CN114690226A - Monocular vision distance measurement method and system based on carrier phase difference technology assistance - Google Patents
Monocular vision distance measurement method and system based on carrier phase difference technology assistance Download PDFInfo
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- CN114690226A CN114690226A CN202210345160.4A CN202210345160A CN114690226A CN 114690226 A CN114690226 A CN 114690226A CN 202210345160 A CN202210345160 A CN 202210345160A CN 114690226 A CN114690226 A CN 114690226A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
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Abstract
The invention provides a monocular vision distance measurement method and a monocular vision distance measurement system based on the carrier phase differential technology assistance, which comprise the following steps: acquiring multi-frame images in the advancing direction of a vehicle and the vehicle position positioned in real time by a carrier phase differential technology, acquiring the characteristic points and the characteristic point coordinates of a single-frame image, and calculating the distance between each pixel point and a reference point in the image through the longitudinal axis pixel difference and the vehicle displacement difference of the same characteristic point in the two frames of images before and after to obtain a reference distance vector table; acquiring an image containing a target object in real time, identifying pixel points where the target object is located, searching the target object pixel points from a reference distance vector table, and outputting the distance between the target object and a vehicle; the method integrates the differential positioning technology into the monocular vision distance measurement technology, effectively solves the problems that the traditional monocular vision distance measurement algorithm is low in precision and requires early calibration and preparation work and the like, and greatly improves the feasibility and reliability of monocular vision distance measurement in practical engineering application.
Description
Technical Field
The invention belongs to the technical field of computer vision, and particularly relates to a monocular vision distance measurement method and system based on carrier phase difference technology assistance.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Under the condition that social economy is continuously promoted and the pace of informatization construction is accelerated, the integration of high-end technologies such as various modern information technologies, communication technologies, computer vision technologies, navigation positioning technologies and the like becomes more and more important trends and directions for development, wherein the front object distance measurement technology based on computer vision is an important branch of the high-end technologies, and has great scientific research and application values.
Compared with a binocular vision system, the image ranging technology based on monocular vision is simple in structure, and correspondingly, calibration of a camera is simple, so that the problem of stereo matching in binocular vision is solved, and the image ranging technology based on monocular vision has the advantages of being simple in equipment, low in cost, simple in measuring process and the like. However, monocular vision ranging generally adopts a corresponding point calibration method to acquire depth information of an image, that is, a conversion relation of a coordinate system is solved through corresponding coordinates of corresponding points in different coordinate systems, but in the calibration process, due to the limitation of receiving materials, the corresponding coordinates of a point in a world coordinate system and an image coordinate system cannot be recorded very accurately, if the coordinates are not accurate enough, the accuracy of the obtained conversion matrix is also limited, and the accuracy of the coordinate conversion result fluctuates accordingly, because the calibration of the corresponding point calibration method for the camera is performed under the condition that each angle and height of the camera are determined, when any parameter of the camera changes, the calibration is performed again to obtain the conversion matrix under the specific condition, the method is only suitable for the condition of the camera with a fixed position, due to the technological and technical limitations of the existing monocular vision equipment, the problems of low precision, use of calibration at the early stage and the like are caused, and the problems need to be considered and solved in the practical application process.
In a Global Navigation Satellite System (GNSS), rtk (real Time kinematic), which is a carrier phase differential technique, can provide a three-dimensional positioning result of a station in a specified coordinate System in real Time, and achieve centimeter-level accuracy, and is widely applied in practical applications, and also brings a hope for solving a calibration problem in a monocular visual image ranging technique.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a monocular vision distance measurement method and system based on the carrier phase difference technology assistance, the vehicle position is positioned by the carrier phase difference technology RTK assistance, the problems of low monocular vision distance measurement precision, complicated preparation work such as early calibration and the like are solved, and the feasibility and reliability of monocular vision distance measurement in practical engineering application are effectively improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a monocular vision ranging method assisted by a carrier phase differential technology, which comprises the following steps:
acquiring multi-frame images in the advancing direction of a vehicle and the vehicle position positioned in real time by a carrier phase differential technology, and calculating the distance between each pixel point and a reference point in the images through the longitudinal axis pixel difference and the vehicle displacement difference of the same characteristic point in the front and back two frames of images to obtain a reference distance vector table;
the method comprises the steps of collecting images containing a target object in real time, identifying pixel points where the target object is located, searching the pixel points of the target object in a reference distance vector table, and outputting the distance between the target object and a vehicle.
The vehicle-mounted monocular camera is used for shooting images in the advancing direction of the vehicle, and the vehicle position when each frame of image is shot is obtained by utilizing a carrier phase difference technology.
Constructing a reference distance vector table, which comprises the following specific steps:
extracting feature points and feature point coordinates of a single frame image from the acquired image, calculating a longitudinal axis pixel difference and a vehicle displacement difference of the same feature point in two frames of images before and after, and establishing a pixel distance vector table of the longitudinal axis pixel and pixel distance difference;
and calculating the distance between each pixel point in the image and the reference point based on the pixel distance vector table to obtain a reference distance vector table.
The method for acquiring the characteristic points and the characteristic point coordinates comprises the following steps: and denoising and filtering the image by adopting Gaussian filtering, extracting characteristic points by using a Fast algorithm, inhibiting and eliminating redundant characteristic points by adopting a non-maximum value, and identifying the coordinates of the residual characteristic points.
The vertical axis pixel difference of the same feature point in the two front and back frames of images is the vertical coordinate difference of the same feature point in the two frames of images, and the vehicle displacement difference is the distance difference of the vehicle positions when the two frames of images are respectively shot.
And updating and correcting the established pixel distance vector table in real time, comparing the newly calculated pixel distance difference with the pixel distance difference in the pixel distance vector table, if the pixel distance difference is larger than a threshold value, updating the pixel distance vector table, and otherwise, not updating.
And the reference point selects a pixel point close to the lowest corner of the vehicle in the image, and the reference distance vector table comprises the distances from all the pixel points in the image to the reference point.
And carrying out target detection on the acquired monocular vision system image by using a target detection system, extracting the pixel point coordinates of the bottom edge of the boundary frame of the detected target, and searching a reference distance vector table to obtain the distance from the target to the vehicle.
In a second aspect, the present invention provides a monocular vision ranging system assisted by a carrier-phase differential technique, comprising:
a reference distance vector table building module configured to: acquiring multi-frame images in the advancing direction of a vehicle and the position of the vehicle positioned in real time by a carrier phase differential technology, acquiring characteristic points and characteristic point coordinates of a single-frame image, and calculating the distance between each pixel point and a reference point in the image through the longitudinal axis pixel difference and the vehicle displacement difference of the same characteristic point in the front and back two frames of images to obtain a reference distance vector table;
a ranging module configured to: the method comprises the steps of acquiring an image containing a target object in real time, identifying pixel points where the target object is located, searching the target object pixel points from a reference distance vector table, and outputting the distance between the target object and a vehicle.
In a third aspect, the present invention provides an electronic device, comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the monocular visual ranging method based on carrier-phase differential technology assistance.
In a fourth aspect, the present invention provides a computer readable storage medium for storing computer instructions, which when executed by a processor, perform the steps of the monocular visual ranging method based on carrier-phase differential technology assistance.
The above one or more technical solutions have the following beneficial effects:
the invention is based on the traditional computer vision processing, integrates the differential positioning technology into the monocular vision distance measurement technology, effectively improves the problems of low precision of the traditional monocular vision distance measurement algorithm, the requirement of early calibration and preparation work of the monocular vision distance measurement and the like, and greatly improves the feasibility and the reliability of the monocular vision distance measurement in the practical engineering application. In addition, the monocular camera is low in price, and the computer vision algorithm is relatively simple, so that the cost and the expenditure of the original system are not greatly influenced.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a general frame diagram of a monocular vision distance measuring method and system based on the carrier-phase differential technology assistance of the present invention.
FIG. 2 is a schematic diagram of datum selection according to the present invention.
Fig. 3 is a flowchart illustrating initialization implementation of the monocular visual ranging method based on the carrier-phase differential technology.
FIG. 4 is a diagram illustrating pixel distance differences according to an embodiment of the present invention.
FIG. 5 is a diagram of a pixel in a pixel distance vector table according to an embodiment of the present invention.
FIG. 6 is a flowchart illustrating an implementation of an optimized pixel distance vector table in the monocular visual ranging method based on the carrier-phase differential technique of the present invention.
FIG. 7 is a diagram illustrating a target detection result according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. 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.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The general idea provided by the invention is as follows:
the position of a vehicle in the process of traveling is positioned in real time through a carrier phase differential technology, a camera fixed in the front of the vehicle collects a front image, unit distance difference between pixels is calculated through linear fitting according to the difference of longitudinal axis pixels of the same characteristic point in two frames of images and the displacement difference of the real-time position of the vehicle, the process is repeated, a reference distance vector table formed by the distance from each pixel point in the image to a reference point is built, and the distance from a measured object to the vehicle is obtained by searching the distance corresponding to the lower edge pixel of the measured object in the reference distance vector table.
Example one
The embodiment discloses a monocular vision distance measuring method based on carrier phase difference technology assistance
As shown in fig. 1, the embodiment provides a monocular visual ranging method assisted by a carrier-phase differential technique, which includes:
s1: acquiring multi-frame images in the advancing direction of a vehicle and the vehicle position positioned in real time by a carrier phase differential technology, acquiring the characteristic points and the characteristic point coordinates of a single-frame image, and calculating the distance between each pixel point and a reference point in the image through the longitudinal axis pixel difference and the vehicle displacement difference of the same characteristic point in the two frames of images before and after to obtain a reference distance vector table;
s2: the method comprises the steps of collecting images containing a target object in real time, identifying pixel points where the target object is located, searching the pixel points of the target object from a reference distance vector table, and outputting the distance between the target object and a vehicle.
In step S1, the vehicle-mounted monocular camera is used to capture an image of the vehicle in the forward direction, and the carrier phase differential technique is used to obtain the vehicle position when each frame of image is captured, and the reference point is shown in fig. 2, and a pixel point near the lowest corner of the vehicle in the image is selected.
The specific steps of constructing the reference distance vector table are as follows:
s-1-1: extracting feature points and feature point coordinates of a single frame image from the acquired image, calculating a longitudinal axis pixel difference and a vehicle displacement difference of the same feature point in two frames of images before and after, and establishing a pixel distance vector table of the longitudinal axis pixel and pixel distance difference;
s-1-2: calculating the distance between each pixel point in the image and the reference point based on the pixel distance vector table to obtain a reference distance vector table;
as shown in fig. 3, the table of pixel distance vectors of the vertical axis pixel-to-pixel distance differences includes the following steps:
step a: keeping the vehicle going straight ahead, acquiring an image in the driving process through a monocular vision camera, processing the image, carrying out denoising and filtering processing on the image by adopting Gaussian filtering, extracting feature points by using a Fast algorithm, inhibiting and eliminating redundant feature points by adopting a non-maximum value, and forming the residual feature points into a set Cp＝{p0，p1，…pn-1，pnAnd a corresponding set of pixel coordinate information S ″p＝{(x0，y0)，(x1，y1)…(xn-1，yn-1)，(xn，yn) Simultaneously positioning the vehicle position at the moment of image shooting by using RTK, and recording as p ″ (lat ″, lon ″, h ″);
step b: tracking the feature points by using an LK optical flow method, deleting the feature points lost by tracking and updating a set CpAnd corresponding sets of pixel coordinate information
Positioning the vehicle position simultaneously using RTK, note
Step c: traverse set CpThe assumed feature point plThe pixel information of the two previous and next frames of images are respectively
Wherein
The pixel difference is then expressed as:
displacement difference between two frame images:
wherein R is the radius of the earth;
for vertical axis pixel
Performing linear fitting on pixels in the range to obtain pixel distance difference
For vertical axis pixel
Linear interpolation, iterative recording and updating are carried out on longitudinal axis pixel points in the middle of the range
Storing the vertical axis pixel in the range and corresponding pixel distance difference information into a pixel distance vector table, wherein the pixel distance difference is
Actual distance corresponding to unit pixel in the range;
step d: repeating steps a through c until the vertical axis pixels substantially cover the image vertical axis kernel region, as shown in fig. 5;
the pixel distance vector table may also be updated and corrected in real time, as shown in fig. 6, the specific method is as follows:
step e: under the condition that the satellite positioning condition of the vehicle is better judged, the image in the driving process is obtained through the monocular vision camera, the image is processed, the image is subjected to denoising and filtering processing through Gaussian filtering, feature points are extracted through a Fast algorithm, redundant feature points are suppressed and eliminated through a non-maximum value, and the residual feature points form a set Cp＝{p0，p1，…pn-1，pnAnd a corresponding set of pixel coordinate information S ″p＝{(x0，y0)，(x1，y1)…(xn-1，yn-1)，(xn，yn) To simultaneously profitPositioning the position of the key frame time by using RTK, and recording as p ″ ═ lat ″, lon ″, h ″;
step f: tracking the feature points by using an LK optical flow method, deleting the feature points lost by tracking and updating a set CpAnd corresponding sets of pixel coordinate information
At the same time, the position of the key frame time is positioned by using RTK and recorded as
Step g: traverse set CpThe assumed feature point plThe pixel information of the two frames of images before and after are respectively
Wherein
The pixel difference is then expressed as:
displacement difference between two frame images:
wherein R is the radius of the earth;
for vertical axis pixel
Performing linear fitting on pixels in the range to obtain unit distance difference between the pixels
step h: repeating the steps e to g until the set CpThe characteristic point in (1) is null;
the threshold value is set to 10 cm.
In step S-1-2, the pixel point reaches the reference point CoThe distance calculating method of (2) is:
traversing each pixel point (x, y) in the pixel distance vector table, and adding the pixel distance difference of each longitudinal axis pixel less than or equal to y to obtain the pixel point (x, y) to the reference point CoThe distance of (d);
the longitudinal axis pixel of the pixel point in the pixel distance vector table covers the longitudinal axis core area of the image, and each pixel in the image reaches the reference point CoThe distance can be calculated, so that a reference distance vector table consisting of each pixel point in the image and the distance from the pixel point to the reference point is constructed, and the distance of the detected target in the image can be measured after the reference distance vector table is constructed.
As shown in fig. 7, in the vehicle traveling process, to measure the distance between the target object and the vehicle, the camera is used to collect the image of the target object, then the target detection system is used to perform target detection, the coordinate information of the bottom edge of the boundary frame of the detected target is extracted, the lower edge pixel point of the detection frame is selected as the position of the target object, and the distance between the target object and the vehicle is obtained by looking up the reference distance vector table.
Example two
The object of this embodiment is to provide a monocular visual ranging system assisted by a carrier-phase differential technique, which includes:
a reference distance vector table building module configured to: acquiring multi-frame images in the advancing direction of a vehicle and the position of the vehicle positioned in real time by a carrier phase differential technology, acquiring characteristic points and characteristic point coordinates of a single-frame image, and calculating the distance between each pixel point and a reference point in the image through the longitudinal axis pixel difference and the vehicle displacement difference of the same characteristic point in the front and back two frames of images to obtain a reference distance vector table;
a ranging module configured to: the method comprises the steps of acquiring an image containing a target object in real time, identifying pixel points where the target object is located, searching the target object pixel points from a reference distance vector table, and outputting the distance between the target object and a vehicle.
EXAMPLE III
It is an object of this embodiment to provide a computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the program.
Example four
An object of the present embodiment is to provide a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
The steps involved in the apparatuses of the above second, third and fourth embodiments correspond to the first embodiment of the method, and the detailed description thereof can be found in the relevant description of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media containing one or more sets of instructions; it should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any of the methods of the present invention.
Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code that is executable by computing means, such that they are stored in memory means for execution by the computing means, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps of them are fabricated into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. A monocular vision distance measurement method based on carrier phase differential technology assistance is characterized by comprising the following steps:
acquiring multi-frame images in the advancing direction of a vehicle and the vehicle position positioned in real time by a carrier phase differential technology, and calculating the distance between each pixel point and a reference point in the images through the longitudinal axis pixel difference and the vehicle displacement difference of the same characteristic point in the front and back two frames of images to obtain a reference distance vector table;
the method comprises the steps of collecting images containing a target object in real time, identifying pixel points where the target object is located, searching the pixel points of the target object in a reference distance vector table, and outputting the distance between the target object and a vehicle.
2. The method as claimed in claim 1, wherein the monocular vision distance measuring method assisted by carrier phase differential technology is characterized in that the on-board monocular camera is used to capture images of the advancing direction of the vehicle, and the carrier phase differential technology is used to obtain the position of the vehicle when each frame of image is captured.
3. The method for monocular visual ranging assisted by a carrier-phase differential technique as claimed in claim 1, wherein the step of constructing the reference distance vector table comprises the following steps:
s-1-1: extracting feature points and feature point coordinates of a single frame image from the acquired image, calculating a longitudinal axis pixel difference and a vehicle displacement difference of the same feature point in two frames of images before and after, and establishing a pixel distance vector table of the pixel coordinates and the pixel distance difference;
s-1-2: and calculating the distance between each pixel point in the image and the reference point based on the pixel distance vector table to obtain a reference distance vector table.
4. The method for monocular visual ranging assisted by a carrier-phase differential technique according to claim 3, wherein the method for obtaining the feature points and the feature point coordinates comprises: and denoising and filtering the image by adopting Gaussian filtering, extracting characteristic points by using a Fast algorithm, inhibiting and eliminating redundant characteristic points by adopting a non-maximum value, and identifying the coordinates of the residual characteristic points.
5. The method as claimed in claim 3, wherein the pixel distance vector table established in step S-1-1 is updated and corrected in real time, and the newly calculated distance difference is compared with the pixel distance difference in the pixel distance vector table and is greater than the threshold value, the pixel distance vector table is updated, otherwise the pixel distance vector table is not updated.
6. The method as claimed in claim 1, wherein the reference point is a pixel point near the lowest corner of the vehicle in the image, and the reference distance vector table includes distances from all pixel points in the image to the reference point.
7. The monocular visual ranging method based on carrier-phase differential technology as claimed in claim 1, wherein a target detection system is used to perform target detection on the acquired monocular visual system image, extract pixel coordinates of the bottom edge of the boundary frame of the detected target, and obtain the distance from the target to the vehicle by looking up a reference distance vector table.
8. Monocular vision range finding system based on supplementary technique of carrier phase difference, its characterized in that includes:
a reference distance vector table building module configured to: acquiring a multi-frame image of a vehicle advancing direction and a vehicle position positioned in real time by a carrier phase differential technology, acquiring a characteristic point and a characteristic point coordinate of a single-frame image, and calculating the distance between each pixel point and a reference point in the image through a longitudinal axis pixel difference and a vehicle displacement difference of the same characteristic point in two frames of images in front and back to obtain a reference distance vector table;
a ranging module configured to: and acquiring an image containing the target object in real time, identifying pixel points where the target object is located, searching the target object pixel points from the reference distance vector table, and outputting the distance between the target object and the vehicle.
9. A computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, is adapted to carry out the steps of the method according to any one of the preceding claims 1 to 7.
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| CN116543032B (en) * | 2023-07-06 | 2023-11-21 | 中国第一汽车股份有限公司 | Impact object ranging method, device, ranging equipment and storage medium |
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