CN116401326A

CN116401326A - Road identification updating method and device

Info

Publication number: CN116401326A
Application number: CN202111627400.1A
Authority: CN
Inventors: 徐达; 黄治凡; 何俊
Original assignee: Fengtu Technology Shenzhen Co Ltd
Current assignee: Fengtu Technology Shenzhen Co Ltd
Priority date: 2021-12-28
Filing date: 2021-12-28
Publication date: 2023-07-07

Abstract

The application provides a method and a device for updating a road identifier, wherein the method for updating the road identifier comprises the following steps: acquiring a plurality of first road pictures of a target road section; three-dimensional reconstruction is carried out on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section; acquiring the existing road identification information on the target road section; and updating the existing road identification information on the target road section according to the first point cloud information. The method and the device can improve the accuracy of the updating method of the road mark.

Description

Road identification updating method and device

Technical Field

The application relates to the technical field of map processing, in particular to a method and a device for updating road identifiers.

Background

Road signs such as traffic signs, street lamps and the like confirm that the existence state and the position of the road signs in a period of time have important values in map updating, road maintenance and the like. In the existing production process, the updating of the existing road mark is mainly completed manually, and the efficiency is low. Therefore, there are schemes that two-dimensional images are acquired through a vehicle, then map data are updated by utilizing the acquired two-dimensional images, the acquired two-dimensional image data are less, and road identifications are updated by using the two-dimensional images, so that an updating method of the road identifications is inaccurate.

That is, the accuracy of the updating method of the road mark in the prior art is low.

Disclosure of Invention

The application provides a method and a device for updating a road identifier, which aim to solve the problem of lower accuracy of the method for updating the road identifier.

In a first aspect, the present application provides a method for updating a road identifier, where the method for updating a road identifier includes:

acquiring a plurality of first road pictures of a target road section;

performing three-dimensional reconstruction on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section;

acquiring the existing road identification information on the target road section;

and updating the existing road identification information on the target road section according to the first point cloud information.

Optionally, the existing road identification information includes a plurality of existing road identifications and second point cloud information of each existing road identification, and the acquiring the existing road identification information on the target road section includes:

acquiring a plurality of second road pictures on a target road section, wherein the second road pictures are marked with road identification marking frames and categories of all existing road identifications;

performing three-dimensional reconstruction on the plurality of second road pictures to obtain third point cloud information of the target road section, wherein a coordinate system in which the third point cloud information is located is a bottom plate point cloud coordinate system;

Acquiring third point cloud information of each existing road identifier from the third point cloud information of the target road section according to the road identifier marking frame of each existing road identifier and the corresponding category;

clustering the third point cloud information of each type of existing road mark to obtain three-dimensional point cloud coordinates of the point cloud clustering center of each type of existing road mark on the bottom plate point cloud coordinate system;

and determining second point cloud information of each existing road identifier based on the three-dimensional point cloud coordinates of the point cloud cluster center of each existing road identifier.

Optionally, the determining the second point cloud information of each existing road identifier based on the three-dimensional point cloud coordinates of the point cloud clustering center of each existing road identifier includes:

acquiring a preset first coordinate conversion relation and actual geographic coordinates of centers of all the existing road marks under a geographic coordinate system;

converting the three-dimensional point cloud coordinates of the point cloud cluster centers of all the existing road identifications into a bottom plate point cloud coordinate system based on the first coordinate conversion relation to obtain converted geographic coordinates of the point cloud cluster centers;

if the distance between the converted geographic coordinates of the point cloud clustering center and the corresponding actual geographic coordinates of the center of the existing road mark is smaller than the first preset distance, determining the three-dimensional point cloud coordinates of the point cloud clustering center of the existing road mark as second point cloud information of the existing road mark.

Optionally, the obtaining the preset first coordinate transformation relation and the actual geographical coordinates of the centers of the existing road identifications under the geographical coordinate system includes:

acquiring target identification point cloud information of a target category road identification from third point cloud information of the target road section;

clustering the target identification point cloud information based on density to obtain clustering clusters corresponding to each target road identification in the target category road identifications;

determining three-dimensional point cloud coordinates of the target identification point under a bottom plate point cloud coordinate system according to the coordinates of each data point in each cluster;

obtaining geographic coordinates of a target identification point under a geographic coordinate system;

and determining a first coordinate conversion relation between the base plate point cloud coordinate system and the geographic coordinate coefficient based on the three-dimensional point cloud coordinates and the geographic coordinates of the target identification points.

Optionally, the determining, according to the coordinates of each data point in each cluster, the three-dimensional point cloud coordinates of the target identification point in the bottom plate point cloud coordinate system includes:

obtaining plane coordinates of a central point of a region with the maximum density in a target cluster;

sorting the data points in the target cluster according to the height value from large to small to obtain a plurality of sorted data points;

Determining the height coordinates of the target identification points under the bottom plate point cloud coordinate system based on the height values of the first preset number of data points which are ranked at the front;

and determining three-dimensional point cloud coordinates of the target identification point under a bottom plate point cloud coordinate system based on the plane coordinates and the height coordinates.

Optionally, the determining the first coordinate transformation relationship between the base plate point cloud coordinate system and the geographic coordinate coefficient based on the three-dimensional point cloud coordinate and the geographic coordinate of the target identification point includes:

obtaining a second preset number of target identification points from the plurality of target identification points to obtain a plurality of target identification point combinations;

nonlinear optimization is carried out on the three-dimensional point cloud coordinates and the geographic coordinates of each target identification point in each target identification point combination, and a second coordinate transformation relation between the three-dimensional point cloud coordinates and the geographic coordinates in each target identification point combination is obtained;

the first coordinate transformation relationship is determined based on the second coordinate transformation relationship for each combination of target identification points.

Optionally, the determining the first coordinate transformation relationship based on the second coordinate transformation relationship of each target identification point combination includes:

respectively carrying out coordinate transformation on each corresponding target identification point combination based on each second coordinate transformation relation to obtain a first coordinate transformation error corresponding to each second coordinate transformation relation;

Sequencing all the second coordinate conversion relations based on the first coordinate conversion errors from large to small, and determining a third preset number of second coordinate conversion relations which are sequenced in front as a plurality of third coordinate conversion relations;

the first coordinate transformation relationship is determined based on a plurality of third coordinate transformation relationships.

Optionally, the determining the first coordinate transformation relationship based on the plurality of third coordinate transformation relationships includes:

respectively carrying out coordinate transformation on each point cloud clustering center based on each third coordinate transformation relation to obtain a second coordinate transformation error corresponding to each third coordinate transformation relation;

and determining the first coordinate transformation relation by using a third coordinate transformation relation with the minimum second coordinate transformation error.

Optionally, the updating the existing road identification information on the target road section according to the first point cloud information includes:

determining coordinate information of a plurality of first road pictures on a bottom plate point cloud coordinate system and coordinate information of a plurality of first road pictures under a point cloud coordinate system to be verified according to the first point cloud information and third point cloud information of the target road section, wherein the point cloud coordinate system to be verified is a coordinate system where the first point cloud information is located;

Determining a fourth coordinate conversion relation between a point cloud coordinate system to be verified and a bottom plate point cloud coordinate system based on coordinate information of a plurality of first road pictures on the bottom plate point cloud coordinate system and coordinate information of the plurality of first road pictures under the point cloud coordinate system to be verified;

converting the first point cloud information of the road identifier to be verified to a bottom plate point cloud coordinate system based on the fourth coordinate conversion relation to obtain fourth point cloud information of the road identifier to be verified;

and updating the existing road identification information based on the fourth point cloud information of the road identification to be verified.

Optionally, the updating the existing road identification information based on the fourth point cloud information of the road identification to be verified includes:

respectively carrying out target detection on the plurality of first road pictures to obtain a road identification detection frame to be verified and a corresponding category in each first road picture;

clustering the fourth point cloud information in each road identification detection frame to be verified respectively to obtain three-dimensional point cloud coordinates of the point cloud clustering center of each road identification detection frame to be verified on a bottom plate point cloud coordinate system;

and updating the existing road identification information based on the point cloud clustering centers of the road identification detection frames to be verified.

In a second aspect, the present application provides an updating apparatus for a road identifier, where the updating apparatus for a road identifier includes:

a first acquisition unit for acquiring a plurality of first road pictures of a target road section;

the three-dimensional reconstruction unit is used for carrying out three-dimensional reconstruction on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section;

a second obtaining unit, configured to obtain existing road identification information on the target road section;

and the updating unit is used for updating the existing road identification information on the target road section according to the first point cloud information.

Optionally, the existing road identification information includes a plurality of existing road identifications and second point cloud information of each existing road identification, and the second obtaining unit is configured to:

Optionally, the second obtaining unit is configured to:

Optionally, the updating unit is configured to:

In a third aspect, the present application provides a computer device comprising:

one or more processors;

a memory; and

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the method of updating a road identification of any of the first aspects.

In a fourth aspect, the present application provides a computer readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the steps in the method of updating a road identification of any one of the first aspects.

The application provides a method and a device for updating a road identifier, wherein the method for updating the road identifier comprises the following steps: acquiring a plurality of first road pictures of a target road section; three-dimensional reconstruction is carried out on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section; acquiring the existing road identification information on the target road section; and updating the existing road identification information on the target road section according to the first point cloud information. Under the condition that the accuracy of the road identification updating method in the prior art is low, the road identification updating method is creatively provided, the three-dimensional reconstruction is carried out on the plurality of first road pictures to obtain the first point cloud information of the road identification to be verified on the three-dimensional target road section, and the three-dimensional first point cloud information contains more information relative to the two-dimensional pictures, so that the road identification can be updated more accurately by using the three-dimensional first point cloud information to update the existing road identification information on the target road section relative to the prior art, and the accuracy of the road identification updating method is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a scenario of an updating system of a road identifier provided in an embodiment of the present application;

FIG. 2 is a flowchart of one embodiment of a method for updating a road identifier provided in an embodiment of the present application;

fig. 3 is a flowchart of S203 in one embodiment of a method for updating a road identifier provided in the embodiments of the present application;

fig. 4 is a flowchart illustrating a process of acquiring a preset first coordinate transformation relationship in an embodiment of a method for updating a road identifier provided in an embodiment of the present application;

FIG. 5 is a schematic structural diagram of an embodiment of a road identifier updating device provided in an embodiment of the present application;

FIG. 6 is a schematic diagram of one embodiment of a computer device provided in an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

In the description of the present application, it should be understood that the terms "center," "longitudinal," "transverse," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate an orientation or positional relationship based on that shown in the drawings, merely for convenience of description and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be configured and operated in a particular orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more features. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.

In this application, the term "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the application. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present application may be practiced without these specific details. In other instances, well-known structures and processes have not been shown in detail to avoid obscuring the description of the present application with unnecessary detail. Thus, the present application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

The embodiment of the application provides a method and a device for updating a road identifier, which are respectively described in detail below.

Referring to fig. 1, fig. 1 is a schematic view of a scenario of a road identifier updating system provided in an embodiment of the present application, where the road identifier updating system may include a computer device 100, and an updating apparatus of a road identifier is integrated in the computer device 100.

In the embodiment of the present application, the computer device 100 may be an independent server, or may be a server network or a server cluster formed by servers, for example, the computer device 100 described in the embodiment of the present application includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server formed by a plurality of servers. Wherein the Cloud server is composed of a large number of computers or web servers based on Cloud Computing (Cloud Computing).

In the embodiment of the present application, the computer device 100 may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device 100 may be a desktop, a portable computer, a network server, a palm computer (Personal Digital Assistant, PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, an embedded device, etc., and the embodiment is not limited to the type of the computer device 100.

It will be appreciated by those skilled in the art that the application environment shown in fig. 1 is only one application scenario of the present application scenario, and is not limited to the application scenario of the present application scenario, and other application environments may further include more or fewer computer devices than those shown in fig. 1, for example, only 1 computer device is shown in fig. 1, and it will be appreciated that the updating system of the road identifier may further include one or more other computer devices capable of processing data, which is not limited herein.

In addition, as shown in fig. 1, the updating system of the road identification may further include a memory 200 for storing data.

It should be noted that, the schematic view of the scenario of the updating system of the road sign shown in fig. 1 is only an example, and the updating system of the road sign and the scenario described in the embodiments of the present application are for more clearly describing the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application, and as a person of ordinary skill in the art can know that, along with the evolution of the updating system of the road sign and the appearance of the new service scenario, the technical solutions provided in the embodiments of the present application are equally applicable to similar technical problems.

First, in an embodiment of the present application, a method for updating a road identifier is provided, where the method for updating a road identifier includes: acquiring a plurality of first road pictures of a target road section; three-dimensional reconstruction is carried out on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section; acquiring the existing road identification information on the target road section; and updating the existing road identification information on the target road section according to the first point cloud information.

As shown in fig. 2, fig. 2 is a flowchart of one embodiment of a method for updating a road identifier provided in an embodiment of the present application, where the method for updating a road identifier includes steps S201 to S204 as follows:

s201, acquiring a plurality of first road pictures of a target road section.

In the embodiment of the application, a plurality of first road pictures obtained by shooting a target road section in a target time period by a camera are obtained. The target road section may be any road section. The target time period may be 5:00 to 18:00, and may be set according to the specific situation.

In a specific embodiment, a plurality of third road pictures of the target road section are obtained, and the plurality of third road pictures are de-duplicated to obtain a plurality of first road pictures. Further, a plurality of third road pictures of the target road section are obtained, the plurality of third road pictures are subjected to duplication removal, the plurality of third road pictures subjected to duplication removal are obtained, whether the number of the plurality of third road pictures subjected to duplication removal exceeds the number of preset pictures is judged, and if the number of the plurality of third road pictures subjected to duplication removal exceeds the number of the preset pictures, the plurality of third road pictures subjected to duplication removal are determined to be a plurality of first road pictures. The number of the preset pictures may be 60, which is set according to specific situations and is not limited herein.

S202, performing three-dimensional reconstruction on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section.

In this embodiment, the road identifier may include various types of identifiers such as a sign, a street lamp, and a red-green lamp. The Point Cloud information is a set of points, called "Point Cloud", obtained after the spatial coordinates of each data Point on the surface of the object are acquired. The point cloud information may include three-dimensional coordinates (X-axis coordinates, Y-axis coordinates, and Z-axis coordinates), laser reflection Intensity (Intensity), and color information (RGB) of each data point on the point cloud coordinate system to be verified. The point cloud coordinate system to be verified refers to a coordinate system established under the view angle of a camera taking the first road picture. The road identifier to be verified, namely the road identifier to be verified, is the road identifier in the first road picture taken on the target road section.

Three-dimensional reconstruction refers to the establishment of a mathematical model suitable for computer representation and processing of a three-dimensional object, is the basis for processing, operating and analyzing the properties of the three-dimensional object in a computer environment, and is also a key technology for establishing virtual reality expressing an objective world in a computer. Three-dimensional reconstruction generally includes: image acquisition, camera calibration, feature extraction, stereo matching and three-dimensional reconstruction. Specifically, three-dimensional reconstruction is performed on a plurality of first road pictures by using an SFM algorithm, so as to obtain first point cloud information of the road mark to be verified on the target road section. SFM (Structure from motion) is a method of three-dimensional reconstruction for implementing a 3D reconstruction from motion. I.e. 3D information is deduced from the 2D images of the time series. The input to the SFM is a motion or a time series of 2D groups of graphs. Of course, in other embodiments, the three-dimensional reconstruction may also be performed using REMODE (REgularized MOnocular Depth Estimation) or other algorithms, which are not limited herein.

In order to avoid that a vehicle moving on the pictures affects three-dimensional reconstruction, in a specific embodiment, three-dimensional reconstruction is performed on a plurality of first road pictures to obtain first point cloud information of a road identifier to be verified on a target road section, which may include: and respectively carrying out target detection on the plurality of first road pictures by using the trained target detection model to obtain a vehicle detection frame in the first road pictures, removing images in the vehicle detection frame, and carrying out three-dimensional reconstruction on the plurality of first road pictures from which the vehicle detection frame is removed to obtain first point cloud information of the road mark to be verified on the target road section.

S203, acquiring the existing road identification information on the target road section.

In this embodiment of the present application, the existing road identifier information may include a plurality of existing road identifiers and second point cloud information of each of the existing road identifiers. The plurality of existing road identifications and the second point cloud information of each existing road identification can be manually marked and stored in the computer equipment, and the second point cloud information can be read at the moment. Existing road signs may include signs, street lights, red and green lights, and the like.

Because the efficiency of manual labeling is low, in order to improve the efficiency of acquiring the existing road identifier information, as shown in fig. 3, fig. 3 is a flowchart of S203 in one embodiment of the method for updating the road identifier provided in the embodiment of the present application, and in another specific embodiment, acquiring the existing road identifier information on the target road segment may include S301-S305:

S301, acquiring a plurality of second road pictures on the target road section.

The second road picture is marked with a road identification marking frame and a category of each existing road identification. The road identification marking frame and the category can be marked manually. The road mark marking frame is an external rectangle of the position of the road mark.

And S302, performing three-dimensional reconstruction on the plurality of second road pictures to obtain third point cloud information of the target road section.

Specifically, three-dimensional reconstruction can be performed on the plurality of second road pictures through an SFM algorithm, and third point cloud information of the target road section is obtained.

S303, obtaining third point cloud information of all the existing road identifications from the third point cloud information of the target road section according to the road identification marking frames of all the existing road identifications and the corresponding categories.

In a specific embodiment, the obtaining, according to the road identifier marking frame and the corresponding category of each existing road identifier, the third point cloud information of each existing road identifier from the third point cloud information of the target road segment may include: and acquiring third point cloud information in each road identification marking frame from the third point cloud information of the target road section according to the road identification marking frame of each existing road identification, and classifying the third point cloud information in each road identification marking frame according to the category of each road identification marking frame to acquire the third point cloud information of each existing road identification.

S304, clustering the third point cloud information of each type of existing road mark respectively to obtain the three-dimensional point cloud coordinates of the point cloud clustering center of each type of existing road mark on the bottom plate point cloud coordinate system.

The bottom plate point cloud coordinate system is a coordinate system established under the view angle of a camera for taking a plurality of second road pictures. The point cloud coordinate system to be verified refers to a coordinate system established under the view angle of a camera taking the first road picture. When the pose of the cameras for shooting the plurality of first road pictures and the pose of the cameras for shooting the plurality of second road pictures are different, the point cloud coordinate system to be verified and the bottom plate point cloud coordinate system are different. When the pose of the cameras for shooting the plurality of first road pictures and the pose of the cameras for shooting the plurality of second road pictures are the same, the point cloud coordinate system to be verified and the bottom plate point cloud coordinate system are the same coordinate system.

In the embodiment of the application, the third point cloud information of each type of existing road mark can be clustered through clustering algorithms such as k-means, BIRCH, DBSCAN and STING to obtain three-dimensional point cloud coordinates of the point cloud clustering center of each type of existing road mark on the bottom plate point cloud coordinate system.

And S305, determining second point cloud information of each existing road identifier based on the three-dimensional point cloud coordinates of the point cloud cluster center of each existing road identifier.

In a specific embodiment, the three-dimensional point cloud coordinates of the point cloud cluster center of each existing road identifier are determined as the second point cloud information of each existing road identifier.

In another specific embodiment, determining the second point cloud information of each existing road identifier based on the three-dimensional point cloud coordinates of the point cloud cluster center of each existing road identifier may include:

(1) And acquiring a preset first coordinate conversion relation and actual geographic coordinates of centers of the existing road marks under a geographic coordinate system.

In this embodiment of the present application, the first coordinate transformation relationship may be determined according to manual experience, and actual geographic coordinates of centers of the existing road marks under the geographic coordinate system may be measured in advance by manual or other manners. The geographic coordinate system (Geographic Coordinate System) is a coordinate system that uses a three-dimensional sphere to define the earth's surface location to achieve reference to earth's surface points through latitude and longitude. A geographic coordinate system comprises an angle measuring unit, a primary meridian and a reference ellipsoid. In a spherical system, the horizontal line is an equal latitude line or latitude line. The vertical lines are equal-warp lines or meridians. The geographic coordinate system may determine the location of any point on the earth.

(2) And converting the three-dimensional point cloud coordinates of the point cloud cluster centers of the existing road identifications into a bottom plate point cloud coordinate system based on the first coordinate conversion relation to obtain converted geographic coordinates of the point cloud cluster centers.

(3) If the distance between the converted geographic coordinates of the point cloud clustering center and the corresponding actual geographic coordinates of the center of the existing road mark is smaller than the first preset distance, determining the three-dimensional point cloud coordinates of the point cloud clustering center of the existing road mark as second point cloud information of the existing road mark.

The first preset distance may be 2 meters, and the first preset distance may be set according to specific situations, which is not limited herein.

In a specific embodiment, an existing road identifier corresponding to a center actual geographic coordinate closest to a converted geographic coordinate of a point cloud cluster center is determined as an existing road identifier corresponding to the point cloud cluster center on a geographic coordinate system, if a distance between the converted geographic coordinate of the point cloud cluster center and the center actual geographic coordinate of the corresponding existing road identifier is smaller than a first preset distance, the existing road identifier corresponding to the point cloud cluster center on a bottom plate point cloud coordinate system and the existing road identifier corresponding to the point cloud cluster center on the geographic coordinate system are indicated to be the same road identifier, association of the same existing road identifier on the geographic coordinate system and the bottom plate point cloud coordinate system is achieved, and three-dimensional point cloud coordinates of the point cloud cluster center of the existing road identifier can be determined as second point cloud information of the existing road identifier, so that accuracy of the existing road identifier information is ensured.

S204, updating the existing road identification information on the target road section according to the first point cloud information.

In this embodiment of the present application, updating the existing road identifier information on the target road section according to the first point cloud information may include:

(1) And determining coordinate information of the plurality of first road pictures on the bottom plate point cloud coordinate system and coordinate information of the plurality of first road pictures under the point cloud coordinate system to be verified according to the first point cloud information and the third point cloud information of the target road section.

In a specific embodiment, performing feature point matching on the third point cloud information and the plurality of first road pictures to obtain a plurality of first feature point pairs; and estimating the pose based on the plurality of first characteristic point pairs, obtaining the coordinate information of the cameras for shooting the plurality of first road pictures on the bottom plate point cloud coordinates, and determining the coordinate information of the plurality of first road pictures on the bottom plate point cloud coordinates according to the coordinate information of the cameras for shooting the plurality of first road pictures on the bottom plate point cloud coordinates. Specifically, pose estimation is performed based on a plurality of first feature point pairs by using a PNP algorithm, and coordinate information of the first camera on the bottom plate point cloud coordinates is obtained. Similarly, performing feature point matching on the first point cloud information and the plurality of first road pictures to obtain a plurality of second feature point pairs; and estimating the pose based on the plurality of second characteristic point pairs to obtain the coordinate information of the cameras for shooting the plurality of first road pictures on the point cloud coordinate system to be verified, and determining the coordinate information of the plurality of first road pictures on the point cloud coordinate system to be verified according to the coordinate information of the cameras for shooting the plurality of first road pictures on the point cloud coordinate system to be verified.

(2) And determining a fourth coordinate conversion relation between the point cloud coordinate system to be verified and the bottom plate point cloud coordinate system based on the coordinate information of the plurality of first road pictures on the bottom plate point cloud coordinate system and the coordinate information of the plurality of first road pictures under the point cloud coordinate system to be verified.

Specifically, a nonlinear optimization mode is used for determining a fourth coordinate transformation relation between the point cloud coordinate system to be verified and the bottom plate point cloud coordinate system based on coordinate information of the plurality of first road pictures on the bottom plate point cloud coordinate and coordinate information of the plurality of first road pictures under the point cloud coordinate system to be verified. The non-linear optimization may be in the manner of gauss newton's method.

(3) And converting the first point cloud information of the road identifier to be verified to a bottom plate point cloud coordinate system based on the fourth coordinate conversion relation to obtain fourth point cloud information of the road identifier to be verified.

(4) And updating the existing road identification information based on the fourth point cloud information of the road identification to be verified.

In a specific embodiment, updating the existing road identification information based on the fourth point cloud information of the road identification to be verified may include: and respectively carrying out target detection on the plurality of first road pictures to obtain a road identification detection frame to be verified and a corresponding category in each first road picture. Specifically, the trained yolov4 network can be used for respectively performing target detection on the plurality of first road pictures to obtain a road identification detection frame to be verified and a corresponding category in each first road picture. Clustering fourth point cloud information in each type of road identification detection frame to be verified respectively to obtain three-dimensional point cloud coordinates of the point cloud clustering centers of each type of road identification detection frame to be verified on a bottom plate point cloud coordinate system; and updating the existing road identification information based on the point cloud clustering centers of the road identification detection frames to be verified.

In a specific embodiment, updating the existing road identification information based on the point cloud cluster center of each road identification detection frame to be verified may include: and respectively determining each road identification detection frame to be verified as a target road identification detection frame to be verified, and acquiring the road identification to be compared closest to the target road identification detection frame to be verified in the similar existing road identifications corresponding to the target road identification detection frame to be verified. And judging whether the distance between the road mark to be compared and the target road mark detection frame to be verified is smaller than a second preset distance. The second preset distance may be 5m, which is set according to the specific setting. The distance between the road mark to be compared and the target road mark detection frame to be verified is the distance between the center of the road mark to be compared and the point cloud clustering center of the target road mark detection frame to be verified. In other embodiments, other points of the road identifier to be compared with the target road identifier detection frame to be verified may also be selected to determine the distance between the road identifier to be compared and the target road identifier detection frame to be verified.

If the distance between the road identification to be compared and the target road identification detection frame to be verified is not smaller than the second preset distance, determining that the road identification to be verified corresponding to the target road identification detection frame to be verified is a suspected newly-added road identification, and storing the road identification to be verified corresponding to the target road identification detection frame to be verified as a suspected newly-added record in a suspected update database. Further, if the distance between the road identifier to be compared and the target road identifier detection frame to be verified is not smaller than the second preset distance, judging whether the number of suspected newly-added records, which is stored in the suspected updating database and is the suspected newly-added road identifier, of the target road identifier detection frame to be verified exceeds the fourth preset number m. The fourth preset number m may be set according to circumstances. For example, the fourth preset number m=6. If the number of the suspected newly-increased records, which are stored in the suspected updating database and are of the suspected newly-increased road identifiers, of the target to-be-verified road identifier detection frame exceeds the fourth preset number m, determining that the road identifier to be verified corresponding to the target to-be-verified road identifier detection frame is the newly-increased road identifier, and storing the newly-increased road identifier into the newly-increased identifier database. When the target to-be-verified road identification detection frame is recorded as the suspected new identification for a plurality of times, the to-be-verified road identification corresponding to the target to-be-verified road identification detection frame is determined to be the new road identification, so that the probability of misjudging the suspected new identification as the new road identification can be reduced, and the accuracy of updating the road identification is improved. If the number of the suspected newly-increased records, which are stored in the suspected updating database and correspond to the target to-be-verified road identification detection frame, of the suspected newly-increased road identification does not exceed the fourth preset number, determining that the to-be-verified road identification corresponding to the target to-be-verified road identification detection frame is the suspected newly-increased road identification, and storing the to-be-verified road identification corresponding to the target to-be-verified road identification detection frame as a suspected newly-increased record in the suspected updating database.

Further, each existing road identification detection frame is respectively determined to be a target existing road identification detection frame, and the road identification to be compared closest to the target existing road identification detection frame in the similar existing road identifications corresponding to the target existing road identification detection frame is obtained. And judging whether the distance between the road mark to be compared and the target existing road mark detection frame is smaller than a second preset distance. The second preset distance may be 5m, which is set according to the specific setting. The distance between the road mark to be compared and the target existing road mark detection frame is the distance between the center of the road mark to be compared and the point cloud clustering center of the target existing road mark detection frame. In other embodiments, other points of the road identifier to be compared with the existing road identifier detection frame of the target may also be selected to determine the distance between the road identifier to be compared and the existing road identifier detection frame of the target.

If the distance between the road mark to be compared and the target existing road mark detection frame is smaller than the second preset distance, judging that the existing road mark corresponding to the target existing road mark detection frame still exists, and successfully punching the road mark. If the distance between the road mark to be compared and the target existing road mark detection frame is not smaller than the second preset distance, indicating that the existing road mark corresponding to the target existing road mark detection frame is possibly off-line, and storing the existing road mark corresponding to the target existing road mark detection frame as a suspected off-line record to a suspected updating database. Further, if the distance between the road mark to be compared and the target existing road mark detection frame is not smaller than the second preset distance, judging whether the number of the suspected offline records, which are stored in the suspected updating database and are the suspected offline road marks, of the target existing road mark detection frame exceeds the fifth preset number k. The fifth preset number k may be set according to circumstances, for example, the fifth preset number k=6. If the number of suspected offline records, stored in the suspected updating database, of which the target existing road identification detection frame is a suspected offline road identification exceeds a fifth preset number k, determining that the existing road identification corresponding to the target existing road identification detection frame is an offline road identification, and storing the existing road identification corresponding to the target existing road identification detection frame into an offline identification database; if the number of the suspected offline records, which are stored in the suspected updating database and correspond to the target existing road identification detection frame, of the suspected offline road identification does not exceed the fifth preset number k, determining that the existing road identification corresponding to the target existing road identification detection frame is the suspected offline road identification, and storing the road identification to be verified, which corresponds to the target existing road identification detection frame, into the suspected updating database as a suspected offline record. The suspected offline road mark refers to a road mark which may not exist in the target road section, and the offline road mark refers to a road mark which is judged to be the suspected offline road mark by a fifth preset number of times in the target road section.

Further, the off-line road identification stored in the off-line identification database is removed from the existing road identification information; adding the newly added road identifier stored in the newly added identifier database to the existing road identifier information; the update of the existing road identification information is realized.

Further, the first coordinate transformation relationship between the current backplane point cloud coordinate system and the geographic coordinate system can depend on manual experience. However, the control points are selected manually, so that the selection difficulty is high, and errors are easy to occur due to manual experience. In order to improve the efficiency and accuracy of obtaining the first coordinate transformation relationship, referring to fig. 4, fig. 4 is a flowchart illustrating a method for updating the road identifier according to an embodiment of the present application to obtain a preset first coordinate transformation relationship. As shown in fig. 4, obtaining a preset first coordinate transformation relationship and actual geographic coordinates of centers of the existing road identifications under a geographic coordinate system may include S401-S405:

s401, acquiring target identification point cloud information of a target category road identification from third point cloud information of a target road section.

The road identifications of the target categories can be street lamp identifications, the street lamp identifications on the roads are numerous, have large intervals and are easy to identify, the street lamp identifications are used as the road identifications of the target categories to calculate the first coordinate transformation relation, the efficiency of acquiring the first coordinate transformation relation can be improved, the accuracy of acquiring the first coordinate transformation relation is improved, and therefore the accuracy of updating the road identifications is improved. Of course, in other embodiments, other types of road identifications may be used.

Specifically, third point cloud information in a road identification marking frame belonging to the target category road identification is determined as target identification point cloud information.

S402, clustering the target identification point cloud information based on density to obtain clustering clusters corresponding to each target road identification in the target category road identifications.

In a specific embodiment, clustering is performed on the target identification point cloud information based on density based on a DBSCAN clustering algorithm to obtain clustering clusters corresponding to all target road identifications in the target category road identifications. The DBSCAN (Density-Based Spatial Clustering of Application with Noise) spatial clustering application with noise is a Density clustering algorithm based on high-Density connected areas. In other embodiments, clustering may also be performed using an OPTICS clustering algorithm, a DENCLUE clustering algorithm, and the like, which is not limited herein. Compared with other clustering methods, the density-based clustering method can find clusters with various shapes and sizes in noisy data, and is more suitable for point cloud clustering.

S403, determining the three-dimensional point cloud coordinates of the target identification point under the bottom plate point cloud coordinates according to the coordinates of each data point in each cluster.

The target mark point is the peak of the street lamp mark. Of course, in other embodiments, other points of the street lamp identifier may be used as the target identifier points.

In a specific embodiment, determining the three-dimensional point cloud coordinates of the target identification point under the bottom plate point cloud coordinates according to the coordinates of each data point in each cluster may include:

(1) And obtaining the plane coordinates of the central point of the area with the maximum density in the target cluster.

In a specific embodiment, a mean shift clustering algorithm is used to cluster points in the target cluster, so as to obtain a region with the maximum density, and plane coordinates of a central point of the region with the maximum density are obtained. Wherein the plane coordinates include an X-axis coordinate and a Y-axis coordinate.

(2) And ordering the data points in the target cluster from big to small according to the height value to obtain a plurality of ordered data points.

The data points in the target cluster include three-dimensional coordinates (X-axis coordinates, Y-axis coordinates, and Z-axis coordinates). The height value of the data point is the Z-axis coordinate.

(3) And determining the height coordinates of the target identification point under the point cloud coordinates based on the height values of the first preset number of data points which are ranked at the front.

In a specific embodiment, an average of the height values of the first preset number of data points ranked earlier is determined as the height coordinate of the target identification point under the bottom plate point cloud coordinate system. The first preset number may be specifically set, for example, the first preset number is a ratio of the total number of target clusters, and the first preset number is 2% of the total number of target clusters.

(4) And determining the three-dimensional point cloud coordinates of the target identification point under the bottom plate point cloud coordinate system based on the plane coordinates and the height coordinates.

And determining the plane coordinates as the plane coordinates of the target identification points in the bottom plate point cloud coordinate system, and determining the height coordinates as the height coordinates of the target identification points in the bottom plate point cloud coordinate system, so as to obtain the three-dimensional point cloud coordinates of the target identification points in the bottom plate point cloud coordinate system.

S404, obtaining the geographic coordinates of the target identification points under the geographic coordinate system.

The geographic coordinates of the target identification point in the geographic coordinate system can be measured in advance.

S405, determining a first coordinate transformation relation between the bottom plate point cloud coordinate system and the geographic coordinate system based on the three-dimensional point cloud coordinates and the geographic coordinates of the target identification points.

In a specific embodiment, determining the first coordinate transformation relationship between the base plate point cloud coordinate system and the geographic coordinate system based on the three-dimensional point cloud coordinates and the geographic coordinates of the target identification point may include:

(1) And obtaining a second preset number of target identification points from the plurality of target identification points to obtain a plurality of target identification point combinations.

In this embodiment of the present application, the second preset number is not less than 4, for example, the second preset number is 4.

(2) And carrying out nonlinear optimization on the three-dimensional point cloud coordinates and the geographic coordinates of each target identification point in each target identification point combination to obtain a second coordinate conversion relation between the three-dimensional point cloud coordinates and the geographic coordinates in each target identification point combination.

In a specific embodiment, nonlinear optimization is performed on three-dimensional point cloud coordinates and geographic coordinates of each target identification point in each target identification point combination by using a Gauss Newton method, an LM algorithm and the like, so as to obtain a second coordinate transformation relationship between the three-dimensional point cloud coordinates and the geographic coordinates in each target identification point combination.

(3) The first coordinate transformation relationship is determined based on the second coordinate transformation relationship for each combination of target identification points.

In a specific embodiment, determining the first coordinate transformation relationship based on the second coordinate transformation relationship for each combination of target identification points may include:

(1) And respectively carrying out coordinate transformation on each corresponding target identification point combination based on each second coordinate transformation relation to obtain a first coordinate transformation error corresponding to each second coordinate transformation relation.

In a specific embodiment, coordinate transformation is performed on three-dimensional point cloud coordinates in each corresponding target identification point combination based on a second coordinate transformation relation to obtain transformed geographic coordinates in each target identification point combination, and actual geographic coordinates in each target identification point combination are obtained; and acquiring coordinate deviations of converted geographic coordinates and actual geographic coordinates of each target identification point in the target identification point combination, determining the sum of the coordinate deviations of each target identification point combination as a first coordinate conversion error corresponding to the second coordinate conversion relation, and acquiring the first coordinate conversion error corresponding to each second coordinate conversion relation.

(2) And sequencing the second coordinate conversion relations based on the first coordinate conversion errors from large to small, and determining a third preset number of second coordinate conversion relations sequenced in front as a plurality of third coordinate conversion relations.

The third preset number is 10, and the third preset number can be set according to specific situations.

(3) The first coordinate transformation relationship is determined based on the plurality of third coordinate transformation relationships.

In a specific embodiment, determining the first coordinate transformation relationship based on the plurality of third coordinate transformation relationships may include: and respectively carrying out coordinate transformation on each point cloud clustering center based on each third coordinate transformation relation to obtain a second coordinate transformation error corresponding to each third coordinate transformation relation. Specifically, three-dimensional point cloud coordinates of each point cloud clustering center are converted based on each third coordinate conversion relation respectively to obtain converted geographic coordinates of each point cloud clustering center, coordinate deviations of the converted geographic coordinates and actual geographic coordinates of the point cloud clustering centers are obtained, and the sum of the coordinate deviations of each point cloud clustering center is determined to be a second coordinate conversion error corresponding to the third coordinate conversion relation to obtain a second coordinate conversion error corresponding to each third coordinate conversion relation. And determining the first coordinate transformation relation by using the third coordinate transformation relation with the minimum second coordinate transformation error.

In order to better implement the method for updating the road identifier in the embodiment of the present application, on the basis of the method for updating the road identifier, the embodiment of the present application further provides a device for updating the road identifier, as shown in fig. 5, where the device 500 for updating the road identifier includes:

a first obtaining unit 501, configured to obtain a plurality of first road pictures of a target road section;

the three-dimensional reconstruction unit 502 is configured to perform three-dimensional reconstruction on the plurality of first road pictures to obtain first point cloud information of the road identifier to be verified on the target road section;

a second obtaining unit 503, configured to obtain existing road identification information on a target road segment;

and an updating unit 504, configured to update the existing road identification information on the target road segment according to the first point cloud information.

Optionally, the existing road identification information includes a plurality of existing road identifications and second point cloud information of each of the existing road identifications, and the second obtaining unit 503 is configured to:

three-dimensional reconstruction is carried out on the plurality of second road pictures to obtain third point cloud information of the target road section, wherein a coordinate system where the third point cloud information is located is a bottom plate point cloud coordinate system;

Acquiring third point cloud information of each type of existing road mark from the third point cloud information of the target road section according to the road mark marking frame of each type of existing road mark and the corresponding category;

Optionally, the second obtaining unit 503 is configured to:

acquiring target identification point cloud information of a target category road identification from third point cloud information of a target road section;

Optionally, the second obtaining unit 503 is configured to:

and determining the three-dimensional point cloud coordinates of the target identification point under the bottom plate point cloud coordinate system based on the plane coordinates and the height coordinates.

Optionally, the second obtaining unit 503 is configured to:

the first coordinate transformation relationship is determined based on the plurality of third coordinate transformation relationships.

Optionally, the second obtaining unit 503 is configured to:

And determining the first coordinate transformation relation by using the third coordinate transformation relation with the minimum second coordinate transformation error.

Optionally, the updating unit 504 is configured to:

determining coordinate information of a plurality of first road pictures on a bottom plate point cloud coordinate system and coordinate information of the plurality of first road pictures under a point cloud coordinate system to be verified according to the first point cloud information and third point cloud information of a target road section, wherein the point cloud coordinate system to be verified is a coordinate system in which the first point cloud information is located;

determining a fourth coordinate conversion relation between the point cloud coordinate system to be verified and the bottom plate point cloud coordinate system based on the coordinate information of the plurality of first road pictures on the bottom plate point cloud coordinate system and the coordinate information of the plurality of first road pictures under the point cloud coordinate system to be verified;

converting the first point cloud information of the road identifier to be verified to a bottom plate point cloud coordinate system based on a fourth coordinate conversion relationship to obtain fourth point cloud information of the road identifier to be verified;

Optionally, the updating unit 504 is configured to:

respectively carrying out target detection on a plurality of first road pictures to obtain road identification detection frames to be verified and corresponding categories in each first road picture;

Clustering fourth point cloud information in each type of road identification detection frame to be verified respectively to obtain three-dimensional point cloud coordinates of the point cloud clustering centers of each type of road identification detection frame to be verified on a bottom plate point cloud coordinate system;

The embodiment of the application also provides a computer device, which integrates any of the updating devices of the road identifier provided by the embodiment of the application, and the computer device comprises:

one or more processors;

a memory; and

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to perform the steps in the method of updating a road identification in any of the above-described embodiments of the method of updating a road identification.

