orb

问题 i want to save orb features to database that i get from this code: bmp=BitmapFactory.decodeResource(getResources(),R.drawable.t1); Utils.bitmapToMat(bmp, mat); FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB); detector.detect(mat, keypoints); DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB); extractor.compute(mat, keypoints, features); i using json code to save the data from Mat of feature with the code i get from here: http://answers

问题 I had an application which is tightly coupled with jacorb and it is working great with Jboss. Now, i have to migrate this application to deploy the same in Websphere 8.5.5. General flow is , my application will reach another system (developed in C++) through corba usign jacorb. since IBM is having its own ORB implementations, My application is getting deployed in websphere. If my application is modified to make use of IBM orb jars, then 80% of applciation have to change. Kindly suggest me the

问题 I was just making a small experiment to play around with different detector/descriptor combinations. My code uses an ORB_GPU detector for detection of features and SURF_GPU descriptor for calculating the descriptors. I uses a BruteForceMatcher_GPU to match the descriptors and i am suing the knnMatch method to get the matches. The problem is I am getting a lot of unwanted matches, the code is literally matching every feature it could find in both the images. I am quite confused with this

问题 I read some paper about LSH and I know that is used for solving the approximated k-NN problem. We can divide the algorithm in two parts: Given a vector in D dimensions (where D is big) of any value, translate it with a set of N (where N<<D ) hash functions to a binary vector in N dimensions. Using hamming distance, apply some search technique on the set of given binary codes obtained from phase 1 to find the k-NN. The keypoint is that computing the hamming distance for vectors in N dimensions

问题 I am using the ORB feature detector to find matches between two images using this code: FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB); DescriptorExtractor descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);; DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING); // First photo Imgproc.cvtColor(img1, img1, Imgproc.COLOR_RGB2GRAY); Mat descriptors1 = new Mat(); MatOfKeyPoint keypoints1 = new MatOfKeyPoint(); detector

问题 I have application in CORBA using IIOP protocol, i am using the Java IDL component of the JDK 6 , another ORB implementation. Implementation of both client and server in Java language. Is there any way in the JDK ORB implementation to get the client ORB`s host and port from the server (ORB)code ? Or is there any way with use of IIOP protocol, get client the host and port ? This is we are doing for identification of the client to track the who is requested 回答1: I don't think there is any

问题 I am using OpenCV 3.2 I am trying to use FLANN to match features descriptors in a faster way than brute force. // Ratio to the second neighbor to consider a good match. #define RATIO 0.75 void matchFeatures(const cv::Mat &query, const cv::Mat &target, std::vector<cv::DMatch> &goodMatches) { std::vector<std::vector<cv::DMatch>> matches; cv::Ptr<cv::FlannBasedMatcher> matcher = cv::FlannBasedMatcher::create(); // Find 2 best matches for each descriptor to make later the second neighbor test.

问题 How can I draw a bounding box on best matches in BF MATCHER using Python? 回答1: Here is a summary of the approach it should be a proper solution: Detect keypoints and descriptors on the query image (img1) Detect keypoints and descriptors on the target image (img2) Find the matches or correspondences between the two sets of descriptors Use the best 10 matches to form a transformation matrix Transform the rectangle around img1 based on the transformation matrix Add offset to put the bounding box

问题 I wish to stitch two or more images using OpenCV and C++. The images have regions of overlap but they are not being detected. I tried using homography detector. Can someone please suggest as to what other methods I should use. Also, I wish to use the ORB algorithm, and not SIFT or SURF. The images can be found at- https://drive.google.com/open?id=133Nbo46bgwt7Q4IT2RDuPVR67TX9xG6F 回答1: This a very common problem. Because images like this, they actually do not have much in common. The overlap

问题 I have a small image 50x50. I find ORB keypoints with: (Notice that I have to change the default param of patchSize from 31 to 14 to get some keypoints detected): OrbFeatureDetector det(500,1.2f,8,14,0,2,0,14); //> (From 31 to 14) OrbDescriptorExtractor desc; det.detect(image,kp) //> kp.size() is about 50 keypoints Now If i pass my keypoints to orb.compute I get all keypoints erased. desc.compute(image,kp,kpDesc); //> Now kp.size() == 0 This mean that after I have called .compute the method