Failed to detect Zivid calibration board

Problem

Zivid SDK is not able to detect the checkerboard during hand-eye calibration or infield correction/verification.

Possible causes and solutions

When using the Zivid calibration board, the fiducial/ArUco marker must be visible in the image. Otherwise, the checkerboard detection will fail when performing infield correction or hand-eye calibration. This is not required when using the 9x6 grey-white checkerboards as they don’t have a fiducial marker on them. However, we recommend using the calibration boards as these have been qualified and individually verified by Zivid.

Non-visible fiducial marker	Visible fiducial marker

Tip

Use Zivid Studio to inspect if the capture is good

Note that the SDK does not throw an error if the function is not able to detect any feature points. It will instead return an empty list. The reasoning is that not finding a checkerboard in a point cloud is considered a normal failure and not an (exceptional) error. Therefore, we recommend validating if the detection result after capturing using valid() operator. The code below illustrates how to implement this in a program.

C++

source

const auto detectionResult = Zivid::Calibration::detectFeaturePoints(frame.pointCloud());

if(detectionResult.valid())
{
    std::cout << "Calibration board detected " << std::endl;
    handEyeInput.emplace_back(Zivid::Calibration::HandEyeInput{ robotPose, detectionResult });
    currentPoseId++;
}
else
{
    std::cout
        << "Failed to detect calibration board, ensure that the entire board is in the view of the camera"
        << std::endl;
}

C#

source

var detectionResult = Detector.DetectFeaturePoints(frame.PointCloud);

if(detectionResult.Valid())
{
    Console.WriteLine("Calibration board detected");
    handEyeInput.Add(new HandEyeInput(robotPose, detectionResult));
    ++currentPoseId;
}
else
{
    Console.WriteLine("Failed to detect calibration board, ensure that the entire board is in the view of the camera");
}

Python

source

detection_result = zivid.calibration.detect_feature_points(frame.point_cloud())

if detection_result.valid():
    print("Calibration board detected")
    hand_eye_input.append(zivid.calibration.HandEyeInput(robot_pose, detection_result))
    current_pose_id += 1
else:
    print(
        "Failed to detect calibration board, ensure that the entire board is in the view of the camera"
    )