As shown in fig. 6, a schematic structural diagram of a computer device according to an embodiment of the present application is shown, specifically:

the computer device may include one or more processing cores 'processors 601, one or more computer-readable storage media's memory 602, power supply 603, and input unit 604, among other components. It will be appreciated by those skilled in the art that the computer device structure shown in the figures is not limiting of the computer device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components. Wherein:

Processor 601 is the control center of the computer device and connects the various parts of the overall computer device using various interfaces and lines to perform various functions and process data of the computer device by running or executing software programs and/or modules stored in memory 602 and invoking data stored in memory 602. Optionally, the processor 601 may include one or more processing cores; the processor 601 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, and preferably, the processor 601 may integrate an application processor primarily handling operating systems, user interfaces, application programs, and the like, with a modem processor primarily handling wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601.

The memory 602 may be used to store software programs and modules, and the processor 601 may execute various functional applications and data processing by executing the software programs and modules stored in the memory 602. The memory 602 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 602 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 602 may also include a memory controller to provide access to the memory 602 by the processor 601.

The computer device further includes a power supply 603 for powering the various components, preferably, the power supply 603 can be logically coupled to the processor 601 through a power management system, such that functions of managing charging, discharging, and power consumption are performed by the power management system. The power supply 603 may also include one or more of any components, such as a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.

The computer device may also include an input unit 604, which input unit 604 may be used to receive entered numerical or character information and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

Although not shown, the computer device may further include a display unit or the like, which is not described herein. In particular, in this embodiment, the processor 601 in the computer device loads executable files corresponding to the processes of one or more application programs into the memory 602 according to the following instructions, and the processor 601 executes the application programs stored in the memory 602, so as to implement various functions as follows:

acquiring a plurality of first road pictures of a target road section; three-dimensional reconstruction is carried out on the plurality of first road pictures to obtain first point cloud information of the road mark to be verified on the target road section; acquiring the existing road identification information on the target road section; and updating the existing road identification information on the target road section according to the first point cloud information.

Those of ordinary skill in the art will appreciate that all or a portion of the steps of the various methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, which may be stored in a computer-readable storage medium and loaded and executed by a processor.

To this end, embodiments of the present application provide a computer readable storage medium, which may include: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like. On which a computer program is stored, which is loaded by a processor to perform the steps of any of the road identification updating methods provided by the embodiments of the present application. For example, the loading of the computer program by the processor may perform the steps of:

In the foregoing embodiments, the descriptions of the embodiments are focused on, and the portions of one embodiment that are not described in detail in the foregoing embodiments may be referred to in the foregoing detailed description of other embodiments, which are not described herein again.

In the implementation, each unit or structure may be implemented as an independent entity, or may be implemented as the same entity or several entities in any combination, and the implementation of each unit or structure may be referred to the foregoing method embodiments and will not be repeated herein.

The specific implementation of each operation above may be referred to the previous embodiments, and will not be described herein.

The foregoing describes in detail a method and apparatus for updating a road identifier provided in the embodiments of the present application, and specific examples are applied to describe the principles and embodiments of the present application, where the descriptions of the foregoing embodiments are only used to help understand the method and core ideas of the present application; meanwhile, as those skilled in the art will vary in the specific embodiments and application scope according to the ideas of the present application, the contents of the present specification should not be construed as limiting the present application in summary.

Claims

1. A method for updating a road identifier, comprising:

acquiring a plurality of first road pictures of a target road section;

2. The method for updating a road identifier according to claim 1, wherein the existing road identifier information includes a plurality of existing road identifiers and second point cloud information of each of the existing road identifiers, and the acquiring the existing road identifier information on the target link includes:

3. The method for updating a road identifier according to claim 2, wherein the determining the second point cloud information of each existing road identifier based on the three-dimensional point cloud coordinates of the point cloud cluster center of each existing road identifier comprises:

4. The method for updating a road identifier according to claim 3, wherein the obtaining the preset first coordinate transformation relation and the actual geographical coordinates of the center of each existing road identifier under the geographical coordinate system includes:

5. The method for updating a road identifier according to claim 4, wherein the determining the three-dimensional point cloud coordinates of the target identifier point in the bottom plate point cloud coordinate system according to the coordinates of each data point in each cluster includes:

6. The method according to claim 4, wherein the determining the first coordinate transformation relation between the base plate point cloud coordinate system and the geographic coordinate coefficient based on the three-dimensional point cloud coordinates and the geographic coordinates of the target identification point comprises:

7. The method of updating a road marking according to claim 6, wherein the determining the first coordinate transformation relation based on the second coordinate transformation relation of each target marking point combination comprises:

8. The method of updating a road identifier according to claim 7, wherein the determining the first coordinate transformation relationship based on the plurality of third coordinate transformation relationships comprises:

9. The method for updating a road identifier according to claim 2, wherein updating the existing road identifier information on the target link according to the first point cloud information comprises:

10. The method for updating a road identifier according to claim 9, wherein updating the existing road identifier information based on the fourth point cloud information of the road identifier to be verified comprises:

11. An updating device for a road sign, characterized in that the updating device for a road sign comprises:

12. A computer device, the computer device comprising:

one or more processors;

a memory; and

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the method of updating a road identification of any of claims 1 to 10.

13. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program is loaded by a processor to perform the steps in the method of updating a road marking according to any of claims 1 to 10.