Question

我已经在项目中使用矩形成功实现了SURF检测和跟踪。我的目标是让它尽可能快地运行（最大fps）。问题是，当我尝试使用OpenCL时，代码以1 fps运行，但是当禁用时，它以4 fps运行。我在Core-i3 PC上使用Visual Studio 2015和OpenCV3.0。相机 - 罗技HD 920

我不确定普通PC上SURF检测的平均速度是多少，但我希望它以更高的fps运行。我需要在像ODROID-XU3这样的ARM板上实现相同的代码。

由于OpenCV3.0使用透明API（在后台使用OpenCL），我认为最好让它更快，但事实并非如此。

如何让它运行得更快（fps更快）。

以下是代码：

void surf_detection::surf_detect(){

UMat img_extractor, snap_extractor;

if (crop_image_.empty())
    cv_snapshot.copyTo(dst);
else
    crop_image_.copyTo(dst);
//dst = QImagetocv(crop_image_);

imshow("dst", dst);

Ptr<SURF> detector = SURF::create(minHessian);
Ptr<DescriptorExtractor> extractor = SURF::create(minHessian);

cvtColor(dst, src, CV_BGR2GRAY);
cvtColor(frame, gray_image, CV_BGR2GRAY);


detector->detect(src, keypoints_1);
//printf("Object: %d keypoints detected\n", (int)keypoints_1.size());
detector->detect(gray_image, keypoints_2);
//printf("Object: %d keypoints detected\n", (int)keypoints_1.size());

extractor->compute(src, keypoints_1, img_extractor);
// printf("Object: %d descriptors extracted\n", img_extractor.rows);
extractor->compute(gray_image, keypoints_2, snap_extractor);

std::vector<Point2f> scene_corners(4);
std::vector<Point2f> obj_corners(4);

obj_corners[0] = (cvPoint(0, 0));
obj_corners[1] = (cvPoint(src.cols, 0));
obj_corners[2] = (cvPoint(src.cols, src.rows));
obj_corners[3] = (cvPoint(0, src.rows));

vector<DMatch> matches;
matcher.match(img_extractor, snap_extractor, matches);

double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints
for (int i = 0; i < img_extractor.rows; i++)
{
    double dist = matches[i].distance;
    if (dist < min_dist) min_dist = dist;
    if (dist > max_dist) max_dist = dist;
}
//printf("-- Max dist : %f \n", max_dist);
//printf("-- Min dist : %f \n", min_dist);

vector< DMatch > good_matches;

for (int i = 0; i < img_extractor.rows; i++)
{
    if (matches[i].distance <= max(2 * min_dist, 0.02))
    {
        good_matches.push_back(matches[i]);
    }
}

UMat img_matches;
drawMatches(src, keypoints_1, gray_image, keypoints_2,
    good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
    vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

if (good_matches.size() >= 4){

    for (int i = 0; i<good_matches.size(); i++){

        //get the keypoints from good matches
        obj.push_back(keypoints_1[good_matches[i].queryIdx].pt);
        scene.push_back(keypoints_2[good_matches[i].trainIdx].pt);

    }
}

H = findHomography(obj, scene, CV_RANSAC);

perspectiveTransform(obj_corners, scene_corners, H);

line(img_matches, scene_corners[0], scene_corners[1], Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[1], scene_corners[2], Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[2], scene_corners[3], Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[3], scene_corners[0], Scalar(0, 255, 0), 4);

imshow("Good matches", img_matches);

OpenCV3.0：启用OpenCL而不是禁用时，SURF检测速度较慢

0 个答案: