相机标定实战之双目标定_双目相机标定

相机标定原理

---

---

前言

相机标定可以说是计算机视觉/机器视觉的基础，也是面试过程中经常出现的问题。相机标定涉及的知识面很广，成像几何、镜头畸变、单应矩阵、非线性优化等。在双目测距系统中，相机标定能消除畸变，进行立体校正，从而提高视差计算的准确性，这样才能得到精确的深度图。

首先需要准备一张棋盘，如下图所示。对于标定不同测距范围相机所用的棋盘方格宽度会有所不同。对于短焦双目相机（测距范围在20m以内），棋盘中方格的宽度达到20mm即可；对于长焦双目相机（测距范围在40m左右），棋盘中方格的宽度需要尽量大，否则会影响标定的精度，一般至少达到60mm。

尽量拍摄多组照片，这样可以提高标定效果，标定效果的好坏直接影响到测距的精度。对于短焦相机通常拍摄40组照片即可；长焦相机通常会需要更多组照片，标定长焦相机时拍摄了60组。

一、采集图像

如果使用的是左右图像拼接1个USB接口输出的双目摄像头，在采集图像时需要注意其图像拼接的顺序，例如我使用的双目摄像头拼接顺序从左至右为右目——左目(不知道是不是都是这么拼接的，还是厂家搞错了），这个问题处理不好可能会导致后面的处理结果都不对，所以这里特别说明一下。

import os
import argparse
import cv2

class StereoCamera(object):
    """采集双目标定图片，按键盘【c】或【s】保存图片"""
 
    def __init__(self, chess_width, chess_height, detect=False):
        """
        :param chess_width: chessboard width size，即棋盘格宽方向黑白格子相交点个数，
        :param chess_height: chessboard height size，即棋盘格长方向黑白格子相交点个数
        :param detect: 是否实时检测棋盘格，方便采集数据
        """
        self.chess_width = chess_width
        self.chess_height = chess_height
        self.detect = detect
        self.criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
 
    def detect_chessboard(self, image):
        """检测棋盘格并显示"""
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        ret, corners = cv2.findChessboardCorners(gray, (self.chess_width, self.chess_height), None)
        if ret:
            # 角点精检测
            corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), self.criteria)
            # Draw and display the corners
            image = cv2.drawChessboardCorners(image, (self.chess_width, self.chess_height), corners2, ret)
        return image
 
    def capture2(self, left_video, right_video, save_dir):
        """
        用于采集双USB连接线的双目摄像头
        :param left_video:int or str,左路视频路径或者摄像头ID
        :param right_video:int or str,右视频路径或者摄像头ID
        :param save_dir: str,保存左右图片的路径
        :return:
        """
        self.create_file(save_dir)
        capL = cv2.VideoCapture(left_video)
        capR = cv2.VideoCapture(right_video)
        widthL, heightL, numFramesL, fpsL = self.get_video_info(capL)
        widthR, heightR, numFramesR, fpsR = self.get_video_info(capR)
        print("capL:\n", widthL, heightL, numFramesL, fpsL)
        print("capR:\n", widthR, heightR, numFramesR, fpsR)
        save_videoL = self.create_file(save_dir, "video", "left_video.avi")
        save_videoR = self.create_file(save_dir, "video", "right_video.avi")
        writerL = self.get_video_writer(save_videoL, widthL, heightL, fpsL)
        writerR = self.get_video_writer(save_videoR, widthR, heightR, fpsR)
        i = 0
        while True:
            isuccessL, frameL = capL.read()
            isuccessR, frameR = capR.read()
            if not (isuccessL and isuccessR):
                print("No more frames")
                break
            if self.detect:
                l = self.detect_chessboard(frameL.copy())
                r = self.detect_chessboard(frameR.copy())
            else:
                l = frameL.copy()
                r = frameR.copy()
            cv2.imshow('left', l)
            cv2.imshow('right', r)
            key = cv2.waitKey(10)
            if key == ord('q'):
                break
            elif key == ord('c') or key == ord('s'):
                print("save image:{:0=3d}".format(i))
                cv2.imwrite(os.path.join(save_dir+"/left", "left_{:0=3d}.png".format(i)), frameL)
                cv2.imwrite(os.path.join(save_dir+"/right", "right_{:0=3d}.png".format(i)), frameR)
                i += 1
            writerL.write(frameL)
            writerR.write(frameR)
        capL.release()
        capR.release()
        cv2.destroyAllWindows()
 
    def capture1(self, video, save_dir):
        """
        用于采集单USB连接线的双目摄像头(左右摄像头被拼接在同一个视频中显示)
        :param video:int or str,视频路径或者摄像头ID
        :param save_dir: str,保存左右图片的路径
        """
        self.create_file(save_dir)
        cap = cv2.VideoCapture(video)


        width, height, numFrames, fps = self.get_video_info(cap)
        print("capL:\n", width, height, numFrames, fps)
        save_videoL = self.create_file(save_dir, "video", "left_video.avi")
        save_videoR = self.create_file(save_dir, "video", "right_video.avi")
        writerL = self.get_video_writer(save_videoL, int(width / 2), height, fps)
        writerR = self.get_video_writer(save_videoR, int(width / 2), height, fps)
        i = 0
        while True:
            isuccess, frame = cap.read()
            if not isuccess:
                print("No more frames")
                break
            # 分离左右摄像头
            # 注意：需要根据摄像头画面分割左右图像
            frameL = frame[:, int(width / 2):, :]
            frameR = frame[:, :int(width / 2), :]


            if self.detect:
                l = self.detect_chessboard(frameL.copy())
                r = self.detect_chessboard(frameR.copy())
            else:
                l = frameL.copy()
                r = frameR.copy()
            cv2.imshow('left', l)
            cv2.imshow('right', r)
            key = cv2.waitKey(10)
            if key == ord('q'):
                break
            elif key == ord('c') or key == ord('s'):
                print("save image:{:0=3d}".format(i))
                cv2.imwrite(os.path.join(save_dir+"/left", "left_{:0=3d}.png".format(i)), frameL)
                cv2.imwrite(os.path.join(save_dir+"/right", "right_{:0=3d}.png".format(i)), frameR)
                i += 1
            writerL.write(frameL)
            writerR.write(frameR)
        cap.release()
        cv2.destroyAllWindows()
 
    @staticmethod
    def get_video_info(video_cap):
        width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
        height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
        numFrames = int(video_cap.get(cv2.CAP_PROP_FRAME_COUNT))
        fps = int(video_cap.get(cv2.CAP_PROP_FPS))
        return width, height, numFrames, fps
 
    @staticmethod
    def get_video_writer(save_path, width, height, fps):
        if not os.path.exists(os.path.dirname(save_path)):
            os.makedirs(os.path.dirname(save_path))
        fourcc = cv2.VideoWriter_fourcc(*'XVID')
        frameSize = (int(width), int(height))
        video_writer = cv2.VideoWriter(save_path, fourcc, fps, frameSize)
        print("video:width:{},height:{},fps:{}".format(width, height, fps))
        return video_writer
 
    @staticmethod
    def create_file(parent_dir, dir1=None, filename=None):
        out_path = parent_dir
        if dir1:
            out_path = os.path.join(parent_dir, dir1)
        if not os.path.exists(out_path):
            os.makedirs(out_path)
        if filename:
            out_path = os.path.join(out_path, filename)
        return out_path
 
 
def get_parser():
    width = 12
    height = 8
    left_video = 0
    right_video = -1
    save_dir = "data/"
    parser = argparse.ArgumentParser(description='Camera calibration')
    parser.add_argument('--detect', type=bool, default=True, help='detect corner')
    parser.add_argument('--width', type=int, default=width, help='chessboard width size')
    parser.add_argument('--height', type=int, default=height, help='chessboard height size')
    parser.add_argument('--left_video', type=int, default=left_video, help='left video file or camera ID')
    parser.add_argument('--right_video', type=int, default=right_video, help='right video file or camera ID')
    parser.add_argument('--save_dir', type=str, default=save_dir, help='YML file to save calibrate matrices')
    return parser
 
 
if __name__ == '__main__':
    args = get_parser().parse_args()
    stereo = StereoCamera(args.width, args.height, detect=args.detect)
    if args.left_video > -1 and args.right_video > -1:
        # 双USB连接线的双目摄像头
        stereo.capture2(left_video=args.left_video, right_video=args.right_video, save_dir=args.save_dir)
    elif args.left_video > -1:
        # 单USB连接线的双目摄像头(左右摄像头被拼接在同一个视频中显示)
        stereo.capture1(video=args.left_video, save_dir=args.save_dir)
    else:
        raise Exception("Error: Check your camera{}".format(args.left_video, args.right_video))
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183

二、基于Matlab单双目标定流程

采集棋盘图

尽量让棋盘占据照片中最多的画面（不小于1\3）
尽量让棋盘格出现在图像中的各个位置（尤其图像的四个角）
拍摄的棋盘图是具有多个角度的（前倾，后倾，左倾，右倾，斜倾等）
拍摄的棋盘图要清晰可辩，最好是在最清晰的范围内拍摄
拍摄照片数量要多一点，推荐20张以上

https://blog.csdn.net/leonardohaig/article/details/81254179

三、基于OpenCV-Python双目标定流程

双目标定的目的是获取左右目相机的内参矩阵、畸变向量、旋转矩阵和平移矩阵。除了Matlab的标定工具箱之外，OpenCV同样也实现了张友正标定法，而我们只需要调用相关的函数即可对相机进行标定。
双目相机标定步骤：

检测棋盘格角点

retL, cornersL = cv2.findChessboardCorners(ChessImaL,(self.width, self.height), cv2.CALIB_CB_ADAPTIVE_THRESH | cv2.CALIB_CB_FILTER_QUADS)  # 提取左图每一张图片的角点
retR, cornersR = cv2.findChessboardCorners(ChessImaR,(self.width, self.height), cv2.CALIB_CB_ADAPTIVE_THRESH | cv2.CALIB_CB_FILTER_QUADS)  # 提取右图每一张图片的角点
1
2

对角点进行亚像素精细化

criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
cv2.cornerSubPix(ChessImaL, cornersL, (11, 11), (-1, -1), criteria)  # 亚像素精确化，对粗提取的角点进行精确化
cv2.cornerSubPix(ChessImaR, cornersR, (11, 11), (-1, -1), criteria)  # 亚像素精确化，对粗提取的角点进行精确化
1
2
3

单目标定

#   左侧相机单独标定
retL, K1, D1, rvecsL, tvecsL = cv2.calibrateCamera(objpoints,imgpointsL,ChessImaL.shape[::-1], None, None)
#   右侧相机单独标定
retR, K2, D2, rvecsR, tvecsR = cv2.calibrateCamera(objpoints,imgpointsR,ChessImaR.shape[::-1], None, None)
1
2
3
4

双目标定

criteria_stereo = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 1e-5)

flags = 0
flags |= cv2.CALIB_FIX_INTRINSIC

# 内参、畸变系数、平移向量、旋转矩阵
retS, K1, D1, K2, D2,  R, T, E, F = cv2.stereoCalibrate(objpoints,imgpointsL,imgpointsR,K1,D1,K2,D2,ChessImaR.shape[::-1], criteria_stereo,flags)
1
2
3
4
5
6
7

我们要注意函数中的flags

CV_CALIB_FIX_INTRINSIC:固定K和D矩阵。这是默认标志。如果你校准好你的相机，那就只求解
声明：本文内容由网友自发贡献，不代表【wpsshop博客】立场，版权归原作者所有，本站不承担相应法律责任。如您发现有侵权的内容，请联系我们。转载请注明出处：https://www.wpsshop.cn/w/繁依Fanyi0/article/detail/599266