KirbX's profile - activity

cv::fisheye::projectPoints no results Hi all! I'm actually trying to use cv::fisheye::Projectpoints to create a photo f

cv::fisheye::projectPoints no results Hi all! I'm actually trying to use cv::fisheye::Projectpoints to create a photo f

Opencv4.0.1 build only x86 Hi all! I'm trying to build opencv4.0.1 for windows 10 x64. When I start CMake, I only config

Generate intrinsic matrix from exif values Hi all! I'm trying to find the Essential Matrix in order to find the movement

Generate intrinsic matrix from exif values Hi all! I'm trying to find the Essential Matrix in order to find the movement

Generate intrinsic matrix from exif values Hi all! I'm trying to find the Essential Matrix in order to find the movement

Ok, i corrected another wrong thing : std::vector<cv::Point2f> points1,points2; I gave them an initial size at the

findFundamentalMatrix and SiftGPU Hi all! I'm trying to find the Fundamental Matrix with the findFundamentalMat functio

Obivously yes, you're right... I'm using 346 points actually. Is that too much?

findFundamentalMatrix and SiftGPU Hi all! I'm trying to find the Fundamental Matrix with the findFundamentalMat functio

Thanks! :D Maybe can I ask you if you know how to do a good Best Bin First algorithm with vectors dimensions 128? I can't find any informations about this algorithm...

I'm always optimistic when I start a project! :) I use the worst case every time to be sure it'll work everywhere ;) But, I made my own SIFT implementation and strangely, it works well in the forest (or maybe it's because it's not very effective that it's more effective? I don't know) But it takes me long time to do it. So I wanted something that I can use faster :) Maybe I'll have to continue on my way ^^

Yup, that's right I could do it myself, and I will probably, if there is no other solution :). But actually, the results are quit bad :/ I'm trying to match forest images, and results are unusable ^^ So first, I have to solve this problem ^^

That's why my question is to know if there is a function implemented for big images, such as L2-SIFT (that is SIFT that work with blocks of the big image) or something like this :)

I have now edit my question, maybe it'll be more understandable.

Hello everyone! I have a little problem with the feature matching. I'm using this method with Ptr<SurfFeatureDetector> detector = SurfFeatureDetector::create(minHessian); instead of SurfFeatureDetector detector( minHessian );

But I'm using it with enormous images (72Mb / 11804 * 5850px) and when I start the program, my computer freeze! It just freeze! Nothing works any more. I just waited 30mn and nothing happened. I was wondering if there is a method that can work to do feature matching with those big images (like, if the L2-SIFT is implemented?)

Thanks in advance :) Have a nice day everyone! :)

Edit : Sorry, that's right I didn't give informations. I'm actually on Windows 7 SP1, using a DELL with 4Gb RAM. I'm working with OpenCV 3.1.0 And the code I have is :

Mat img_1 = imread("... /*Large image*/", IMREAD_GRAYSCALE);
Mat img_2 = imread("..."/*Little image*/, IMREAD_GRAYSCALE);

//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;

Ptr<SurfFeatureDetector> detector = SurfFeatureDetector::create(minHessian);
//SurfFeatureDetector detector(minHessian);

std::vector<KeyPoint> keypoints_1, keypoints_2;

detector->detect(img_1, keypoints_1);
detector->detect(img_2, keypoints_2);
std::cout << " Step 1" << std::endl;

and my computer doesn't type "Step 1" in the console, so I suppose the problem come from detector->detect(img_1, keypoints_1);

I know it works when I resize img_1 by a factor of 0.5 . So I'm sure it's a memory problem.

Hello everybody, Is there a way to denoise something like this? Grey2024.PNG

If yes, can you help me find the way??

Thanks all! Have a nice day! :)