CN113177988A - Calibration method, device, equipment and storage medium for dome camera and laser - Google Patents
Calibration method, device, equipment and storage medium for dome camera and laser Download PDFInfo
- Publication number
- CN113177988A CN113177988A CN202110480932.0A CN202110480932A CN113177988A CN 113177988 A CN113177988 A CN 113177988A CN 202110480932 A CN202110480932 A CN 202110480932A CN 113177988 A CN113177988 A CN 113177988A
- Authority
- CN
- China
- Prior art keywords
- camera
- dimensional
- angular points
- calibration
- laser
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000015654 memory Effects 0.000 claims description 21
- 230000006870 function Effects 0.000 claims description 18
- 230000003287 optical effect Effects 0.000 claims description 14
- 238000001914 filtration Methods 0.000 claims description 12
- 238000004422 calculation algorithm Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 4
- 230000004927 fusion Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000007620 mathematical function Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000149 penetrating effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a calibration method, a calibration device, calibration equipment and a storage medium for a spherical screen camera and laser, which are used for acquiring two-dimensional image data and point cloud data of a calibration plate at different positions and different angles, wherein the calibration plate is a checkerboard calibration plate with MXN angular points, and the angular points are intersection points of checkerboards on the calibration plate; calibrating internal parameters of the dome camera based on the two-dimensional image data; acquiring positions of four angular points in the point cloud data to acquire two-dimensional checkerboard angular points, and acquiring three-dimensional checkerboard angular points corresponding to the two-dimensional checkerboard angular points according to a pre-established matching relationship between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points; the method and the device have the advantages that the external parameters of the dome camera and the laser sensor are optimized based on the acquired three-dimensional checkerboard angular points, the calibration accuracy of the dome camera is improved by combining the characteristics of the laser sensor, the matching between the laser sensor and the dome camera is completed, and the method and the device have the advantages of short time consumption and high efficiency in the calibration process.
Description
Technical Field
The invention relates to the technical field of calibration of dome cameras, in particular to a calibration method, device, equipment and storage medium for a dome camera and laser.
Background
At present, it is becoming a trend that various high-end technology products are created based on the laser radar and camera fusion technology in China, so the related technology of the laser radar and camera fusion is developed rapidly. The most basic technology for fusing the two is the calibration of external parameters between the two, which is the basis for ensuring the consistency of the environmental information sensed by the two. However, many effective technical schemes have been provided for realizing the calibration between the spherical screen camera and the laser, but the method is rarely applied to the calibration between the spherical screen camera and the laser, and the existing camera also has the problem of poor calibration precision.
Therefore, how to provide a method for improving the calibration accuracy of a camera becomes a technical problem which needs to be solved urgently.
Disclosure of Invention
The embodiment of the invention aims to provide a calibration method, a calibration device, calibration equipment and a storage medium for a spherical screen camera and laser, so as to solve the technical problem that the existing camera is poor in calibration precision.
In order to solve the above technical problem, an embodiment of the present invention provides a calibration method for a ball screen camera and a laser, which adopts the following technical scheme:
a calibration method of a dome camera and laser is applied to the dome camera and comprises the following steps:
acquiring two-dimensional image data and point cloud data of a calibration plate at different positions and different angles, wherein the two-dimensional image data is acquired by a dome camera, the point cloud data is acquired by a laser sensor, the calibration plate is a checkerboard calibration plate with M x N angular points, and the angular points are intersection points of checkerboards on the calibration plate;
calibrating internal parameters of the dome camera based on the two-dimensional image data;
acquiring positions of four angular points in the point cloud data to acquire two-dimensional checkerboard angular points, and acquiring three-dimensional checkerboard angular points corresponding to the two-dimensional checkerboard angular points according to a preset matching relation between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and optimizing external parameters of the spherical screen camera and the laser sensor based on the acquired corner points of the three-dimensional checkerboard.
Further, the specific step of calibrating the internal parameters of the dome camera based on the two-dimensional image data includes:
extracting position data of each corner point in the two-dimensional image data;
matching the coordinates of angle pixel points of the acquired position data of the angular points with the standard calibration plate image;
and calculating the rotation parameters of the two-dimensional image data relative to the standard calibration plate image through an SFM algorithm to obtain the internal parameters of the dome camera.
Further, the method comprises the following steps: filtering the point cloud data; the specific steps of filtering the point cloud data comprise:
noise returned by the laser sensor is obtained;
obtaining the confidence of the noise point;
comparing the confidence coefficient of the noise point with a preset threshold value;
and removing noise points with confidence degrees exceeding a threshold value to obtain filtered point cloud data.
Further, the specific step of acquiring the two-dimensional checkerboard corner points includes:
selecting four angular points of the upper left, the lower right and the upper right in the point cloud data anticlockwise;
and according to the four corner fitting planes, uniformly selecting the positions of the corner projections in the M multiplied by N point cloud data on the planes to obtain the two-dimensional checkerboard corners.
Further, the specific steps of optimizing the external parameters of the dome camera and the laser sensor include:
rotating a three-dimensional point P _ lidar generated by a laser sensor through external reference to obtain a three-dimensional point under a camera coordinate system, and marking as P _ camera;
projecting the P _ camera to an image coordinate system through internal reference of a camera to obtain a P _ project, wherein the camera coordinate system is a three-dimensional rectangular coordinate system, the origin of the camera coordinate system is located at the optical center of a lens, an X axis and a Y axis are respectively parallel to two sides of a phase plane, a Z axis is a lens optical axis and is vertical to an image plane, the image coordinate system takes the image center as the origin of coordinates, and the X axis and the Y axis are parallel to the two sides of an image;
optimizing external parameters of the spherical screen camera and the laser sensor through a cost function;
wherein the cost function is:
in order to solve the above technical problem, an embodiment of the present invention further provides a ball screen camera and a laser calibration device, which adopt the following technical solutions:
the utility model provides a ball curtain camera and laser calibration device, includes:
the calibration board is a checkerboard calibration board with MXN angular points, and the angular points are intersection points of checkerboards on the calibration board;
the internal reference calibration module is used for calibrating the internal reference of the dome camera;
the point cloud data processing module is used for acquiring the positions of four angular points in the point cloud data so as to acquire two-dimensional checkerboard angular points, and acquiring three-dimensional checkerboard angular points corresponding to the two-dimensional checkerboard angular points according to the preset matching relationship between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and the external parameter optimization module is used for optimizing the external parameters of the spherical screen camera and the laser sensor.
Further, the apparatus further comprises:
the point cloud filtering module is used for filtering the point cloud data;
the two-dimensional checkerboard angular point generation module is used for processing the filtered point cloud data and generating two-dimensional checkerboard angular points;
the matching relation establishing module is used for establishing the matching relation between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and the three-dimensional checkerboard corner generating module is used for generating three-dimensional checkerboard corners.
Further, the external parameters of the optimized dome camera and the laser sensor specifically include:
rotating a three-dimensional point P _ lidar generated by a laser sensor through external reference to obtain a three-dimensional point under a camera coordinate system, and marking as P _ camera;
projecting the P _ camera to an image coordinate system through internal reference of a camera to obtain a P _ project, wherein the camera coordinate system is a three-dimensional rectangular coordinate system, the origin of the camera coordinate system is located at the optical center of a lens, an X axis and a Y axis are respectively parallel to two sides of a phase plane, a Z axis is a lens optical axis and is vertical to an image plane, the image coordinate system takes the image center as the origin of coordinates, and the X axis and the Y axis are parallel to the two sides of an image;
optimizing external parameters of the spherical screen camera and the laser sensor through a cost function;
wherein the cost function is:
in order to solve the above technical problem, an embodiment of the present invention further provides a computer device, which adopts the following technical solutions:
a computer device, comprising a memory and a processor, wherein the memory stores computer readable instructions, and the processor implements the steps of the calibration method of the dome camera and the laser as described above when executing the computer readable instructions.
