CN107945166B - Binocular vision-based method for measuring three-dimensional vibration track of object to be measured - Google Patents
Binocular vision-based method for measuring three-dimensional vibration track of object to be measured Download PDFInfo
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Abstract
The invention discloses a binocular vision-based method for measuring a three-dimensional vibration track of an object to be measured, which comprises the following steps of: shooting an object to be detected by using two cameras to obtain video stream data; selecting one frame of data at the same time as a first frame from the video stream data of the two cameras, and obtaining the pixel coordinates of the object to be detected in the first frame; calculating the offset vector of the object to be detected between the second frame and the first frame through the pixel similarity, obtaining the matched pixel coordinates of the object to be detected in the second frame, and calculating the world coordinates of the object to be detected in the second frame by combining the pixel coordinates of the two cameras and the world coordinates; calculating the estimated pixel coordinate of the third frame and the corresponding world coordinate of the object to be detected in the third frame by using the matched pixel coordinate of the object to be detected in the second frame and the pixel similarity of the second frame and the third frame; and repeating the steps until the three-dimensional vibration track of the object to be measured in the measuring time period is obtained. The method is simple and has high measurement precision.
Description
Technical Field
The invention relates to the field of video monitoring, in particular to a binocular vision-based method for measuring a three-dimensional vibration track of an object to be measured.
Background
In order to reduce noise of the rotating equipment, the operating condition of the rotating equipment needs to be monitored to obtain vibration information of the rotating equipment, so that the noise of the rotating equipment during operation is reduced by adopting an active noise reduction method. The traditional method for monitoring the operation of the rotating equipment usually adopts a strain gauge type measuring method, which is mainly used in two dimensions or even one dimension, but cannot be realized in three dimensions. The three-dimensional vibration information of the rotating equipment can provide a large amount of operation data for workers to reduce noise of the rotating equipment. At present, the problem of obtaining three-dimensional vibration information of instrument equipment is difficult.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a binocular vision-based method for measuring the three-dimensional vibration track of an object to be measured, which can obtain the three-dimensional vibration track of the object to be measured, is simple and practical and has high measurement precision.
In order to achieve the above purposes, the technical scheme adopted by the invention is as follows: the binocular vision-based method for measuring the three-dimensional vibration track of the object to be measured comprises two cameras with different directions, wherein lens surfaces of the two cameras are positioned on the same plane, and central axes of the two cameras are parallel; which comprises the following steps:
shooting an object to be detected by using two cameras, and obtaining video stream data of the two cameras;
selecting one frame of data at the same time as a first frame from the video stream data of the two cameras, and obtaining the pixel coordinates of the object to be detected in the first frame;
calculating an offset vector of the object to be measured between the second frame and the first frame through the pixel similarity, obtaining an estimated pixel coordinate of the object to be measured in the second frame, determining the estimated pixel coordinate as a matched pixel coordinate of the object to be measured in the second frame if the estimated pixel coordinate meets the precision requirement, and calculating a world coordinate of the object to be measured in the second frame by combining the pixel coordinates and the world coordinates of the two cameras;
calculating the estimated pixel coordinate of the object to be measured in the third frame and the corresponding world coordinate of the object to be measured in the third frame by using the matched pixel coordinate of the object to be measured in the second frame and the pixel similarity of the second frame and the third frame;
and repeating the steps until the three-dimensional vibration track of the object to be measured in the measuring time period is obtained.
Further, the method for calculating the estimated pixel coordinates of the object to be measured in the second frame comprises the following steps:
a1: selecting the width and height of the two camera images as W and H respectively; the maximum width and height of the object to be measured are w and h respectively,the object to be measured in the first frame I0Has a pixel coordinate of (i)0,j0) The pixel distribution is A0：
A2: searching the object to be detected in the second frame I, selecting the width and the height of a search box as w and h respectively, setting the pixel coordinate of the search box as (I, j), and setting the pixel distribution as A:
a3: calculating an offset vector:
wherein ω (i, j) is the pixel similarity, and
n is the number of times the search box is shifted when searching in the second frame, (x)n,yn) For the pixel coordinate of the search box after the nth shift in the second frame, the value range of (i, j) is distance (x)n,yn) More recent
Pixel coordinates of the individual pixel points; (i)n,jn) Is a distance (x)n,yn) More recent
The value range of the pixel coordinates of each pixel point;
a4: order to
The pixel coordinate of the object to be measured in the second frame is estimated to be (x'n，y’n)＝m(xn，yn)＝(xn，yn)+M(xn，yn)。
Further, the method for judging whether the estimated pixel coordinate is the matching pixel coordinate of the object to be measured in the second frame includes:
if M (x)nYn) | | less than or equal to epsilon or N > NmaxEstimating pixel coordinates as matched pixel coordinates of the object to be measured in the second frame;
if M (x)nYn) | > epsilon and N is less than or equal to NmaxThen return to step a 3;
wherein epsilon is a preset threshold value of the tracking step length of the object to be detected in the second frame, NmaxThe maximum number of offsets when searching in the second frame for the preset search box.
Further, before measurement, the internal parameter matrixes of the two cameras and the external parameter matrixes of the two cameras are respectively obtained.
Further, the external parameter matrix and the external parameter matrix obtaining method are a Zhang Zhengyou calibration method.
Further, the conversion formula of the pixel coordinate and the world coordinate is as follows:
wherein the content of the first and second substances,
is an internal parameter matrix, and the internal parameter matrix,
is an external parameter matrix, and (u, v) is the coordinate of the object to be measured in the pixel coordinate system; (u)0,v0) Is the center of the image plane; (x, y) is the coordinate of the object to be measured in the image plane coordinate; (X)W,YW,ZW) The coordinates of the object to be measured in the world coordinate system are obtained.
Compared with the prior art, the invention has the advantages that:
(1) the method provided by the invention has high measurement precision and simple method, the pixel similarity of the whole image and the object to be measured is calculated in each frame based on the pixel characteristics of the object to be measured in the image, the offset vector is calculated according to the pixel similarity, and the offset vector meeting the conditions is obtained through continuous iteration, so that the matched pixel coordinate of the object to be measured in each frame is determined. And determining the three-dimensional coordinates according to the matched pixel coordinates of the object to be measured in the two cameras.
(2) The measuring method of the invention belongs to a non-contact measuring method, and the camera can be arranged in a relatively closed space, so that the measuring method is suitable for vibrating objects working in severe environment; the durability is high, the camera is not contacted with a vibrating object, the working environment is relatively good, and the camera can be used for a long time.
(3) Compared with the traditional strain gauge type measurement, the measurement method provided by the invention can acquire the three-dimensional vibration information of the object to be measured, track the object to be measured, completely record the vibration track and carry out a large amount of vibration analysis.
Drawings
Fig. 1 is a flowchart of a measurement method according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
It should be noted that the "selected" and "preset" data are directly determined; the data of the "setting" is calculated to be determined.
Referring to fig. 1, an embodiment of the present invention provides a method for measuring a three-dimensional vibration trajectory of an object to be measured based on binocular vision, including two cameras with different orientations, lens surfaces of the two cameras being located on a same plane, and central axes being parallel; which comprises the following steps:
shooting an object to be detected by using two cameras, and obtaining video stream data of the two cameras;
selecting one frame of data at the same time as a first frame from the video stream data of the two cameras, and obtaining the pixel coordinates of the object to be detected in the first frame; the pixel coordinates in the first frame are selected and therefore determined directly as a basis for calculating the pixel coordinates of the object to be measured in the second frame.
Calculating an offset vector of the object to be measured between the second frame and the first frame through the pixel similarity, obtaining an estimated pixel coordinate of the object to be measured in the second frame, determining the estimated pixel coordinate as a matched pixel coordinate of the object to be measured in the second frame if the estimated pixel coordinate meets the precision requirement, and calculating a world coordinate of the object to be measured in the second frame by combining the pixel coordinates and the world coordinates of the two cameras;
calculating the estimated pixel coordinate of the object to be measured in the third frame and the corresponding world coordinate of the object to be measured in the third frame by using the matched pixel coordinate of the object to be measured in the second frame and the pixel similarity of the second frame and the third frame; that is, whether the estimated pixel coordinate of the object to be measured in the third frame meets the precision requirement is judged, and if so, the estimated pixel coordinate is determined to be the matched pixel coordinate of the object to be measured in the third frame.
Repeating the steps until a three-dimensional vibration track of the object to be measured in the measurement time period is obtained, namely, calculating the pixel coordinate of the object to be measured in the second frame according to the pixel coordinate of the object to be measured in the first frame, calculating the pixel coordinate of the object to be measured in the third frame according to the calculated pixel coordinate of the object to be measured in the second frame, calculating the pixel coordinate of the object to be measured in the fourth frame according to the calculated pixel coordinate of the object to be measured in the third frame, repeating the steps in the same way, calculating to finally obtain the pixel coordinate of the object to be measured in each frame in the measurement time period, and obtaining the world coordinate of the object to be measured in each frame in the measurement time period according to the conversion relation between the pixel coordinate of the camera and the world coordinate.
The principle of the invention is as follows: the method comprises the steps of calculating the coordinate of a matched pixel in a current frame through the coordinate of the matched pixel of an object to be measured in a previous frame, shooting the object to be measured by using two cameras, and calculating the world coordinate of the object to be measured at the moment by combining the pixel coordinate of the two cameras and the world coordinate of the object to be measured at the same time.
In the measurement, two cameras are simultaneously performed, and the measurement steps and calculation methods of the two cameras are the same, taking a first frame and a second frame of one camera as an example, wherein the pixel coordinates of the object to be measured in the first frame are selected, so that the parameters of the first frame are known, and the measurement is required from the second frame, however, for two consecutive frames to be measured, the pixel coordinates of the object to be measured in the next frame can be determined from the pixel coordinates of the previous frame, and the pixel coordinates of the object to be measured in the previous frame can be determined from the pixel coordinates of the previous frame, in short, the pixel coordinates of the second frame can be calculated from the pixel coordinates of the first frame, the pixel coordinates of the third frame can be calculated from the pixel coordinates of the second frame, and the pixel coordinates of the fourth frame can be calculated from the pixel coordinates of the third frame, repeating the steps to obtain the three-dimensional vibration trajectory of the object to be measured in the measurement time period, as shown in fig. 1, the specific steps of calculating the second frame from the first frame are as follows:
s1: acquiring an internal parameter matrix of a camera and an external parameter matrix of the camera; the method for acquiring the internal parameter matrix and the external parameter matrix is a common method, and preferably adopts a Zhangyingyou calibration method.
S2: selecting width and height of a camera image as W and H respectively; the maximum width and height of the object to be measured are w and h respectively, and the object to be measured is in a first frame I0Has a pixel coordinate of (i)0,j0) The pixel distribution is A0：
Because the first frame is selected, the maximum width and height of the first frame, and the pixel coordinates and the pixel distribution of the object to be measured in the first frame are known; for convenience of description, the images of the two cameras may also be selected to be the same size, W wide and H high.
S3: searching the object to be detected in the second frame I, selecting the width and the height of a search box as w and h respectively, setting the pixel coordinate of the search box as (I, j), and setting the pixel distribution as A:
s4: calculating an offset vector:
wherein ω (i, j) is the pixel similarity, and
n is the number of times the search box is shifted when searching in the second frame, (x)n,yn) For the pixel coordinate of the search box after the nth shift in the second frame, the value range of (i, j) is distance (x)n,yn) More recent
Pixel coordinates of the individual pixel points; (in, jn) is a distance (x)nYn) most recent
The value range of the pixel coordinates of each pixel point;
order to
The pixel coordinate of the object to be measured in the second frame is estimated to be (x'n,y’n)＝m(xn,yn)＝(xn,yn)+M(xn,yn)；
S5: and (3) judging: if M (x)n,yn) Less than or equal to epsilon or N is more than NmaxEstimating pixel coordinates as matched pixel coordinates of the object to be measured in the second frame;
if M (x)n,yn) N is less than or equal to N and | | > epsilonmaxThen return to step S4;
wherein epsilon is a preset threshold value of the tracking step length of the object to be detected in the second frame, NmaxThe maximum number of offsets when searching in the second frame for the preset search box.
And repeating the steps to calculate the coordinate of the matched pixel of the object to be measured in each frame of the two cameras.
Regarding the threshold of the tracking step, it is related to the pixel resolution of the image and the size of the object to be detected in the image, for example, the image resolution is 10000 × 10000, the size of the object to be detected in the image is 1000 × 1000, the threshold is set to 5, meaning that the target position moves by a distance of more than 5 pixels, the target movement is determined, and below 5 movements, the movement distance is considered as small enough to be ignored, and no movement is considered.
Setting NmaxThe meaning of (1) is that the program cannot loop all the time to find because the target cannot be found, and thus the program runs away.
According to the matched pixel coordinates of the object to be measured in the two cameras, combining the pixel coordinates and a world coordinate conversion formula, carrying out simultaneous solution on the equation set to obtain the world coordinates of the object to be measured in each frame; the conversion formula of the pixel coordinate and the world coordinate is as follows:
wherein the content of the first and second substances,
is an internal parameter matrix, and the internal parameter matrix,
is an extrinsic parameter matrix(u, v) is the coordinate of the object to be measured in the pixel coordinate system, namely the pixel coordinate; (u)0,v0) Is the center of the image plane; (x, y) is the coordinate of the object to be measured in the image plane coordinate; (X)C,YC,ZC) The coordinate of the object to be measured in the camera coordinate system; (X)W,YW,ZW) The coordinates of the object to be measured in the world coordinate system are obtained.
For example, the coordinate of the matching pixel of the object to be measured in the first camera is (u)1,v1) The coordinate of the matching pixel of the object to be measured in the second camera is (u)2,v2)。
For the first video camera to be used,
in the case of a second camera, the camera,
simultaneous solution of equation sets (X)W,YW,ZW)。
Respectively calculating pixel coordinates of an object to be measured in the two cameras at the same time, and when judging whether the estimated pixel coordinates are matched pixel coordinates or not, only when the estimated pixel coordinates of the object to be measured in the two cameras are both judged to be matched pixel coordinates, calculating the world coordinates at the moment, and entering the calculation in the next frame; otherwise, if the estimated pixel coordinate of the object to be measured in one of the cameras is judged to be the matched pixel coordinate, that is, the condition is satisfied, but the estimated pixel coordinate of the object to be measured in the other camera is judged to be the non-matched pixel coordinate, that is, the condition of the matched pixel coordinate is not satisfied, then the object satisfying the condition is calculated continuously, in the process, the position of the search frame of the object to be measured may not be changed or may be changed slightly until the estimated pixel coordinate of the object to be measured in the other camera is judged to be the matched pixel coordinate, and then the current world coordinate is calculated and the calculation in the next frame is performed.
The present invention is not limited to the above-described embodiments, and it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements are also considered to be within the scope of the present invention. Those not described in detail in this specification are within the skill of the art.
Claims (5)
1. The binocular vision-based method for measuring the three-dimensional vibration track of the object to be measured comprises two cameras with different directions, wherein lens surfaces of the two cameras are positioned on the same plane, and central axes of the two cameras are parallel; the method is characterized by comprising the following steps:
shooting an object to be detected by using two cameras, and obtaining video stream data of the two cameras;
selecting one frame of data at the same time as a first frame from the video stream data of the two cameras, and obtaining the pixel coordinates of the object to be detected in the first frame;
calculating an offset vector of the object to be measured between the second frame and the first frame through the pixel similarity, obtaining an estimated pixel coordinate of the object to be measured in the second frame, determining the estimated pixel coordinate as a matched pixel coordinate of the object to be measured in the second frame if the estimated pixel coordinate meets the precision requirement, and calculating a world coordinate of the object to be measured in the second frame by combining the pixel coordinates and the world coordinates of the two cameras;
calculating the estimated pixel coordinate of the object to be measured in the third frame and the corresponding world coordinate of the object to be measured in the third frame by using the matched pixel coordinate of the object to be measured in the second frame and the pixel similarity of the second frame and the third frame;
repeating the steps until a three-dimensional vibration track of the object to be measured in the measuring time period is obtained;
the method for calculating the estimated pixel coordinate of the object to be measured in the second frame comprises the following steps:
a1: selecting the width and height of the two camera images as W and H respectively; test objectThe maximum width and height of the body are w and h respectively, and the object to be measured is in the first frame I0Has a pixel coordinate of (i)0,j0) The pixel distribution is A0：
A2: searching the object to be detected in the second frame I, selecting the width and the height of a search box as w and h respectively, setting the pixel coordinate of the search box as (I, j), and setting the pixel distribution as A:
a3: calculating an offset vector:
wherein ω (i, j) is the pixel similarity, and
n is the number of times the search box is shifted when searching in the second frame, (x)n,yn) For the pixel coordinate of the search box after the nth shift in the second frame, the value range of (i, j) is distance (x)n,yn) More recent
Pixel coordinates of the individual pixel points; (i)n,jn) Is a distance (x)n,yn) More recent
The value range of the pixel coordinates of each pixel point;
a4: order to
The pixel coordinate of the object to be measured in the second frame is estimated to be (x'n,y’n)＝m(xn,yn)＝(xn,yn)+M(xn,yn)。
2. The measurement method according to claim 1, wherein the method of determining whether the estimated pixel coordinate is a matching pixel coordinate of the object to be measured in the second frame comprises:
if M (x)n,yn) Less than or equal to epsilon or N is more than NmaxEstimating pixel coordinates as matched pixel coordinates of the object to be measured in the second frame;
if M (x)n,yn) N is less than or equal to N and | | > epsilonmaxThen return to step a 3;
wherein epsilon is a preset threshold value of the tracking step length of the object to be detected in the second frame, NmaxThe maximum number of offsets when searching in the second frame for the preset search box.
3. The measurement method according to claim 1, characterized in that: before measurement, internal parameter matrixes of the two cameras and external parameter matrixes of the two cameras are obtained respectively.
4. A measuring method according to claim 3, characterized in that: the external parameter matrix and the external parameter matrix obtaining method are Zhangyingyou calibration method.
5. The measurement method of claim 1, wherein the pixel coordinate and world coordinate conversion formula is:
wherein the content of the first and second substances,
is an internal parameter matrix, and the internal parameter matrix,
is an external parameter matrix, and (u, v) is the coordinate of the object to be measured in the pixel coordinate system; (u)0,v0) Is the center of the image plane; (x, y) is the coordinate of the object to be measured in the image plane coordinate; (X)W,YW,ZW) The coordinates of the object to be measured in the world coordinate system are obtained.
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