Hello,
I tried to detect and recognize face through LBPH algorithm. For that, I tried the following example:
Mastering OpenCV Chapter 8 FaceRecognition
The code runs and works successfully for Eignefaces and Fisherfaces but gives an exception when recognize for LBPH algorithm. I can't figure it out. The exception is:
OpenCV Error: Bad argument (no parameter 'eigenvectors' is found) in unknown function, file "..\modules\core\src\algorithm.cpp" line 882.
In line 882,
CV_Error_( CV_StsBadArg, ("No parameter '%s' is found", parameter ? parameter : "<NULL>") );
So, what am I doing wrong? Please experts come and rescue me. Thanks
Update:
The following is the code where is the problem:
else if (m_mode == MODE_RECOGNITION) {
if (gotFaceAndEyes && (preprocessedFaces.size() > 0) && (preprocessedFaces.size() == faceLabels.size())) {
// Generate a face approximation by back-projecting the eigenvectors & eigenvalues.
Mat reconstructedFace;
reconstructedFace = reconstructFace(model, preprocessedFace);
if (m_debug)
if (reconstructedFace.data)
imshow("reconstructedFace", reconstructedFace);
// Verify whether the reconstructed face looks like the preprocessed face, otherwise it is probably an unknown person.
double similarity = getSimilarity(preprocessedFace, reconstructedFace);
string outputStr;
if (similarity < UNKNOWN_PERSON_THRESHOLD) {
// Identify who the person is in the preprocessed face image.
identity = model->predict(preprocessedFace);
outputStr = toString(identity);
}
else {
// Since the confidence is low, assume it is an unknown person.
outputStr = "Unknown";
}
cout << "Identity: " << outputStr << ". Similarity: " << similarity << endl;
// Show the confidence rating for the recognition in the mid-top of the display.
int cx = (displayedFrame.cols - faceWidth) / 2;
Point ptBottomRight = Point(cx - 5, BORDER + faceHeight);
Point ptTopLeft = Point(cx - 15, BORDER);
// Draw a gray line showing the threshold for an "unknown" person.
Point ptThreshold = Point(ptTopLeft.x, ptBottomRight.y - (1.0 - UNKNOWN_PERSON_THRESHOLD) * faceHeight);
rectangle(displayedFrame, ptThreshold, Point(ptBottomRight.x, ptThreshold.y), CV_RGB(200,200,200), 1, CV_AA);
// Crop the confidence rating between 0.0 to 1.0, to show in the bar.
double confidenceRatio = 1.0 - min(max(similarity, 0.0), 1.0);
Point ptConfidence = Point(ptTopLeft.x, ptBottomRight.y - confidenceRatio * faceHeight);
// Show the light-blue confidence bar.
rectangle(displayedFrame, ptConfidence, ptBottomRight, CV_RGB(0,255,255), CV_FILLED, CV_AA);
// Show the gray border of the bar.
rectangle(displayedFrame, ptTopLeft, ptBottomRight, CV_RGB(200,200,200), 1, CV_AA);
}
}
