keypoint

问题 I'm currently working on a personal project with OpenCV and I have a few issues during the execution of the program. After implementing an AKAZE + BOW recognizer (which didn't seem to work well enough for my problem) I wanted to try out a SIFT (and eventually SURF) implementation. For my project I'm following this one found on github and I'm using VS2015 (community) and OpenCV 2.4.13 over Windows 10. The issue I'm having, as stated in the title, lies with the ucrtbase.dll which gets an

问题 I am trying to understand how to get the descriptor for a given KeyPoint in OpenCV. So far my code looks like follows: #include <iostream> #include "opencv2/opencv.hpp" typedef cv::Mat Image; int main(int argc, const char * argv[]) { Image imgA = cv::imread("images/buddhamulticam_total100.png", CV_LOAD_IMAGE_GRAYSCALE); Image imgB = cv::imread("images/buddhamulticam_total101.png", CV_LOAD_IMAGE_GRAYSCALE); cv::Ptr<cv::FeatureDetector> detector = cv::FeatureDetector::create("ORB"); cv::Ptr<cv:

问题 I'm java developer .My goal is to detect image keypoints using javaCV this is my code : final CvMat image1 = cvLoadImageM("im1.png" , 0); final CvMat image2 = cvLoadImageM("im2.png", 0); SIFT sift = new SIFT(); FeatureDetector featureDetector =sift.getFeatureDetector(); KeyPoint keypoint1 = new KeyPoint(); KeyPoint keypoint2 = new KeyPoint() ; featureDetector.detect(image1, keypoint1 , null); featureDetector.detect(image2,keypoint2, null); but when I run this code I got an access violation

问题 I'm java developer .My goal is to detect image keypoints using javaCV this is my code : final CvMat image1 = cvLoadImageM("im1.png" , 0); final CvMat image2 = cvLoadImageM("im2.png", 0); SIFT sift = new SIFT(); FeatureDetector featureDetector =sift.getFeatureDetector(); KeyPoint keypoint1 = new KeyPoint(); KeyPoint keypoint2 = new KeyPoint() ; featureDetector.detect(image1, keypoint1 , null); featureDetector.detect(image2,keypoint2, null); but when I run this code I got an access violation

问题 I followed a blob detection example (using cv2.SimpleBlobDetector ) and successfully detected the blobs in my binary image. But then I don't know how to extract the coordinates and area of the keypoints. Here are the code for the blob detections: # I skipped the parameter setting part. blobParams = cv2.SimpleBlobDetector_Params() blobVer = (cv2.__version__).split('.') if int(blobVer[0]) < 3: detector = cv2.SimpleBlobDetector(blobParams) else: detector = cv2.SimpleBlobDetector_create

问题 I am trying to only draw the keypoints ( without the image) using this example code: import cv2 import numpy as np img = cv2.imread('test.png') gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) sift = cv2.SIFT() kp = sift.detect(gray,None) img=cv2.drawKeypoints(gray,kp) cv2.imwrite('sift_keypoints.jpg',img) I tried cv2.drawKeypoints(None,kp) and cv2.drawKeypoints(kp) but to no avail. Any ideas how this could be achieved ? Thanks. 回答1: You can get ONLY the keypoints by drawing them on a solid black

问题 I want get the SIFT feature for specified points. These points is gotten by hand not by KeyPoint Detector. My question is: I only know the position of the points but have no idea about the size and angle value. How should I set this value? Here is my code: int main() { Mat img_object = imread("img/test.jpg", 0); SiftDescriptorExtractor extractor; Mat descriptors; std::vector<KeyPoint> keypoints; // set keypoint position and size: should I set // size parameter to 32 for 32x32 patch? KeyPoint

问题 In reference manual of OpenCV 2.4.3 KeyPoint::class_id is described as "object id that can be used to clustered keypoints by an object they belong to". Due to lack of my adequate knowledge about 'keypoint' I can't understand whats the purpose of class_id . My another question is, by using feature detector, descriptor and matcher we can detect matching keypoints of a query object in a training image. But how can segment out the query object in the training image. Can we use grabcut or

问题 We were using SIFT in openCV 2.4.3 and we decided to upgrade to openCV 2.4.6. After the upgrade, the memory usage jumped from about (150MB) to 1.2GB in openCV 2.4.6. Does someone knows if is this a bug or something that we need to configure now? Our image has 1.4MB. This behavior was observed on iOS. The problem seems to be happening also in Linux (CentOs). Tks 回答1: I remember there was a bug in one of those versions regarding keypoint extraction. I saw it with ORB, so I don't know if it is

问题 I'm experiencing a performance problem when I use BRISK for feature detection and description in OpenCV. Basically I try to match all the descriptors I get from this image: against all the descriptors I get from a database of images using flann based matcher with the LSH algorithm and BRISK for feature detection and description. My database of images is composed of 242 images. In this 242 images there are three images corresponding to each object taken separately in the above "complex" image