Question

我目前正在使用一个朝下的相机拍摄，棋盘图案位于地面上的固定位置。我正在使用带有OpenCV的python来跟踪摄像机的位移，并使用输出根据x，y，z方向绘制位移。最后，我想将摄像机安装在悬停式多旋翼无人机的底部，以便校准GPS精度。

我使用的基本方法是：

定义对象点
打开视频
基于已保存的相机矩阵的Undistort帧（已执行相机校准）
查找棋盘角落
如果发现角落，请修改角落
查找旋转和平移向量（cv2.pnpransac）
项目3D指向图像平面（cv2.projectpoints）

将旋转矢量转换为旋转矩阵

np_rodrigues = np.asarray(rvecs_new[:,:],np.float64)
rmatrix = cv2.Rodrigues(np_rodrigues)[0]

根据this answer:

计算相机姿势

cam_pos = -np.matrix(rmatrix).T * np.matrix(tvecs_new)

存储值

camx.append(cam_pos.item(0))
camy.append(cam_pos.item(1))
camz.append(cam_pos.item(2))

然而当我使用应该是恒定高度的直线的视频运行此代码时，绘制的x，y图表给出了弯曲的x，y图，并且z不是常数，如图所示通过x，z图：http://imgur.com/QIY3wgQ,pDM5T0x,HEDJtAt#1

有什么理由不应该在图表上给出一条直线？步骤9中的相机姿势计算可能出错？

完整的代码如下：

    # Criteria, defining object points
    import cv2
    import numpy as np
    import time
    import matplotlib.pyplot as plt

    #IMPORTANT: Enter chess board dimensions 
    chw = 9
    chh = 6

    #Defining draw functions for lines
    def draw(img, corners, imgpts):
        corner = tuple(corners[0].ravel())
        cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5)
        cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5)
        cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)
        return img

    # Load previously saved data
    with np.load('camera_calib.npz') as X:
        mtx, dist, _, _, _ = [X[i] for i in ('mtx','dist','rvecs','tvecs','imgpts')]

    # Criteria, defining object points
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
    objp = np.zeros((chh*chw,3), np.float32)
    objp[:,:2] = np.mgrid[0:chw,0:chh].T.reshape(-1,2)

    # Setting axis
    axis = np.float32([[9,0,0], [0,6,0], [0,0,-10]]).reshape(-1,3)

    cap = cv2.VideoCapture('Calibration\\video_chess2.MP4')
    count = 0
    fcount = 0
    while(cap.isOpened()):
        ret1, img = cap.read()
        if ret1 == False or count==lim:
            print('Video analysis complete.')
            break
        if count > 0:
            h,  w = img.shape[:2]
            newcameramtx, roi=cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),1,(w,h))
            # Undistorting
            img2 = cv2.undistort(img, mtx, dist, None, newcameramtx)

            gray = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)
            ret2, corners = cv2.findChessboardCorners(gray, (chw,chh),None)
            if ret2 == True:
                fcount = fcount+1
                # Refining corners
                cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)

                # Find the rotation and translation vectors
                rvecs_new, tvecs_new, inliers = cv2.solvePnPRansac(objp, corners, mtx, dist)

                # Project 3D points to image plane
                imgpts, jac = cv2.projectPoints(axis, rvecs_new, tvecs_new, mtx, dist)
                draw(img2,corners,imgpts)
                cv2.imshow('img',img2)
                cv2.waitKey(1)


                # Converting rotation vector to rotation matrix
                np_rodrigues = np.asarray(rvecs_new[:,:],np.float64)
                rmatrix = cv2.Rodrigues(np_rodrigues)[0]

                # Pose (According to https://stackoverflow.com/questions/16265714/camera-pose-estimation-opencv-pnp)
                cam_pos = -np.matrix(rmatrix).T * np.matrix(tvecs_new)

                camx.append(cam_pos.item(0))
                camy.append(cam_pos.item(1))
                camz.append(cam_pos.item(2))

            else:
                print 'Board not found'

        count += 1
        print count
    cv2.destroyAllWindows()
    plt.plot(camx,camy)
    plt.show()

OpenCV中的摄像机位移估计 - 不正确的姿势输出

0 个答案: