如何在 OpenCV 4.1.1 Aruco 标记检测中实现更高的稳定性？

Question

我正在视频中试验 Aruco 检测。

我正在尝试检测视频帧中的 Aruco 标记，但检测器无法检测到所有标记。这是一张稳定的图像，因此视频中没有任何移动。

我无法使用默认检测器参数使其正常工作，因此我进行了一些试验以获得最佳结果。

在标准输出和显示器上，我可以看到检测器无法获取每一帧上的每个标记，但我不知道如何实现更好的检测率。

这是我的 python 代码：


import cv2 as cv

print(cv.__version__)

import argparse
import sys
import os.path
import numpy as np
import json
winName = "Augmented Reality using Aruco markers in OpenCV"

parser = argparse.ArgumentParser(description='Augmented Reality using Aruco markers in OpenCV')
parser.add_argument('--video', default='ar_in.avi', help='Path to the input video file.')
args = parser.parse_args()

if not os.path.isfile(args.video):
    print("Input video file ", args.video, " doesn't exist")
    parser.print_help()
    sys.exit(1)
cap = cv.VideoCapture(args.video)

# Initialize the detector parameters - picked a working combination from millions of random examples
parameters =  cv.aruco.DetectorParameters_create()
parameters.minDistanceToBorder =  7
parameters.cornerRefinementMaxIterations = 149
parameters.minOtsuStdDev= 4.0
parameters.adaptiveThreshWinSizeMin= 7
parameters.adaptiveThreshWinSizeStep= 49
parameters.minMarkerDistanceRate= 0.014971725679291437
parameters.maxMarkerPerimeterRate= 10.075976700411534 
parameters.minMarkerPerimeterRate= 0.2524866841549599 
parameters.polygonalApproxAccuracyRate= 0.05562707541937206
parameters.cornerRefinementWinSize= 9
parameters.adaptiveThreshConstant= 9.0
parameters.adaptiveThreshWinSizeMax= 369
parameters.minCornerDistanceRate= 0.09167132584946237

#Load the dictionary that was used to generate the markers.
dictionary = cv.aruco.Dictionary_get(cv.aruco.DICT_5X5_50)

detected_markers={}
frame_counter = 0
while cv.waitKey(1) < 0:
    frame_counter += 1
    try:
        # get frame from the video
        hasFrame, frame = cap.read()
        # Stop the program if reached end of video
        if not hasFrame:
            print("Done processing !!!")
            cv.waitKey(3000)
            break
                
        # Detect the markers in the image
        markerCorners, markerIds, rejectedCandidates = cv.aruco.detectMarkers(frame, dictionary, parameters=parameters)
        print('frame: {} ids: {}'.format(frame_counter, markerIds.tolist()))
        im_out = cv.aruco.drawDetectedMarkers(frame, markerCorners, markerIds)

        # Showing the original image with the markers drawn on it
        cv.imshow(winName, im_out.astype(np.uint8))

    except Exception as inst:
        print(inst)
    
cv.destroyAllWindows()

标准输出如下所示：

$ ar_with_aruco.py
4.1.1
frame: 1 ids: [[21], [22]]
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Done processing !!!

Answer 1

马克笔太粗了，相机拍到了侧面。该算法可能无法识别黑色方形边缘。我使标记更薄，因此 aruco 检测现在更加稳健。也许一点白边可以使标记可识别。我把我的问题留在这里，这样任何人都可以从中学习。我已将新视频上传到我的github。

如何在 OpenCV 4.1.1 Aruco 标记检测中实现更高的稳定性？

How to achieve more stability in OpenCV 4.1.1 Aruco marker detection?

python

opencv

marker

aruco

stability