, the executing entity may obtain the target point cloud data, and determine the point position information of the corresponding point of the target point cloud data in the preset map based on the coordinate value included in the target point cloud data. Generally, the coordinate value included in the target point cloud data may be a coordinate value of a corresponding point of the target point cloud data in a preset map, or may be an initial coordinate value of the target point cloud data in a coordinate system using the point cloud data acquisition device shown in fig. 1 as a coordinate origin, and the initial coordinate value of the target point cloud data may be converted into a coordinate value of the corresponding point in the preset map by coordinate value conversion (for example, the coordinate value of the corresponding point in the preset map may be a longitude and latitude value, and coordinate value conversion is performed according to the longitude and latitude value of the point cloud data acquisition device and the initial coordinate value of the target point cloud data).
The point position information can be used for representing the position of a corresponding point of the target point cloud data in a preset map. As an example, the point position information may be coordinate values of the corresponding points in a preset map, and may also be information representing a grid area of a preset size containing the corresponding points. It should be understood that, when the preset map is a three-dimensional map, the coordinate values of the corresponding points in the preset map may be three-dimensional coordinate values or two-dimensional coordinate values (for example, coordinate values excluding coordinate values representing height), and accordingly, the grid region may be a three-dimensional grid region or a two-dimensional grid region.
In the present embodiment, based on the map range information acquired in step 201 and the point position information determined in step 202, the execution subject may determine whether the position of the corresponding point described above is located within the road map based on the point position information and the map range information. As an example, assume that the map range information is "(x 0, y0), L1, W1", where (x0, y0) is the lower left corner coordinate of the road map, L1 is the lateral length of the road map, and W1 is the longitudinal width of the road map. Assuming that the point position information is "(x 1, y 1)", where (x1, y1) are coordinate values of corresponding points of the target point cloud data in a preset map, if x0 ≦ x1 ≦ x0+ L1 and y0 ≦ y1 ≦ y0+ W1, it is determined that the positions of the corresponding points are located within the road map.
In response to determining that the location is within the road map, a determination is made as to whether the location of the corresponding point is within a target area in the road map based on the point location information, step 204.
In this embodiment, the execution body may determine whether the position of the corresponding point is located within the target area in the road map based on the point position information in response to determining that the position of the corresponding point is located within the road map. The target area may be a map area preset in the road map, and for example, if the road map includes a lane image, a sidewalk image, and a green belt image, the target area may be the lane image. Continuing with the example of step 203, assume that the information used to characterize the target region is "(x 2, y2), L2, W2", where (x2, y2) is the lower left corner coordinate of the target region, L2 is the lateral length of the target region, and W2 is the longitudinal width of the target region. And if x2 is not less than x1 not less than x2+ L2 and y2 not less than y1 not less than y2+ W2, determining that the position of the corresponding point is positioned in the target area.
In this implementation, the executing agent may delete the target point cloud data in response to determining that the executing agent is located within the target area. As an example, assuming that the target area represents a lane area on a road, when the vehicle shown in fig. 1 travels on the lane, other vehicles are still present on the lane, and the executing entity may delete the point cloud data representing the positions of the other vehicles, so that a determination error of the surroundings of the vehicle due to the executing entity determining the other vehicles as obstacles may be avoided, thereby improving the accuracy of road recognition based on the point cloud data.
With continued reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the method for processing point cloud data according to the present embodiment. In the application scenario of fig. 3, a terminal device 301 is provided on a vehicle traveling on a road, and a road map 302 is displayed on the screen of the terminal device 301 in real time. Wherein, the icon 3021 represents the current driving position of the vehicle, and 3022-3025 represent the green belt, the left lane, the right lane and the sidewalk on the road respectively. The terminal device 301 first determines map range information (e.g., coordinate values of four intersections of a road map) representing a range that the road map 302 occupies in a preset map (e.g., an electronic map for navigation). Then, the terminal device 301 acquires target point cloud data (point cloud data represented by a dot 3026 in fig. 3), and determines point position information (e.g., coordinate values of a corresponding point) of the target point cloud data in a preset map. Next, the terminal apparatus 301 determines whether the position of the corresponding point is located within the target area (such as the left lane 3023 and the right lane 3024 in fig. 3) in the road map in response to determining that the position of the corresponding point is located within the road map 302. Finally, the terminal device 301 deletes the target point cloud data in response to determining that the corresponding point is located within the target area. By performing the above steps multiple times, the terminal device 301 may delete the point cloud data of which the corresponding point is located inside the target area, and retain the point cloud data of which the corresponding point is located outside the target area.
According to the method provided by the embodiment of the application, the map range information representing the position of the road map in the preset map and the point position information of the target point cloud data are analyzed to determine whether the corresponding point of the target point cloud data in the preset map is located in the target area of the road map, and if the corresponding point of the target point cloud data in the preset map is located in the target area, the target point cloud data are deleted, so that the accuracy of filtering the point cloud data is improved, and the flexibility of processing the point cloud data is improved.
With further reference to FIG. 4, a flow 400 of yet another embodiment of a method for processing point cloud data is illustrated. The process 400 of the method for processing point cloud data includes the steps of:
In the present embodiment, an electronic device (for example, a terminal device shown in fig. 1) on which the method for processing point cloud data operates may acquire a road map from a remote place or a local place through a wired connection manner or a wireless connection manner, and acquire coordinate information of the road map in a preset map. The road map may be included in a preset map. The coordinate information may be used to represent the position of the road map on the preset map, for example, the coordinate information may be coordinates of each corner point of the road map within the preset map. As an example, the preset map may be an electronic map that the execution subject previously acquired from a remote (e.g., a server shown in fig. 1) or from a local, which may be used for navigation. The road map may be a navigation image including an image of a road displayed in real time on the display screen of the execution subject. It should be noted that the preset map may be a three-dimensional map or a two-dimensional map.
In this embodiment, the execution body may divide the road map to obtain a grid map composed of grids with a preset size. It should be noted that, when the preset map is a three-dimensional map, the road map may be a map obtained by projecting the three-dimensional road map onto a two-dimensional plane, and accordingly, the grid map is a two-dimensional grid map.
In this embodiment, the execution body may determine a number of a grid included in the grid map based on the coordinate information. As an example, the execution subject may calculate the maximum value of the number of the grid according to the following formula:
I max ＝(x max -x min )/r+[(y max -y min )/r]×L (1)，
wherein, I max Is the maximum value of the number of the grid, x max 、x min The maximum coordinate value and the minimum coordinate value, y, of the grid map on the x-axis of the preset map max 、y min The maximum coordinate value and the minimum coordinate value of the grid map on the y axis in the preset map are respectively shown, r is the side length of a single square grid, and L is the number of grids in each line in the grid map. Wherein (x) max -x min ) R and (y) max -y min ) The results obtained for/r retain the integer part respectively.
As an example, as shown in fig. 5, assuming that r is 1 meter and L is 4 (including incomplete grids), the number of each grid included in the grid map 501 is 0 to 19.
In step 404, the determined sequence number is determined as map range information representing a range occupied by the road map in a preset map including the road map.
In the present embodiment, based on the sequence number determined in step 403, the execution main body may determine the determined sequence number as map range information representing a range that the road map occupies in the preset map including the road map. Continuing with the example shown in FIG. 5, the map range information may be the various serial numbers determined, i.e., 0-19.
In this embodiment, the executing body may obtain the target point cloud data, and determine the coordinate value of the corresponding point of the target point cloud data in the preset map based on the coordinate value included in the target point cloud data. In general, the coordinate value included in the target point cloud data may be a coordinate value of a corresponding point of the target point cloud data in a preset map, or may be an initial coordinate value of the target point cloud data in a coordinate system using the point cloud data acquisition device shown in fig. 1 as a coordinate origin, and the initial coordinate value of the target point cloud data may be converted into a coordinate value of the corresponding point in the preset map by coordinate value conversion (for example, coordinate value conversion is performed according to a longitude and latitude value of the point cloud data acquisition device and the initial coordinate value of the target point cloud data).
And step 406, determining the grid serial number of the corresponding point in the grid map based on the determined coordinate value and the preset size.
In this embodiment, the execution body may determine the grid number of the corresponding point in the grid map based on the determined coordinate value and the preset size. As an example, the grid number of the corresponding point of the target point cloud data in the grid map may be calculated by the following formula:
I＝(x-x min )/r+[(y-y min )/r]×L (2)，
wherein, I is the grid serial number of the corresponding point of the target point cloud data, x and y are the x-axis coordinate and the y-axis coordinate of the corresponding point of the target point cloud data in the grid map respectively, and x and y are the coordinates of the corresponding point of the target point cloud data in the grid map min 、y min The minimum coordinate value of the grid map on the x axis and the minimum coordinate value of the grid map on the y axis in the preset map are respectively shown, r is the side length of a single square grid, and L is the number of grids in each line of the grid map. Wherein, (x-x) min ) R and (y-y) min ) The results obtained for/r retain the integer part respectively.
Continuing with the example shown in FIG. 5, assume the origin of coordinates (x) of the grid map min ,y min ) If the coordinates of the corresponding point 502 of the target point cloud data in the grid map 501 are (0, 0) and (2.5,3.5), the grid number of the corresponding point 502 of the target point cloud data is 14.
In this embodiment, the executing entity may determine the grid serial number determined in step 406 as the point position information of the corresponding point of the target point cloud data in the preset map. Continuing with the example shown in fig. 5, the point location information of the corresponding point at which the target point cloud data is located may be set to a value of 14. Through the steps, the information of the position of the representation point can be converted into a one-dimensional serial number from a two-dimensional coordinate, so that the storage space can be saved, and the complexity of processing point cloud data is reduced.
In this embodiment, step 408 is substantially the same as step 203 in the corresponding embodiment of fig. 2, and is not described herein again.
In some optional implementations of this embodiment, the executing entity may determine whether the position of the corresponding point is located in the road map according to the following steps:
first, it is determined whether a grid number is included in the number numbers of the grids included in the grid map. Then, in response to determining, including, determining that the location of the corresponding point is within the road map. Continuing with the example shown in fig. 5, if the grid number of the corresponding point of the target point cloud data is 14, which is smaller than the maximum value 19 of the grid numbers in the grid map, it is determined that the position of the corresponding point of the target point cloud data is located in the road map.
In response to determining that the location is within the road map, step 409 determines whether the location of the corresponding point is within a target area in the road map based on the point location information.
In this embodiment, step 409 is substantially the same as step 204 in the corresponding embodiment of fig. 2, and is not described herein again.
In some optional implementations of the embodiment, the executing entity may determine whether the position of the corresponding point is located in the target area in the road map according to the following steps: first, the number of grids included in a target area in a road map is determined. Then, in response to determining that the number of the grid included in the target area includes the grid number, it is determined that the position of the corresponding point is located within the target area. Continuing with the example shown in fig. 5, assuming that the target area 503 is used to characterize a lane, the number of grids included in the target area is calculated as follows by using the above formula 2: 1. 2, 5, 6, 9, 10, 13, 14, 17, 18 including the serial number 14 of the grid where the corresponding point 502 of the target point cloud data is located, it is determined that the position of the corresponding point of the target point cloud data is located in the target area.
At step 410, in response to determining that the target point cloud data is located within the target area, the target point cloud data is deleted.
In this embodiment, step 410 is substantially the same as step 205 in the corresponding embodiment of fig. 2, and is not described herein again.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the method for processing point cloud data in the present embodiment highlights the step of determining the road map as the grid map, and the step of determining whether the corresponding point of the target point cloud data in the preset map is located within the target area based on the grid map. Therefore, the scheme described by the embodiment can filter the point cloud data more quickly, and the flexibility of processing the point cloud data is increased.
With further reference to fig. 6, as an implementation of the methods shown in the above-mentioned figures, the present application provides an embodiment of an apparatus for processing point cloud data, which corresponds to the method embodiment shown in fig. 2, and which can be applied to various electronic devices.
As shown in fig. 6, the apparatus 600 for processing point cloud data of the present embodiment includes: a first acquisition unit 601 configured to acquire a road map and determine map range information representing a range that the road map occupies in a preset map including the road map; a second obtaining unit 602 configured to obtain the target point cloud data, and determine point position information of a corresponding point of the target point cloud data in a preset map based on a coordinate value included in the target point cloud data; a first determination unit 603 configured to determine whether the position of the corresponding point is located within the road map based on the point position information and the map range information; a second determination unit 604 configured to determine whether a position of the corresponding point is located within a target area in the road map based on the point position information in response to the determination of being located within the road map; a deletion unit 605 configured to delete the target point cloud data in response to determining to be located within the target area.
In the present embodiment, the first acquisition unit 601 may acquire the road map from a remote place or from a local place by a wired connection manner or a wireless connection manner, and determine map range information representing a range occupied by the road map in a preset map including the road map. The road map may be included in a preset map. The preset map may be an electronic map that is acquired by the first acquisition unit 601 from a remote location (e.g., the server shown in fig. 1) or from a local location in advance. In this implementation, the map range information may include coordinates of each corner point of the road map. Optionally, the map range information may further include coordinates of one of the corner points of the road map and a length and a width of the road map.
In this embodiment, the second obtaining unit 602 may obtain the target point cloud data, and determine the point position information of the corresponding point of the target point cloud data in the preset map based on the coordinate value included in the target point cloud data. Generally, the coordinate value included in the target point cloud data may be a coordinate value of a corresponding point of the target point cloud data in a preset map, or may be an initial coordinate value of the target point cloud data in a coordinate system using the point cloud data acquisition device shown in fig. 1 as a coordinate origin, and the initial coordinate value of the target point cloud data may be converted into a coordinate value of the corresponding point in the preset map by coordinate value conversion (for example, the coordinate value of the corresponding point in the preset map may be a longitude and latitude value, and coordinate value conversion is performed according to the longitude and latitude value of the point cloud data acquisition device and the initial coordinate value of the target point cloud data). The point position information can be used for representing the position of a corresponding point of the target point cloud data in a preset map. As an example, the point position information may be coordinate values of the corresponding points in a preset map, and may also be information representing a grid area of a preset size containing the corresponding points.
In this embodiment, the first determination unit 603 may determine whether the position of the corresponding point is located within the road map based on the point position information and the map range information. As an example, assume that the map range information is "(x 0, y0), L1, W1", where (x0, y0) is the lower left corner coordinate of the road map, L1 is the lateral length of the road map, and W1 is the longitudinal width of the road map. Assuming that the point position information is "(x 1, y 1)", where (x1, y1) are coordinate values of corresponding points of the target point cloud data in a preset map, if x0 ≦ x1 ≦ x0+ L1 and y0 ≦ y1 ≦ y0+ W1, it is determined that the positions of the corresponding points are located within the road map.
In this embodiment, the second determination unit 604 may determine whether the position of the corresponding point is located within the target area in the road map based on the point position information in response to determining that the position of the corresponding point is located within the road map. The target area may be a map area preset in the road map, and for example, if the road map includes a lane image, a sidewalk image, and a green belt image, the target area may be the lane image. As an example, assume that the information used to characterize the target region is "(x 2, y2), L2, W2", where (x2, y2) is the lower left corner coordinate of the target region, L2 is the lateral length of the target region, and W2 is the longitudinal width of the target region. And if x2 is not less than x1 not less than x2+ L2 and y2 not less than y1 not less than y2+ W2, determining that the position of the corresponding point is positioned in the target area.
In this embodiment, the deletion unit 605 may delete the target point cloud data in response to determining that it is located within the target area. As an example, assuming that the target area represents a lane area on a road, when a truck appears in front of the vehicle as shown in fig. 1, the deleting unit 605 may delete the point cloud data representing the position of the truck, so as to avoid a wrong determination of the surrounding environment of the vehicle due to the device 600 determining the truck as an obstacle, thereby improving the accuracy of road recognition based on the point cloud data.
In some optional implementations of this embodiment, the first obtaining unit 601 may include: an acquisition module (not shown in the figure) configured to acquire coordinate information of a road map in a preset map; a first determination module (not shown in the drawings) configured to determine the road map as a grid map composed of grids of a preset size; a second determining module (not shown in the drawings) configured to determine a serial number of a grid included in the grid map based on the coordinate information; a third determination module (not shown in the drawings) configured to determine the determined sequence number as map range information representing a range occupied by the road map in a preset map including the road map.
In some optional implementations of this embodiment, the second obtaining unit 602 may include: a fourth determining module (not shown in the figures) configured to determine, based on the coordinate values included in the target point cloud data, coordinate values of corresponding points of the target point cloud data in a preset map; a fifth determining module (not shown in the figures) configured to determine a grid serial number of the corresponding point in the grid map based on the determined coordinate value and a preset size; and a sixth determining module (not shown in the figure) configured to determine the grid serial number as the point position information of the corresponding point of the target point cloud data in the preset map.
In some optional implementations of this embodiment, the first determining unit 603 may include: a seventh determining module (not shown in the drawings) configured to determine whether a grid serial number is included in the serial numbers of the grids included in the grid map; an eighth determining module (not shown in the figures) configured to determine, in response to a determination that comprises, that the location of the corresponding point is located within the road map.
In some optional implementations of this embodiment, the second determining unit 604 may include: a ninth determining module (not shown in the figure) configured to determine a serial number of a grid included in the target area in the road map; a tenth determining module (not shown in the figures) configured to determine that the position of the corresponding point is located within the target area in response to determining that the number of the grid included in the target area includes the grid number.
In some optional implementations of the embodiment, the preset map may be a preset three-dimensional point cloud map, and the road map may be a map area extracted from the three-dimensional point cloud map and including point clouds in a preset coordinate range.
According to the device provided by the embodiment of the application, the map range information representing the position of the road map in the preset map and the point position information of the target point cloud data are analyzed to determine whether the corresponding point of the target point cloud data in the preset map is located in the target area of the road map, and if the corresponding point of the target point cloud data in the preset map is located in the target area, the target point cloud data are deleted, so that the accuracy of filtering the point cloud data is improved, and the flexibility of processing the point cloud data is improved.
Referring now to FIG. 7, shown is a block diagram of a computer system 700 suitable for use in implementing a terminal device of an embodiment of the present application. The terminal device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a touch screen, keys, and the like; an output section 707 including a Liquid Crystal Display (LCD), a speaker, and the like; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program, when executed by a Central Processing Unit (CPU)701, performs the above-described functions defined in the method of the present application. It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable medium or any combination of the two. A computer readable medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this application, a computer readable medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first acquisition unit, a second acquisition unit, a first determination unit, a second determination unit, and a deletion unit. Where the names of these units do not constitute a limitation on the unit itself in some cases, for example, the first acquisition unit may also be described as a "unit that acquires a road map and determines map range information that characterizes a range that the road map occupies in a preset map including the road map".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the terminal device described in the above embodiments; or may exist separately without being assembled into the terminal device. The computer readable medium carries one or more programs which, when executed by the terminal device, cause the terminal device to: acquiring a road map, and determining map range information representing a range occupied by the road map in a preset map comprising the road map; acquiring target point cloud data, and determining point position information of corresponding points of the target point cloud data in a preset map based on coordinate values included in the target point cloud data; determining whether the position of the corresponding point is located in the road map based on the point position information and the map range information; in response to determining to be located within the road map, determining whether a location of the corresponding point is located within a target area in the road map based on the point location information; in response to determining to be located within the target area, the target point cloud data is deleted.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (14)
1. A method for processing point cloud data, comprising:
acquiring a road map, and determining map range information representing a range occupied by the road map in a preset map comprising the road map, wherein the map range information comprises a grid serial number included in a grid map, and the grid map is determined based on the road map;
acquiring target point cloud data, and determining point position information of corresponding points of the target point cloud data in the preset map based on coordinate values included in the target point cloud data;
determining whether the position of the corresponding point is located within the road map based on the point position information and the map range information;
in response to determining to be located within the road map, determining whether a location of the corresponding point is located within a target area in the road map based on the point location information;
deleting the target point cloud data in response to determining to be located within the target area.
2. The method of claim 1, wherein the determining map range information characterizing a range occupied by the road map in a preset map including the road map comprises:
acquiring coordinate information of the road map in a preset map;
determining the road map as a grid map consisting of grids of a preset size;
determining a serial number of a grid included in the grid map based on the coordinate information;
and determining the determined sequence number as map range information representing a range occupied by the road map in a preset map including the road map.
3. The method of claim 2, wherein the determining point position information of the corresponding point of the target point cloud data in the preset map based on the coordinate values included in the target point cloud data comprises:
determining coordinate values of corresponding points of the target point cloud data in the preset map based on the coordinate values included by the target point cloud data;
determining a grid serial number of the corresponding point in the grid map based on the determined coordinate value and the preset size;
and determining the grid serial number as the point position information of the corresponding point of the target point cloud data in the preset map.
4. The method of claim 3, wherein the determining whether the location of the corresponding point is within the road map based on the point location information and the map range information comprises:
determining whether the grid serial number is included in the serial numbers of the grids included in the grid map;
determining, in response to determining, comprises determining that the location of the corresponding point is within the road map.
5. The method of claim 4, wherein the determining whether the location of the corresponding point is within a target area in the road map based on the point location information comprises:
determining the serial number of a grid contained in a target area in the road map;
and in response to determining that the grid serial number is included in the serial numbers of the grids included in the target area, determining that the position of the corresponding point is located in the target area.
6. The method according to one of claims 1 to 5, wherein the predetermined map is a predetermined three-dimensional point cloud map, and the road map is a map area extracted from the three-dimensional point cloud map and containing point clouds in a predetermined coordinate range.
7. An apparatus for processing point cloud data, comprising:
a first acquisition unit configured to acquire a road map, and determine map range information representing a range that the road map occupies in a preset map including the road map, wherein the map range information includes a grid number included in a grid map determined based on the road map;
a second acquisition unit configured to acquire target point cloud data and determine point position information of a corresponding point of the target point cloud data in the preset map based on a coordinate value included in the target point cloud data;
a first determination unit configured to determine whether the position of the corresponding point is located within the road map based on the point position information and the map range information;
a second determination unit configured to determine whether the position of the corresponding point is located within a target area in the road map based on the point position information in response to determining that the corresponding point is located within the road map;
a deletion unit configured to delete the target point cloud data in response to determining that the target point cloud data is located within the target area.
8. The apparatus of claim 7, wherein the first obtaining unit comprises:
the acquisition module is configured to acquire coordinate information of the road map in a preset map;
a first determination module configured to determine the road map as a grid map composed of grids of a preset size;
a second determination module configured to determine a serial number of a grid included in the grid map based on the coordinate information;
a third determination module configured to determine the determined sequence number as map range information representing a range occupied by the road map in a preset map including the road map.
9. The apparatus of claim 8, wherein the second obtaining unit comprises:
a fourth determination module configured to determine, based on the coordinate values included in the target point cloud data, coordinate values of corresponding points of the target point cloud data in the preset map;
a fifth determining module configured to determine a grid serial number of the corresponding point in the grid map based on the determined coordinate value and the preset size;
a sixth determining module configured to determine the grid sequence number as point position information of a corresponding point of the target point cloud data in the preset map.
10. The apparatus of claim 9, wherein the first determining unit comprises:
a seventh determining module configured to determine whether the grid serial number is included in serial numbers of grids included in the grid map;
an eighth determination module configured to determine that the location of the corresponding point is within the road map in response to determining that includes.
11. The apparatus of claim 10, wherein the second determining unit comprises:
a ninth determining module configured to determine a serial number of a grid included in a target area in the road map;
a tenth determining module configured to determine that the position of the corresponding point is located within the target area in response to determining that the grid serial number is included in the serial numbers of the grids included in the target area.
12. The apparatus according to one of claims 7 to 11, wherein the predetermined map is a predetermined three-dimensional point cloud map, and the road map is a map area extracted from the three-dimensional point cloud map and containing point clouds in a predetermined coordinate range.
13. A terminal device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
14. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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| CN112837346A (en) * | 2021-02-01 | 2021-05-25 | 意诺科技有限公司 | Method and device for detecting in-place of moving target |
| CN113466815A (en) * | 2021-06-29 | 2021-10-01 | 东软睿驰汽车技术（沈阳）有限公司 | Object identification method, device, equipment and storage medium |
| CN114036255B (en) * | 2022-01-07 | 2022-03-25 | 北京四维图新科技股份有限公司 | High-precision map data inspection method, device and equipment |
| CN116687564A (en) * | 2023-05-22 | 2023-09-05 | 北京长木谷医疗科技股份有限公司 | Surgical robot self-sensing navigation method system and device based on virtual reality |
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