In order to solve the above technical problem, an embodiment of the present invention further provides a computer-readable storage medium, which adopts the following technical solutions: the computer readable storage medium stores computer readable instructions, and the computer readable instructions, when executed by the processor, implement the steps of the calibration method of the dome camera and the laser as described above.
Compared with the prior art, the embodiment of the invention mainly has the following beneficial effects:
the invention discloses a calibration method, a calibration device and a calibration equipment of a dome camera and laser, belonging to the technical field of calibration of dome cameras, wherein the method comprises the steps of acquiring two-dimensional image data and point cloud data of a calibration plate obtained at different positions and different angles, wherein the two-dimensional image data is acquired by the dome camera, the point cloud data is acquired by a laser sensor, the calibration plate is a checkerboard calibration plate with MXN angular points, and the angular points are intersection points of checkerboards on the calibration plate; calibrating internal parameters of the dome camera based on the two-dimensional image data; acquiring positions of four angular points in the point cloud data to acquire two-dimensional checkerboard angular points, and acquiring three-dimensional checkerboard angular points corresponding to the two-dimensional checkerboard angular points according to a preset matching relation between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points; and optimizing external parameters of the spherical screen camera and the laser sensor based on the acquired corner points of the three-dimensional checkerboard. The method and the device have the advantages that the calibration accuracy of the dome camera is improved by combining the characteristics of the laser sensor, the matching between the laser sensor and the dome camera is completed, and the calibration process is short in time consumption and high in efficiency.
Drawings
In order to more clearly illustrate the solution of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without inventive labor.
FIG. 1 illustrates a flow diagram of one embodiment of a method for calibration of a dome camera and laser according to the present invention;
FIG. 2 illustrates a sub-flow diagram of one embodiment of a method for calibration of a dome camera and laser according to the present invention;
FIG. 3 illustrates another sub-flow diagram of one embodiment of a method for calibration of a dome camera with a laser according to the present invention;
fig. 4 shows a schematic structural diagram of an embodiment of a dome camera and a laser calibration device according to the present invention.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs; the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention; the terms "comprising" and "having," and any variations thereof, in the description and claims of this invention and the description of the above figures, are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and in the claims, or in the drawings, are used for distinguishing between different objects and not necessarily for describing a particular sequential order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
In order to make the technical solutions of the present invention better understood by those skilled in the art, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of an embodiment of a calibration method of a dome camera and a laser according to the present invention is shown. The calibration method of the dome camera and the laser comprises the following steps:
s100, two-dimensional image data and point cloud data obtained by a calibration plate at different positions and different angles are obtained, wherein the two-dimensional image data are collected by a dome camera, the point cloud data are collected by a laser sensor, the calibration plate is a checkerboard calibration plate with MXN angular points, and the angular points are intersection points of checkerboards on the calibration plate.
Specifically, in step S100 provided in the embodiment of the present invention, a calibration board is placed in the view angle of the dome camera and the laser slave sensor, and a shooting switch of the dome camera and a scanning switch of the laser sensor are turned on, so that the dome camera collects two-dimensional image data of the calibration board, the laser sensor collects point cloud data of the calibration board, the calibration board is a currently commonly used disc-type chess calibration board, and checkerboard patterns on the calibration board generate M × N angular points.
Preferably, the laser sensor needs to collect 50 frames of point cloud data and superimpose the point cloud data when collecting the point cloud data of the calibration plate, because the laser sensor is non-repeatedly scanned, the scanning positions of the laser sensor are different in the same period frequency, and in order to obtain complete point cloud data, the laser sensor collects point cloud data in at least one period, namely all the point cloud data collected within 1 second.
Preferably, before the two-dimensional image data and the point cloud data of the calibration plate are collected, the spherical screen camera and the laser sensor are required to be fixed at a preset position, the spherical screen camera and the laser sensor are placed on the same straight line and are adjusted at different heights, the angle of view of the spherical screen camera and the angle of view of the laser sensor are concentrically arranged, and the spherical screen camera and the laser sensor can have the same angle of view when the calibration plate is shot in the arrangement mode.
The position and the angle of the calibration plate relative to the dome camera and the laser sensor are changed, for example, when two-dimensional image data and point cloud data are collected for the first time, the distance between the calibration plate and the dome camera is 80cm, in collecting the two-dimensional image data and the point cloud data again, the distance between the calibration plate and the dome camera can be changed to 90cm, and after the position of the calibration plate is changed, the dome camera and the laser sensor are controlled again to collect the two-dimensional image data and the point cloud data.
Further, in order to prevent the calibration result from being over-fitted, when the position and the angle of the calibration board are changed, the calibration board needs to be in the same plane as the calibration board in the previous position when the position of the calibration board is changed.
S200, calibrating internal parameters of the dome camera based on the two-dimensional image data;
specifically, in step S200 provided in the embodiment of the present invention, the dome camera is used to capture two-dimensional image data, mxn two-dimensional image data checkerboard corner positions are extracted, and internal parameters of the dome camera are calibrated by a calibration method;
s300, acquiring positions of four corner points in the point cloud data to acquire two-dimensional checkerboard corner points, and acquiring three-dimensional checkerboard corner points corresponding to the two-dimensional checkerboard corner points according to a preset matching relation between the two-dimensional checkerboard corner points and the three-dimensional checkerboard corner points;
specifically, in step S300 provided in the embodiment of the present invention, four corner points of the top left, bottom right, and top right in the point cloud data are selected counterclockwise; according to the four corner fitting planes, uniformly selecting the positions of corner projections in the M multiplied by N point cloud data on the planes to obtain two-dimensional checkerboard corners; establishing a matching relation between two-dimensional checkerboard angular points and three-dimensional checkerboard angular points by a Camera-Lidar calibration method, and obtaining three-dimensional checkerboard angular points through the two-dimensional checkerboard angular points and the matching relation; and
s400, optimizing external parameters of the spherical screen camera and the laser sensor based on the acquired corner points of the three-dimensional checkerboard.
Referring to fig. 2, a sub-flow diagram of one embodiment of a method for calibrating a dome camera to a laser according to the present invention is shown. In this embodiment, the calibrating the internal reference of the dome camera specifically includes the following steps:
s210, extracting position data of corner points in the two-dimensional image data;
s220, carrying out angle pixel point coordinate matching on the position data of the corner points acquired in the S210 and the standard calibration board image;
and S230, calculating rotation parameters of the two-dimensional image data relative to the standard calibration plate image through an SFM algorithm to obtain camera internal parameters.
Referring to fig. 3, another sub-flow diagram of an embodiment of a method for calibrating a dome camera to a laser according to the present invention is shown.
In this embodiment, the method further includes the steps of: filtering the point cloud data; the specific steps of filtering the point cloud data comprise:
s310, noise returned by the laser penetrating rod ball is obtained;
s320, obtaining the confidence coefficient of the noise point;
s330, comparing the confidence coefficient of the noise point with a preset threshold value;
s340, extracting noise points with confidence degrees exceeding a threshold value to obtain filtered point cloud data;
it should be noted that the invention can also filter the point cloud data in a manner of removing outliers in the point cloud data by using a statistical filter.
In this embodiment, the specific steps of optimizing the external parameters of the dome camera and the laser sensor include:
s410, rotating the three-dimensional point P _ lidar generated by the laser sensor through an external parameter to obtain a three-dimensional point under a camera coordinate system, and marking as P _ camera;
s420, projecting the P _ camera to an image coordinate system through internal reference of the camera to obtain a P _ project, wherein the camera coordinate system is a three-dimensional rectangular coordinate system, the origin of the camera coordinate system is located at the optical center of the lens, an X axis and a Y axis are respectively parallel to two sides of a phase plane, a Z axis is a lens optical axis and is vertical to an image plane, the image coordinate system takes the image center as the origin of coordinates, and the X axis and the Y axis are parallel to the two sides of the image; further, each matching pair of the current frame is projected to a camera coordinate system by utilizing current frame camera intrinsic parameters of the two-dimensional image data, specifically, the ith point of the current frame forms the three-dimensional coordinates of the ith point of the camera coordinate system through the camera intrinsic parameters, and distortion is removed by utilizing a characteristic point incidence angle distortion method through a distortion model in the projection process, so that the camera coordinate system can be restored to the ideal camera three-dimensional coordinates. Mathematical functions and procedures of the distortion model: the method comprises the steps of measuring an incident angle A and a corresponding distorted incident angle B within a field angle of a lens by using a precise optical instrument, and fitting a mathematical relation between the incident angles A and B by using a binary 9-power equation to form a mathematical model for adjusting the projection distortion of a camera.
S430, optimizing external parameters of the dome camera and the laser sensor through a cost function, specifically, minimizing Euclidean distances of P _ project and P _ camera through the cost function;
wherein the cost function is:
and optimizing external parameters of the dome camera and the laser sensor through the cost function, effectively improving the overall automatic calibration efficiency, and obtaining the optimal external parameters through the cost function to ensure that the sum of Euclidean distances between the P _ project coordinate point and the P _ camera coordinate point is minimum.
According to the method, the laser sensor is adopted to obtain point cloud data, the obtained point cloud data are processed, then Camera-Lidar calibration is carried out, the generated three-dimensional point P _ Lidar is converted into an image system through external reference rotation and internal reference projection, then the optimal external reference is obtained through a cost function, the sum of Euclidean distances between a P _ project coordinate point and a P _ Camera coordinate point is minimum, and calibration of the dome Camera is completed.
With further reference to fig. 4, as an implementation of the method shown in fig. 1, the present invention provides an embodiment of a ball screen camera and a laser calibration apparatus, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 1, and the apparatus may be specifically applied to various electronic devices.
A ball curtain camera and laser calibration device, the device includes:
a data obtaining module 510, configured to obtain two-dimensional image data and point cloud data obtained by a calibration plate at different positions and at different angles, where the two-dimensional image data is collected by a dome camera, the point cloud data is collected by a laser sensor, the calibration plate is a checkerboard calibration plate with mxn angular points, and the angular points are intersections of checkerboards on the calibration plate;
an internal reference calibration module 520, configured to calibrate internal references of the dome camera;
the point cloud data processing module 530 is configured to acquire positions of four corner points in the point cloud data to acquire two-dimensional checkerboard corner points, and acquire three-dimensional checkerboard corner points corresponding to the two-dimensional checkerboard corner points according to a pre-established matching relationship between the two-dimensional checkerboard corner points and the three-dimensional checkerboard corner points;
and an external parameter optimizing module 540, configured to optimize external parameters of the dome camera and the laser sensor.
Further, the point cloud data processing module comprises:
the point cloud filtering module is used for filtering the point cloud data;
the two-dimensional checkerboard angular point generation module is used for processing the filtered point cloud data and generating two-dimensional checkerboard angular points;
the matching relation establishing module is used for establishing the matching relation between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and the three-dimensional checkerboard corner generating module is used for generating three-dimensional checkerboard corners.
In a specific embodiment, the external reference optimizing module 540 optimizes the external reference of the dome camera and the laser sensor specifically including:
rotating a three-dimensional point P _ lidar generated by a laser sensor through external reference to obtain a three-dimensional point under a camera coordinate system, and marking as P _ camera;
projecting the P _ camera to an image coordinate system through internal reference of a camera to obtain a P _ project, wherein the camera coordinate system is a three-dimensional rectangular coordinate system, the origin of the camera coordinate system is located at the optical center of a lens, an X axis and a Y axis are respectively parallel to two sides of a phase plane, a Z axis is a lens optical axis and is vertical to an image plane, the image coordinate system takes the image center as the origin of coordinates, and the X axis and the Y axis are parallel to the two sides of an image;
optimizing external parameters of the spherical screen camera and the laser sensor through a cost function;
wherein the cost function is:
and optimizing external parameters of the dome camera and the laser sensor through the cost function, effectively improving the overall automatic calibration efficiency, and obtaining the optimal external parameters through the cost function to ensure that the sum of Euclidean distances between the P _ project coordinate point and the P _ camera coordinate point is minimum.
In order to solve the above technical problem, an embodiment of the present invention further provides a computer device.
The computer device includes a memory, a processing, and a network interface communicatively coupled to each other via a device bus. It should be noted that the present embodiment illustrates only a computer device having component memories, processing and network interfaces, but it should be understood that not all illustrated components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.
The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.
The memory includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the memory may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like provided on the computer device. Of course, the memory may also include both internal and external storage devices of the computer device. In this embodiment, the memory is generally used to store an operating device installed in the computer device and various application software, such as computer readable instructions of a calibration method for a dome camera and a laser. In addition, the memory may also be used to temporarily store various types of data that have been output or are to be output.
The processor may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor is typically used to control the overall operation of the computer device. In this embodiment, the processor is configured to execute computer readable instructions or processing data stored in the memory, for example, computer readable instructions for executing the calibration method of the dome camera and the laser.
The network interface may include a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the computer device and other electronic devices.
The invention discloses computer equipment, wherein a calibration method of a dome camera and laser is stored in a memory of the computer equipment in a computer readable instruction mode, and when a processor runs the computer readable instruction, the calibration method of the dome camera and the laser is realized.
Specifically, the specific implementation method of the processor for the instruction may refer to the description of the relevant steps in the embodiment corresponding to fig. 1, which is not described herein again.
The invention further provides another embodiment, namely a computer-readable storage medium, which stores computer-readable instructions, where the computer-readable instructions are executable by at least one processor, and discloses a computer-readable storage medium, where the method for calibrating a dome camera and a laser is stored in the storage medium in the form of computer-readable instructions, and the computer-readable instructions are executed by the processor to perform the steps of the method for calibrating a dome camera and a laser.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus, system, and method may be implemented in other ways. For example, the system embodiments described above are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or systems recited in the system claims may also be implemented by one unit or system in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A calibration method of a dome camera and laser is characterized by being applied to the dome camera and comprising the following steps:
acquiring two-dimensional image data and point cloud data of a calibration plate at different positions and different angles, wherein the two-dimensional image data is acquired by a dome camera, the point cloud data is acquired by a laser sensor, the calibration plate is a checkerboard calibration plate with M x N angular points, and the angular points are intersection points of checkerboards on the calibration plate;
calibrating internal parameters of the dome camera based on the two-dimensional image data;
acquiring positions of four angular points in the point cloud data to acquire two-dimensional checkerboard angular points, and acquiring three-dimensional checkerboard angular points corresponding to the two-dimensional checkerboard angular points according to a pre-established matching relationship between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and optimizing external parameters of the spherical screen camera and the laser sensor based on the acquired corner points of the three-dimensional checkerboard.
2. The method for calibrating a dome camera and a laser according to claim 1, wherein the step of calibrating the internal parameters of the dome camera based on the two-dimensional image data comprises:
extracting position data of each corner point in the two-dimensional image data;
matching the coordinates of angle pixel points of the acquired position data of the angular points with the standard calibration plate image;
and calculating the rotation parameters of the two-dimensional image data relative to the standard calibration plate image through an SFM algorithm to obtain the internal parameters of the dome camera.
3. The method for calibrating a dome camera to a laser as claimed in claim 1, wherein the method further comprises the steps of: filtering the point cloud data;
the step of filtering the point cloud data comprises the following steps:
noise returned by the laser sensor is obtained;
obtaining the confidence of the noise point;
comparing the confidence coefficient of the noise point with a preset threshold value;
and removing noise points with confidence degrees exceeding a threshold value to obtain filtered point cloud data.
4. The method for calibrating a dome camera and a laser according to claim 1, wherein the step of acquiring the two-dimensional checkered corner points comprises:
selecting four angular points of the upper left, the lower right and the upper right in the point cloud data anticlockwise;
and according to the four corner fitting planes, uniformly selecting the positions of the corner projections in the M multiplied by N point cloud data on the planes to obtain the two-dimensional checkerboard corners.
5. The method for calibrating a dome camera and a laser as claimed in claim 1, wherein the specific step of optimizing the external parameters of the dome camera and the laser sensor comprises:
rotating a three-dimensional point P _ lidar generated by a laser sensor through external reference to obtain a three-dimensional point under a camera coordinate system, and marking as P _ camera;
projecting the P _ camera to an image coordinate system through internal reference of a camera to obtain a P _ project, wherein the camera coordinate system is a three-dimensional rectangular coordinate system, the origin of the camera coordinate system is located at the optical center of a lens, an X axis and a Y axis are respectively parallel to two sides of a phase plane, a Z axis is a lens optical axis and is vertical to an image plane, the image coordinate system takes the image center as the origin of coordinates, and the X axis and the Y axis are parallel to the two sides of an image;
optimizing external parameters of the spherical screen camera and the laser sensor through a cost function;
wherein the cost function is:
6. the utility model provides a ball curtain camera and laser calibration device which characterized in that includes:
the calibration board is a checkerboard calibration board with MXN angular points, and the angular points are intersection points of checkerboards on the calibration board;
the internal reference calibration module is used for calibrating the internal reference of the dome camera;
the point cloud data processing module is used for acquiring the positions of four angular points in the point cloud data so as to acquire two-dimensional checkerboard angular points, and acquiring three-dimensional checkerboard angular points corresponding to the two-dimensional checkerboard angular points according to a pre-established matching relationship between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and the external parameter optimization module is used for optimizing the external parameters of the spherical screen camera and the laser sensor.
7. The dome camera and laser calibration device of claim 6, further comprising:
the point cloud filtering module is used for filtering the point cloud data;
the two-dimensional checkerboard angular point generation module is used for processing the filtered point cloud data and generating two-dimensional checkerboard angular points;
the matching relation establishing module is used for establishing the matching relation between the two-dimensional checkerboard angular points and the three-dimensional checkerboard angular points;
and the three-dimensional checkerboard corner generating module is used for generating three-dimensional checkerboard corners.
8. The dome camera and laser calibration device of claim 6, wherein the external parameters of the optimized dome camera and laser sensor specifically comprise:
rotating a three-dimensional point P _ lidar generated by a laser sensor through external reference to obtain a three-dimensional point under a camera coordinate system, and marking as P _ camera;
projecting the P _ camera to an image coordinate system through internal reference of a camera to obtain a P _ project, wherein the camera coordinate system is a three-dimensional rectangular coordinate system, the origin of the camera coordinate system is located at the optical center of a lens, an X axis and a Y axis are respectively parallel to two sides of a phase plane, a Z axis is a lens optical axis and is vertical to an image plane, the image coordinate system takes the image center as the origin of coordinates, and the X axis and the Y axis are parallel to the two sides of an image;
optimizing external parameters of the spherical screen camera and the laser sensor through a cost function;
wherein the cost function is:
9. computer device, characterized in that it comprises a memory and a processor, wherein said memory stores computer readable instructions, said processor when executing said computer readable instructions implements the steps of the calibration method of dome camera and laser according to any one of claims 1 to 5.
10. A computer readable storage medium, wherein the computer readable storage medium stores computer readable instructions, and when the computer readable instructions are executed by a processor, the steps of the calibration method of a dome camera and a laser according to any one of claims 1 to 5 are implemented.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110480932.0A CN113177988B (en) | 2021-04-30 | 2021-04-30 | Spherical screen camera and laser calibration method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110480932.0A CN113177988B (en) | 2021-04-30 | 2021-04-30 | Spherical screen camera and laser calibration method, device, equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113177988A true CN113177988A (en) | 2021-07-27 |
| CN113177988B CN113177988B (en) | 2023-12-05 |
Family
ID=76925747
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110480932.0A Active CN113177988B (en) | 2021-04-30 | 2021-04-30 | Spherical screen camera and laser calibration method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113177988B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115861445A (en) * | 2022-12-23 | 2023-03-28 | 广东工业大学 | Hand-eye calibration method based on calibration plate three-dimensional point cloud |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111862224A (en) * | 2019-04-17 | 2020-10-30 | 杭州海康威视数字技术股份有限公司 | Method and device for determining external parameters between camera and laser radar |
| WO2020233443A1 (en) * | 2019-05-21 | 2020-11-26 | 菜鸟智能物流控股有限公司 | Method and device for performing calibration between lidar and camera |
| CN112669393A (en) * | 2020-12-31 | 2021-04-16 | 中国矿业大学 | Laser radar and camera combined calibration method |
-
2021
- 2021-04-30 CN CN202110480932.0A patent/CN113177988B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111862224A (en) * | 2019-04-17 | 2020-10-30 | 杭州海康威视数字技术股份有限公司 | Method and device for determining external parameters between camera and laser radar |
| WO2020233443A1 (en) * | 2019-05-21 | 2020-11-26 | 菜鸟智能物流控股有限公司 | Method and device for performing calibration between lidar and camera |
| CN112669393A (en) * | 2020-12-31 | 2021-04-16 | 中国矿业大学 | Laser radar and camera combined calibration method |
Non-Patent Citations (2)
| Title |
|---|
| 孟勃;刘雪君;: "一种自动、快速的Kinect标定方法", 计算机工程与科学, no. 06 * |
| 许小徐;黄影平;胡兴;: "智能汽车激光雷达和相机数据融合系统标定", 光学仪器, no. 06 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115861445A (en) * | 2022-12-23 | 2023-03-28 | 广东工业大学 | Hand-eye calibration method based on calibration plate three-dimensional point cloud |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113177988B (en) | 2023-12-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP7060774B2 (en) | Calibration methods, devices, devices, storage media, and programs for external parameters of image acquisition devices | |
| CN110300292B (en) | Projection distortion correction method, device, system and storage medium | |
| CN111754578B (en) | Combined calibration method for laser radar and camera, system and electronic equipment thereof | |
| CN111738923A (en) | Image processing method, apparatus and storage medium | |
| CN110163087B (en) | Face gesture recognition method and system | |
| WO2023000595A1 (en) | Curved screen-based phase deflection measurement method and system, and terminal | |
| CN114387347B (en) | Method, device, electronic equipment and medium for determining external parameter calibration | |
| JP2022085910A (en) | Camera calibration method, apparatus, electronic device, storage medium, program, and roadside apparatus | |
| CN111323751A (en) | Sound source positioning method, device and storage medium | |
| CN111311671B (en) | Workpiece measuring method and device, electronic equipment and storage medium | |
| CN113177988A (en) | Calibration method, device, equipment and storage medium for dome camera and laser | |
| WO2023010565A1 (en) | Method and apparatus for calibrating monocular speckle structured light system, and terminal | |
| CN113763478B (en) | Unmanned vehicle camera calibration method, device, equipment, storage medium and system | |
| TW202247108A (en) | Visual positioning method, equipment, and medium | |
| CN111161348A (en) | Monocular camera-based object pose estimation method, device and equipment | |
| CN110415196A (en) | Method for correcting image, device, electronic equipment and readable storage medium storing program for executing | |
| CN114359400A (en) | External parameter calibration method and device, computer readable storage medium and robot | |
| CN108650465B (en) | Method and device for calculating augmented reality label of camera picture and electronic equipment | |
| CN113759346A (en) | Laser radar calibration method and device, electronic equipment and storage medium | |
| CN112652056A (en) | 3D information display method and device | |
| CN113643358B (en) | External parameter calibration method, device, storage medium and system of camera | |
| CN103674010B (en) | Produce method and the guider of an image bar code and a navigation picture | |
| WO2023103884A1 (en) | Object model establishment method and apparatus, and electronic device and storage medium | |
| CN117710597A (en) | Three-dimensional modeling method and system based on oblique photographic data and electronic equipment | |
| CN115014202A (en) | Line structured light vision sensor calibration method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |