Regarding cvFeatureTree Function

[Chen Kai-2]

Hi:

    Recently I am doing object recognition using SURF implemented in OpenCV 1.1pre version, after cvExtractSURF function, I tried cvFeatureTree and cvFindFeatures functions to find correspond points between two images. And whether a descriptor is matched is decided by comparing two nearest descriptors, if distMin1 < 0.6 * distMin2, then it's accepted. But it was strange when using cvFindFeatures, it cannot find any correspond points meeting above criteria. Meanwhile, a most naive function to find matched points will work.(Test data is the same)

    So I am writing to ask if there is anything wrong with this function, or I just misused it.

 

    Part of the source code :

 

CvMemStorage* storage = cvCreateMemStorage(0);

 

//Load image from disk
IplImage* IplGray1,* IplGray2;
IplGray1 = cvLoadImage(argv[2], CV_LOAD_IMAGE_GRAYSCALE );
IplGray2 = cvLoadImage(argv[2], CV_LOAD_IMAGE_GRAYSCALE );

 

CvSURFParams surfParam = cvSURFParams(1000.0, 1);
CvSeq* img1KPoints,* img2KPoints;
CvSeq* img1Descriptors,* img2Descriptors;

 

cvExtractSURF(IplGray1, 0, &img1KPoints, &img1Descriptors, storage, surfParam);
cvExtractSURF(IplGray2, 0, &img2KPoints, &img2Descriptors, storage, surfParam);

 

//two image's descriptor numbers.
int img1DescNum = img1Descriptors->total;
int img2DescNum = img2Descriptors->total;
int length = img1Descriptors->elem_size / sizeof(float);//Descriptor length

 

CvMat* desc1Mat,* desc2Mat;
desc1Mat = cvCreateMat(img1DescNum, length, CV_32FC1);
desc2Mat = cvCreateMat(img2DescNum, length, CV_32FC1);

 

//copy descriptor sequence to matrix
for (int i(0); i < img1DescNum; i++)
{
     float* curDesc = (float*)cvGetSeqElem(img1Descriptors, i);
     for (int k(0); k < length; k++)
          CV_MAT_ELEM(*desc1Mat, float, i, k) = curDesc[k];
}
for (int i(0); i < img2DescNum; i++)
{
     float* curDesc = (float*)cvGetSeqElem(img2Descriptors, i);
     for (int k(0); k < length; k++)
          CV_MAT_ELEM(*desc2Mat, float, i, k) = curDesc[k];
}

 

//Uses KD-Tree in OpenCV to match key points:
CvFeatureTree* KDTree = cvCreateFeatureTree(desc1Mat);
CvMat* matResults,* matDist;
matResults = cvCreateMat(img2DescNum, 2, CV_32S);
matDist = cvCreateMat(img2DescNum, 2, CV_64FC1);
cvFindFeatures(KDTree, desc2Mat, matResults, matDist, 2, 400);//To find 2 nearest neighbors
int numMatched(0);
for (int i(0); i < matDist->rows; i++)
{
    double dist1 = CV_MAT_ELEM(*matDist, double, i, 0);
    double dist2 = CV_MAT_ELEM(*matDist, double, i, 1);
    double minDist = MIN(dist1, dist2);
    double maxDist = MAX(dist2, dist2);
    if (minDist < 0.6 * maxDist)// Check if it meets the criteria
    {
        int idx1, idx2;
        idx1 = CV_MAT_ELEM(*matResults, int, i, 0);
        idx2 = CV_MAT_ELEM(*matResults, int, i, 1);
        CvSURFPoint* pt1,* pt2;
        pt1 = (CvSURFPoint*)cvGetSeqElem(img1KPoints, idx1);
        pt2 = (CvSURFPoint*)cvGetSeqElem(img2KPoints, idx2);

 

        //This line is for visualizing
        //cvLine(IplMatched, cvPoint(pt1->pt.x, pt2->pt.y), cvPoint(pt2->pt.x + IplImg1->width, pt2->pt.y), colors[i%8]);
  
        numMatched++;
    }
}
printf("%d points matched using KD-tree-BBF search!\n", numMatched);
//Result: numMatched is always 0 or 1...
//Where did I go wrong?

 

    Thank you for your time.

    Looking forward to your reply.

 

-------------------------------
Best Wishes

School of Computer Science and Technology

University of Science and Technology of China

K.Chen

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