CN110133663B - Distributed acoustic image joint calibration positioning method - Google Patents
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- G—PHYSICS
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- 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
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
- G01S15/06—Systems determining the position data of a target
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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
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
- G01S15/06—Systems determining the position data of a target
- G01S15/08—Systems for measuring distance only
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Abstract
The invention provides a distributed acoustic image joint calibration positioning method, which is characterized in that a camera, an air sonar and the like are installed above a road at equal heights, the distance between the air sonar and the center of the camera is determined, and a three-dimensional rectangular coordinate system with the center of the air sonar array and the video center of the camera as the origin is constructed; determining the position coordinates of the target in an air sonar coordinate system through an air sonar, and calculating the included angle between the target and a horizontal plane and a plumb bob plane under a camera coordinate system through the transverse horizontal distance of two origins and an inverse trigonometric function formula; calculating the corresponding pixel coordinates of the target in the camera picture according to the camera parameters; and reflecting the sound source target position in a camera picture through pixel coordinates to realize sound image joint calibration and positioning. The invention can realize the combination of city vision and hearing and provide enough technical support for the development of intelligent transportation and intelligent cities.
Description
Technical Field
The invention belongs to the field of signal processing, and relates to the theories of sonar beam forming, acoustic signal detection, acoustic image combination, target positioning and the like.
Background
With the progress of social science and technology, cameras and air sonars play more and more important roles in the social fields of traffic, security, environmental protection and the like. Through the combined work of the camera and the air sonar, the combination and the combined calibration of the video image and the real-time audio frequency are realized, and the accurate positioning of the sounding target in the video image is realized.
An air sonar is generally a microphone array composed of a plurality of high-precision microphone modules, and has functions such as acoustic positioning, sound recognition, and sound enhancement. Since the last 80 years, the array signal processing technology is widely applied to the research of passive positioning of a sound source, but the sound positioning effect is abstract and cannot be visually represented in the existing urban sensory equipment, so that the specific position of the sound source can be more visually reflected by using the array signal processing technology in combination with a camera system.
At present, a better joint calibration method for sonar positioning and video is not available, an air sonar and a camera are installed in a distributed mode in practical application, the air sonar is not accurately mapped to a camera picture due to the fact that the air sonar is not coincident with the center origin of the camera, conversion marking needs to be performed in a video image manually, accuracy is not accurate enough, and automatic accurate joint positioning cannot be achieved.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a distributed sound-image joint calibration method, which realizes the combination of urban vision and hearing, provides enough technical support for the development of intelligent transportation and intelligent cities, and has great significance for the development of accurate positioning of vehicle targets in cities and actual engineering application.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps: installing a camera, an air sonar and the like above a road, determining the distance between the air sonar and the center of the camera, and constructing a three-dimensional rectangular coordinate system with the center of the air sonar array and the video center of the camera as the origin; determining the position coordinates of the target in an air sonar coordinate system through an air sonar, and calculating the included angle between the target and a horizontal plane and a plumb bob plane under a camera coordinate system through the transverse horizontal distance of two origins and an inverse trigonometric function formula; calculating the corresponding pixel coordinates of the target in the camera picture according to the camera parameters; and reflecting the target position of the sound source in a camera picture through pixel coordinates to realize the combined calibration and positioning of the sound image.
The steps of the invention are developed, and the method specifically comprises the following steps:
firstly, a camera is installed at the transverse center above a road, an air sonar and a camera are installed at equal height, and an air sonar array center and a camera video center are respectively used as original points to buildVertical three-dimensional rectangular coordinate system o 1 And o 2 The horizontal distance between the two origins is d;
secondly, passively positioning and determining the target s in the air sonar coordinate system o through the air sonar 1 The included angle alpha between the horizontal plane and the vertical plane of the mounting rod, and the position coordinates (a, b, h) of the target in the air sonar coordinate system are calculated through a trigonometric function, wherein,
h is the height of the mounting rod;
thirdly, calculating the included angle between the target and the horizontal plane in the camera coordinate system
And the included angle with the vertical surface of the mounting rod
Fourthly, determining the picture pixel size of the camera as mxn, adjusting the field angle of the camera as theta, and measuring the distance d from the bottom edge in the field of view of the camera to the monitoring rod piece 1 ；
Fifthly, calculating the Y-axis pixel coordinate of the target in the camera picture
And pixel coordinates in the X axis
Wherein xl is the pixel distance from the center to the left road boundary on the X-axis, xr is the pixel distance from the center to the right road boundary, the pixel position of the road boundary in the picture can be represented as a straight line, kl is the slope of the left boundary in the coordinate system, and kr is the slope of the right boundary in the coordinate system;
and sixthly, determining and reflecting the sound source target position on the image through the pixel coordinates, and realizing the combined calibration and positioning of the sound image.
The beneficial effects of the invention are: the method is simple and practical, can reflect various acoustic signal targets on the road in the image of the camera in real time, can be used for the fields of illegal whistle vehicle positioning, suspicious target positioning, environmental noise monitoring and the like, has profound significance for establishing intelligent traffic, perfecting city security, building smart cities and the like, and promotes the application and development of passive positioning technology in the fields of traffic, security, monitoring and the like.
Drawings
FIG. 1 is a schematic block diagram of the process flow of the present invention;
FIG. 2 is a schematic view of an air sonar and camera mounting location;
FIG. 3 is a schematic view of a camera mounting;
fig. 4 is a schematic view of a monitor screen display.
Detailed Description
The present invention will be further described with reference to the following drawings and examples, which include, but are not limited to, the following examples.
Aiming at the problem that in practical application, when an air sonar and a camera are installed in a distributed mode, the center origin of the air sonar and the center origin of the camera are not coincident, and the air sonar positioning effect is difficult to accurately map to a camera picture, the invention provides the distributed acoustic image positioning combined calibration method.
As shown in fig. 1, the distributed acoustic image joint calibration method provided by the present invention mainly includes the following steps:
the first step is as follows: determining the distance between the air sonar and the center of the camera
As shown in FIG. 2, the cameras and the air sonar are installed in a distributed mode, the cameras are installed at the transverse central position of the road, and the air sonar is locatedEstablishing a three-dimensional rectangular coordinate system with the air sonar array center and the video center of the camera as the original points and respectively being o beside the camera 1 And o 2 The lateral horizontal distance of the two origins is d.
The second step is that: air sonar positioning
Through passive positioning of air sonar, target s is determined in air sonar coordinate system o 1 The included angle alpha between the horizontal plane and the vertical plane of the installation rod and the included angle beta between the vertical plane of the installation rod are calculated, and the position coordinates (a, b, h) of the target in the air sonar coordinate system are calculated through a trigonometric function
Where h is the height of the mounting bar, i.e., the z-axis coordinate of the target.
The third step: calculating the included angle of the target in the coordinate system of the camera
The camera and the air sonar are arranged at the same height h, and the included angle alpha between the target and the horizontal plane in the camera coordinate system is calculated through the horizontal distance between the two original points and the inverse trigonometric function formula 1 And the angle beta with the vertical plane of the mounting rod 1 ：
Where d is the lateral horizontal distance of the two coordinate system origins.
The fourth step: determining parameters of a camera
The picture pixel size of the camera is mxn, the field angle of the camera is adjusted to theta, and the bottom edge in the field of view of the camera is measuredDistance d from the monitoring rod 1 As shown in particular in fig. 3.
The fifth step: calculating the corresponding pixel position of the target in the camera picture
As shown in fig. 4, the corresponding pixel position of the object on the Y-axis in the screen:
the pixel coordinates of the target in the X-axis direction can be expressed as:
wherein xl is the pixel distance from the center to the left road boundary on the X-axis, xr is the pixel distance from the center to the right road boundary, the pixel position of the road boundary in the picture can be represented as a straight line, kl is the slope of the left boundary in the coordinate system, and kr is the slope of the right boundary in the coordinate system.
And a sixth step: sound image joint localization
And determining and reflecting the sound source target position on the image through the pixel coordinates to realize the sound image joint calibration and positioning.
An embodiment of the invention comprises the following steps:
the first step is as follows: determining the distance between the air sonar and the center of the camera
The camera and the air sonar are installed in a distributed mode, the camera is installed at the transverse center of a road, the air sonar is located beside the camera, and a three-dimensional rectangular coordinate system is established by respectively taking the center of the air sonar array and the video center of the camera as the origin to be o 1 And o 2 The lateral horizontal distance of the two origins is d.
In the coordinate system, any point s on the road has a unique corresponding point with the coordinate system of the air sonar and the camera. Under the three-dimensional coordinate system, the vector of the line connecting any point s on the road plane and the origin o is
Then vector
In the plane Y 0 O O Z O Is projected as
Then vector
In plane X 0 O O Z O Is projected as
The definition of the method is that,
the included angle between the Y axis and the Y axis is alpha,
if the angle between the x-axis and the x-axis is beta, a point s can be uniquely identified by alpha and beta.
The second step is that: air sonar positioning
Target s is determined in air sonar coordinate system o through air sonar passive positioning 1 The included angle alpha between the middle part and the horizontal plane and the included angle beta between the middle part and the vertical plane of the mounting rod. And calculating the position coordinates (a, b, h) of the target in the air sonar coordinate system through a trigonometric function
Where h is the height of the mounting bar, i.e., the z-axis coordinate of the target.
The third step: calculating the included angle of the target in the camera coordinate system
The camera and the air sonar are arranged at the same height h, and the included angle alpha between the target and the horizontal plane in the camera coordinate system is calculated through the horizontal distance between the two original points and an inverse trigonometric function formula 1 And the angle beta with the vertical plane of the mounting rod 1 ：
Where d is the lateral horizontal distance of the two coordinate system origins.
The fourth step: determining parameters of a camera
The picture pixel size of the camera is mxn, the field angle of the camera is adjusted to theta, and the distance between the bottom edge in the field of view of the camera and the monitoring rod piece is measured to d 1 As shown in fig. 3:
the fifth step: calculating the corresponding pixel position of the target in the camera picture:
because there is a one-to-one correspondence between the pixels of the camera view and the field angle, for a given arbitrary target location in the camera coordinate system, the corresponding pixel location of the target on the Y-axis in the view can be determined:
in the X-axis direction, the angles do not correspond to the pixels one to one, but the distances correspond to the angles one to one, and if sl represents the actual distance from the left boundary of the road to the Y-axis, sr represents the actual distance from the right boundary of the road to the Y-axis, the left boundary of the road in the camera frame can be represented as a straight line perpendicular to the X-axis in the camera coordinate system:
x＝sl
the right side boundary of the road can also be expressed as a straight line perpendicular to the X axis
x＝-sr
The coordinate system shown in fig. 4 is re-established in the monitoring picture of the camera road, and the pixel position of the target corresponding to the Y axis in the picture is converted into:
n 11 ＝n-n 1
assuming that the center of the camera image is O, the pixel distance from the center on the X-axis to the left road boundary in the image is xl, and the pixel distance from the center to the right road boundary in the image is xr, it can be seen that the pixel position of the road boundary in the image can be represented as a straight line, the slope of the left boundary in the coordinate system is kl, and the slope of the right boundary in the coordinate system is kr.
The pixel boundary on the left X-axis can be expressed as:
y＝kl×x+b b＝-kl×xl
the pixel boundary on the right X-axis can be expressed as:
y＝kr×x+b b＝-kr×xr
the pixel distance xl from the center of the X-axis picture to the left road boundary, the pixel distance xr from the right road boundary, the left boundary slope kl and the right boundary slope kr can be calibrated and obtained on the picture of the camera.
At a known Y-axis pixel location n 1 Under the condition (2), the actual pixel distance of the road boundary at that time can be obtained.
Left boundary distance X left Expressed as:
right side boundary distance X right Expressed as:
when the coordinates of the target s in the camera coordinate system are (a-d, b, h), the pixel coordinates in the X-axis direction can be expressed as:
namely:
and a sixth step: sound image joint localization
And determining and reflecting the sound source target position on the image through the pixel coordinates to realize the sound image joint calibration and positioning.
Claims (2)
1. A distributed sound image joint calibration positioning method is characterized by comprising the following steps: installing a camera, an air sonar and the like above a road, determining the distance between the air sonar and the center of the camera, and constructing a three-dimensional rectangular coordinate system with the center of the air sonar array and the video center of the camera as the origin; determining the position coordinates of the target in an air sonar coordinate system through an air sonar, and calculating the included angle between the target and a horizontal plane and a plumb bob plane under a camera coordinate system through the transverse horizontal distance of two origins and an inverse trigonometric function formula; calculating the corresponding pixel coordinates of the target in the camera picture according to the camera parameters; and reflecting the sound source target position in a camera picture through pixel coordinates to realize sound image joint calibration and positioning.
2. The distributed sound image joint alignment localization method according to claim 1, characterized by comprising the steps of:
firstly, a camera is installed at the transverse center position above a road, an air sonar and the camera are installed at equal heights, and a three-dimensional rectangular coordinate system o is established by taking the air sonar array center and the video center of the camera as the origin points 1 And o 2 The horizontal distance between the two origins is d;
secondly, passively positioning and determining the target s in the air sonar coordinate system o through the air sonar 1 The included angle alpha between the horizontal plane and the vertical plane of the mounting rod and the position coordinates (a, b, h) of the target in the air sonar coordinate system are calculated through a trigonometric function,wherein,
h is the height of the mounting rod;
thirdly, calculating the included angle between the target and the horizontal plane in the camera coordinate system
And the included angle with the vertical surface of the mounting rod
Fourthly, determining the picture pixel size of the camera as m multiplied by m, adjusting the field angle of the camera as theta, and measuring the distance d from the bottom edge in the field of view of the camera to the monitoring rod piece 1 ；
Fifthly, calculating the Y-axis pixel coordinate of the target in the camera picture
And pixel coordinates in the X axis
Wherein xl is the pixel distance from the center to the left road boundary on the X-axis, xr is the pixel distance from the center to the right road boundary, the pixel position of the road boundary in the picture can be expressed as a straight line, kl is the slope of the left boundary in the coordinate system, kr is the slope of the right boundary in the coordinate system, n 11 The corresponding pixel position of the target on the Y axis in the picture is shown, sl represents the actual distance from the boundary on the left side of the road to the Y axis, and sr represents the actual distance from the boundary on the right side of the road to the Y axis;
and sixthly, determining and reflecting the sound source target position on the image through the pixel coordinates, and realizing the combined calibration and positioning of the sound image.
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| CN110441737B (en) * | 2019-08-26 | 2023-02-24 | 上海声茵科技有限公司 | Sound source positioning method and equipment adopting fisheye lens |
| CN110672313B (en) * | 2019-10-22 | 2021-06-01 | 上海声茵科技有限公司 | Fault diagnosis method and equipment based on sound signals |
| CN110807901B (en) * | 2019-11-08 | 2021-08-03 | 西安联丰迅声信息科技有限责任公司 | Non-contact industrial abnormal sound detection method |
| CN111915918A (en) * | 2020-06-19 | 2020-11-10 | 中国计量大学 | System and method for calibrating automobile whistling snapshot device on site based on dynamic characteristics |
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Denomination of invention: A Distributed Audio Image Joint Calibration and Localization Method Granted publication date: 20230310 Pledgee: Xi'an Caijin Financing Guarantee Co.,Ltd. Pledgor: LIANFENG ACOUSTIC TECHNOLOGIES Co.,Ltd. Registration number: Y2024980011038 |