相机外参计算错误

3

我正在尝试从两张图像中找到相机外参。我已经有了来自CameraCalibration的内参,场景具有已知的尺寸(使用3DSMAX创建)。

棋盘大小为1000*1000,每个方格大小为125*125。相机位于(0,0,3000),直视位于原点中心的棋盘。在第二张图像中,相机沿Y轴旋转30度并向左平移(-1500, 0, -402),以再次对准棋盘中心: camera setup

GoodFeaturesToTrack正确识别出81个角点: chessboards

我创建了棋盘角点的三维点,使用cvFindExtrinsicCameraParams2计算内参和使用cvRodrigues2获取旋转矩阵。以下是代码:

Imports Emgu.CV
Imports Emgu.CV.Structure
Imports Emgu.CV.CvInvoke
Imports Emgu.CV.CvEnum
Imports Emgu.CV.UI
Imports System.Drawing
Imports System.IO
Imports System.Diagnostics
Imports System.Math
Module main_

    Sub Main()

        Const MAXFEATURES As Integer = 100
        Dim featuresA(0)() As PointF
        Dim featuresB(0)() As PointF
        Dim features As Integer = 0
        Dim imgA As Emgu.CV.Image(Of Emgu.CV.Structure.Bgr, Byte)
        Dim imgB As Emgu.CV.Image(Of Emgu.CV.Structure.Bgr, Byte)
        Dim grayA As Emgu.CV.Image(Of Emgu.CV.Structure.Gray, Byte)
        Dim grayB As Emgu.CV.Image(Of Emgu.CV.Structure.Gray, Byte)
        Dim pyrBufferA As Emgu.CV.Image(Of Emgu.CV.Structure.Gray, Byte)
        Dim pyrBufferB As Emgu.CV.Image(Of Emgu.CV.Structure.Gray, Byte)
        Dim pointsA As Matrix(Of Single)
        Dim pointsB As Matrix(Of Single)
        Dim flags As Emgu.CV.CvEnum.LKFLOW_TYPE = Emgu.CV.CvEnum.LKFLOW_TYPE.DEFAULT
        Dim imagesize As Size
        Dim termcrit As New Emgu.CV.Structure.MCvTermCriteria(20, 0.03D)
        Dim status As Byte() = Nothing
        Dim errors As Single() = Nothing
        Dim red As Bgr = New Bgr(Color.Red)

        ' Load chessboards
        imgA = New Image(Of [Structure].Bgr, Byte)("chessboard centre.jpg")
        imgB = New Image(Of [Structure].Bgr, Byte)("chessboard left.jpg")
        grayA = imgA.Convert(Of Gray, Byte)()
        grayB = imgB.Convert(Of Gray, Byte)()

        ' setup for feature detection
        imagesize = cvGetSize(grayA)
        pyrBufferA = New Emgu.CV.Image(Of Emgu.CV.Structure.Gray, Byte)(imagesize.Width + 8, imagesize.Height / 3)
        pyrBufferB = New Emgu.CV.Image(Of Emgu.CV.Structure.Gray, Byte)(imagesize.Width + 8, imagesize.Height / 3)
        features = MAXFEATURES

        ' Find features
        featuresA = grayA.GoodFeaturesToTrack(features, 0.01, 25, 3)
        grayA.FindCornerSubPix(featuresA, New System.Drawing.Size(10, 10), New System.Drawing.Size(-1, -1), termcrit)
        features = featuresA(0).Length

        ' Compute optical flow. Not necessary here but good to remember
        Emgu.CV.OpticalFlow.PyrLK(grayA, grayB, pyrBufferA, pyrBufferB, featuresA(0), New Size(25, 25), 3, termcrit, flags, featuresB(0), status, errors)
        Debug.Assert(featuresA(0).GetUpperBound(0) = featuresB(0).GetUpperBound(0))

        ' Copy features to an easier-to-use matrix and get min/max to create 3d points
        Dim minx As Double = Double.MaxValue
        Dim miny As Double = Double.MaxValue
        Dim maxx As Double = Double.MinValue
        Dim maxy As Double = Double.MinValue
        pointsA = New Matrix(Of Single)(features, 2)
        pointsB = New Matrix(Of Single)(features, 2)
        For i As Integer = 0 To features - 1
            pointsA(i, 0) = featuresA(0)(i).X
            pointsA(i, 1) = featuresA(0)(i).Y
            pointsB(i, 0) = featuresB(0)(i).X
            pointsB(i, 1) = featuresB(0)(i).Y
            If pointsA(i, 0) < minx Then
                minx = pointsA(i, 0)
            End If
            If pointsA(i, 1) < miny Then
                miny = pointsA(i, 1)
            End If
            If pointsA(i, 0) > maxx Then
                maxx = pointsA(i, 0)
            End If
            If pointsA(i, 1) > maxy Then
                maxy = pointsA(i, 1)
            End If
        Next

        ' Create 3D object points that correspond to chessboard corners
        ' (The chessboard is 1000*1000, squares are 125*125)
        Dim corners As Integer = Sqrt(features)
        Dim obj As New Matrix(Of Double)(features, 3)
        Dim squaresize2dx As Double = (maxx - minx) / 8 ' pixel width of a chessboard square
        Dim squaresize2dy As Double = (maxy - miny) / 8 ' pixel height of a chessboard square
        For i As Integer = 0 To features - 1
            obj(i, 0) = Math.Round((pointsA(i, 0) - minx) / squaresize2dx) * 125 ' X=0, 125, 250, 375 ... 1000
            obj(i, 1) = Math.Round((pointsA(i, 1) - miny) / squaresize2dy) * 125 ' idem in Y
            obj(i, 2) = 0
            ' Debug.WriteLine(pointsA(i, 0) & " " & pointsA(i, 1) & " " & obj(i, 0) & " " & obj(i, 1) & " " & obj(i, 2)) ' Just to verify
        Next

        ' These were calculated with CalibrateCamera using the same images
        Dim intrinsics As New Matrix(Of Double)({{889.1647, 0.0, 318.3721},
                                                 {0.0, 888.5134, 238.4254},
                                                 {0.0, 0.0, 1.0}})
        ' Find extrinsics
        Dim distortion As New Matrix(Of Double)({-0.036302, 2.008797, -29.674306, -29.674306})
        Dim translation As New Matrix(Of Double)(3, 1)
        Dim rotation As New Matrix(Of Double)(3, 1)
        cvFindExtrinsicCameraParams2(obj, pointsA, intrinsics, distortion, rotation, translation, False)

        ' Convert rotation vector to rotation matrix
        Dim rotmat As New Matrix(Of Double)(3, 3)
        Dim jacobian As New Matrix(Of Double)(9, 3)
        cvRodrigues2(rotation, rotmat, jacobian)

        ' From http://en.wikipedia.org/wiki/Rotation_representation paragraph "Conversion formulae between representations"
        Dim yr As Double = Asin(-rotmat(2, 0))
        Dim xr As Double = Asin(rotmat(2, 1) / Cos(yr))
        Dim zr As Double = Asin(rotmat(1, 0) / Cos(yr))

    End Sub
End Module

结果似乎不正确,我期望的是翻译/旋转,但我得到了这个:

translation
208.394425348956 
-169.447506344527 
-654.273807995629 
rotation
-0.0224937226554797 
-2.13660350939653 
-1.10542281290682 
rotmat
-0.741100224945266 0.322885083546921 -0.588655824237707 
-0.293966101915684 0.632206237134128 0.716867633983572 
0.603617749499279 0.704315622822328 -0.373610915174894 
xr=1.08307908108382 yr=-0.648031006135158 zr=-0.377625254910525
xr=62.0558602250101° yr=-37.1294416451609° zr=-21.636333343925°

有人知道我做错了什么吗?谢谢!


+1 介绍我使用cvRodrigues2()函数,谢谢! - coder9
2个回答

1

找到了。畸变系数为

k1, k2, p1, p2, k3

而不是

k1, k2, k3, k4, k5

就像我编写的那样。当我将它们设置为

-0.05716, 2.519006, -0.001674, -0.001021, -33.372798

答案(大致)是正确的


1
请看针孔相机方程式: ' ~ A * R|T * [x, y, z, 1]',其中外参矩阵R|T的尺寸为3x4。请注意,将其与无穷远处的“理想”或消失点(例如[1,0,0,0])相乘会给您一个对应的R|T列。这意味着要找到R|T的所有列,您必须至少拥有三个可以从棋盘格模式中轻松找到的消失点。
现在你只有一个,所以如果你的结果看起来合理,那么你就很幸运。再试一次,并选择最少10-20个不同的倾斜、距离和校准支架的倾斜角度。

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