surf

问题 I would like to plot a 3D graph, y=100-x^2, cycle around the Y axis in 360 degrees. Eventually to become like a cone. Is that possible? I have an array x=1:1:100 , and an array y , size(1 100). I tried an Z array, z=1:1:100 as the 3th axis in the base of the cone. With plot3 I done the one graph of y=100-x^2. I would like to kinda animate it and have eventually a cone, or a surface cone. 回答1: Is this what you are looking for? r = 1:1:100; y = 100-r.^2; theta = 0:pi/20:2*pi; xx = bsxfun(@times

问题 I am using the python bindings for OpenCV 2.4.X and OpenCV 3.1 but with the following simple two-liner import cv2 detector = cv2.FeatureDetector_create("SURF") I get the following output: Traceback (most recent call last): File "version_test.py", line 3, in <module> detector = cv2.FeatureDetector_create("SURF") AttributeError: 'module' object has no attribute 'FeatureDetector_create' What are the reasons for this error in each version? 回答1: It seemed that I need opencv-devel and opencv

问题 I am wondering what is the maximum distance of detection/recognition of an image using SURF method? Has any one tried. Camera: Logitech Webcam Pro 9000 回答1: In computer vision the distance from camera does not really matter. What matters is the expanse size of the object contour. For example you can place a really huge object 10km from camera's object-glass and it could still cover the whole visual field. From CV point of view, it will be the same as having a small object right in front of

问题 I want to extract (x,y) pixel coordinates out of the SURF points returned, as an example in the example provided here using Matlab. It is clear that using 'ptsIn(1).Location' I can return the (x,y) coordinates of the point. But the points retuned included some decimal points as well, as an example (102.9268, 51.7285). Is there any way to convert this to pixel positions in the image plane, or just averaging these values will give the pixel positions? Thank you. 回答1: To understand it further I

问题 I want to compute SURF Features from keypoints that I specify. I am using the Python wrapper of OpenCV. The following is the code I am trying to use, but I cannot find a working example anywhere. surf = cv2.SURF() keypoints, descriptors = surf.detect(np.asarray(image[:,:]),None,useProvidedKeypoints = True) How can I specify the keypoints to be used by this function? Similar, unanswered, question: cvExtractSURF don't work when useProvidedKeypoints = true Documentation 回答1: If I understand the

问题 I am attempting to implement the OpenCV 3.0.0 SURF Feature Description and Detection but after running the sample code on the OpenCV site, I receive a load of errors all related to SURF. Any idea of what could be going wrong? Thanks! #include <stdio.h> #include <iostream> #include "opencv2/core.hpp" #include "opencv2/features2d.hpp" #include "opencv2/highgui.hpp" #include "opencv2/calib3d.hpp" #include "opencv2/xfeatures2d.hpp" #include <opencv2/nonfree/nonfree.hpp> using namespace cv; using

问题 I am using sift algorithm in opencv code to get descriptors and keypoints from images.My code is Ptr<IplImage> image; vector<KeyPoint> keypoints; OutputArray des; Feature2D *descriptor_type = new SIFT() Mat image_mat(image); (*descriptor_type)(image_mat,noArray(),keypoints,des,false); Here I can get the keypoints of the image in vector < KeyPoint > .After that,I want to get the Octave of each KeyPoint for more details .But when I cout each keypoint octave value for one image,it seems so

问题 I know there are already several questions with the same subject asked here, but I couldn't find any help. So I want to compare 2 images in order to see how similar they are and I'm using the well known find_obj.cpp demo to extract surf descriptors and then for the matching I use the flannFindPairs. But as you know this method doesn't discard the outliers and I'd like to know the number of true positive matches so I can figure how similar those two images are. I have already seen this

问题 I am trying to use OpenCV to match images like these: img2 http://img849.imageshack.us/img849/8177/clearz.jpg And I need to find the best intersection of them. I tried using SURFDetector and matching using BruteforceMatcher, but finds descriptors not equal. Tell me please the correct way to solve problem. 回答1: Did you have a look to this code example? Here you can see how to find an object using SURF descriptors. Go to main(), and check the code step by step. You can try it with your images

问题 I'm trying to get started working with sift feature extraction using (C++) OpenCv. I need to extract features using SIFT, match them between the original image (e.g. a book) and a scene, and after that calculate the camera pose. So far I have found this algorithm using SURF. Does anyone know a base code from which I can get started, or maybe a way to convert the algorithm in the link from SURF to SIFT? Thanks in advance. EDIT: Ok, I worked out a solution for the sift problem. Now I'm trying