/external/opencv3/doc/py_tutorials/py_feature2d/py_orb/ |
D | py_orb.markdown | 1 ORB (Oriented FAST and Rotated BRIEF) {#tutorial_py_orb} 8 - We will see the basics of ORB 13 As an OpenCV enthusiast, the most important thing about the ORB is that it came from "OpenCV Labs". 15 their paper **ORB: An efficient alternative to SIFT or SURF** in 2011. As the title says, it is a 17 Yes, SIFT and SURF are patented and you are supposed to pay them for its use. But ORB is not !!! 19 ORB is basically a fusion of FAST keypoint detector and BRIEF descriptor with many modifications to 30 Now for descriptors, ORB use BRIEF descriptors. But we have already seen that BRIEF performs poorly 31 with rotation. So what ORB does is to "steer" BRIEF according to the orientation of keypoints. For 36 ORB discretize the angle to increments of \f$2 \pi /30\f$ (12 degrees), and construct a lookup tabl… 44 to the result. To resolve all these, ORB runs a greedy search among all possible binary tests to [all …]
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/external/opencv3/modules/features2d/perf/ |
D | perf_orb.cpp | 25 Ptr<ORB> detector = ORB::create(1500, 1.3f, 1); in PERF_TEST_P() 45 Ptr<ORB> detector = ORB::create(1500, 1.3f, 1); in PERF_TEST_P() 67 Ptr<ORB> detector = ORB::create(1500, 1.3f, 1); in PERF_TEST_P()
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/external/opencv3/modules/features2d/perf/opencl/ |
D | perf_orb.cpp | 25 Ptr<ORB> detector = ORB::create(1500, 1.3f, 1); in OCL_PERF_TEST_P() 47 Ptr<ORB> detector = ORB::create(1500, 1.3f, 1); in OCL_PERF_TEST_P() 77 Ptr<ORB> detector = ORB::create(1500, 1.3f, 1); in OCL_PERF_TEST_P()
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/external/opencv3/modules/features2d/misc/java/src/cpp/ |
D | features2d_manual.hpp | 33 ORB = 5, in CV_EXPORTS_AS() 49 GRID_ORB = GRIDDETECTOR + ORB, in CV_EXPORTS_AS() 65 PYRAMID_ORB = PYRAMIDDETECTOR + ORB, in CV_EXPORTS_AS() 80 DYNAMIC_ORB = DYNAMICDETECTOR + ORB, in CV_EXPORTS_AS() 126 case ORB: in CV_EXPORTS_AS() 127 fd = ORB::create(); in CV_EXPORTS_AS() 317 ORB = 3, 330 OPPONENT_ORB = OPPONENTEXTRACTOR + ORB, 358 case ORB: 359 de = ORB::create();
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/external/opencv3/modules/java/src/ |
D | features2d+FeatureDetector.java | 33 ORB = 5, field in FeatureDetector 45 GRID_ORB = GRIDDETECTOR + ORB, 57 PYRAMID_ORB = PYRAMIDDETECTOR + ORB, 69 DYNAMIC_ORB = DYNAMICDETECTOR + ORB,
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D | features2d+DescriptorExtractor.java | 29 ORB = 3, field in DescriptorExtractor 36 OPPONENT_ORB = OPPONENTEXTRACTOR + ORB,
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/external/opencv3/modules/cudafeatures2d/include/opencv2/ |
D | cudafeatures2d.hpp | 455 class CV_EXPORTS ORB : public cv::ORB, public Feature2DAsync class 469 static Ptr<ORB> create(int nfeatures=500, 475 int scoreType=ORB::HARRIS_SCORE,
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/external/opencv3/modules/cudafeatures2d/perf/ |
D | perf_features2d.cpp | 99 PERF_TEST_P(Image_NFeatures, ORB, 112 cv::Ptr<cv::cuda::ORB> d_orb = cv::cuda::ORB::create(nFeatures); 134 cv::Ptr<cv::ORB> orb = cv::ORB::create(nFeatures);
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/external/opencv3/modules/features2d/test/ |
D | test_descriptors_regression.cpp | 258 Ptr<ORB> fd = ORB::create(); in regressionTest() 330 ORB::create() ); in TEST() 357 Ptr<ORB> orb = ORB::create(); in TEST() 387 Ptr<ORB> orb = ORB::create(); in TEST()
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D | test_orb.cpp | 50 Ptr<FeatureDetector> fd = ORB::create(10000, 1.2f, 8, 31, 0, 2, ORB::HARRIS_SCORE, 31, 20); in TEST()
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D | test_keypoints.cpp | 163 CV_FeatureDetectorKeypointsTest test(ORB::create()); in TEST()
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/external/opencv3/modules/cudafeatures2d/test/ |
D | test_features2d.cpp | 125 CV_ENUM(ORB_ScoreType, cv::ORB::HARRIS_SCORE, cv::ORB::FAST_SCORE) in CV_ENUM() 127 PARAM_TEST_CASE(ORB, cv::cuda::DeviceInfo, ORB_FeaturesCount, ORB_ScaleFactor, ORB_LevelsCount, ORB… in CV_ENUM() 157 CUDA_TEST_P(ORB, Accuracy) in CUDA_TEST_P() argument 165 cv::Ptr<cv::cuda::ORB> orb = in CUDA_TEST_P() 166 cv::cuda::ORB::create(nFeatures, scaleFactor, nLevels, edgeThreshold, firstLevel, in CUDA_TEST_P() 188 …cv::Ptr<cv::ORB> orb_gold = cv::ORB::create(nFeatures, scaleFactor, nLevels, edgeThreshold, firstL… in CUDA_TEST_P() 205 INSTANTIATE_TEST_CASE_P(CUDA_Features2D, ORB, testing::Combine( 213 testing::Values(ORB_ScoreType(cv::ORB::HARRIS_SCORE)),
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/external/opencv3/modules/cudafeatures2d/src/ |
D | orb.cpp | 50 Ptr<cv::cuda::ORB> cv::cuda::ORB::create(int, float, int, int, int, int, int, int, int, bool) { thr… in create() 338 class ORB_Impl : public cv::cuda::ORB 705 if (scoreType_ == ORB::HARRIS_SCORE) in computeKeyPointsPyramid() 854 Ptr<cv::cuda::ORB> cv::cuda::ORB::create(int nfeatures, in create()
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/external/opencv3/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/ |
D | RobustMatcher.h | 22 detector_ = cv::ORB::create(); in RobustMatcher() 23 extractor_ = cv::ORB::create(); in RobustMatcher()
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/external/opencv3/doc/py_tutorials/py_feature2d/py_matcher/ |
D | py_matcher.markdown | 21 string based descriptors like ORB, BRIEF, BRISK etc, cv2.NORM_HAMMING should be used, which used 22 Hamming distance as measurement. If ORB is using WTA_K == 3 or 4, cv2.NORM_HAMMING2 should be 41 Let's see one example for each of SURF and ORB (Both use different distance measurements). 43 ### Brute-Force Matching with ORB Descriptors 60 orb = cv2.ORB() 67 ORB) and crossCheck is switched on for better results. Then we use Matcher.match() method to get the 153 While using ORB, you can pass the following. The commented values are recommended as per the docs,
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/external/opencv3/samples/cpp/tutorial_code/xfeatures2D/ |
D | LATCH_match.cpp | 36 Ptr<cv::ORB> orb_detector = cv::ORB::create(10000); in main()
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/external/opencv3/doc/tutorials/features2d/akaze_tracking/ |
D | akaze_tracking.markdown | 1 AKAZE and ORB planar tracking {#tutorial_akaze_tracking} 7 In this tutorial we will compare *AKAZE* and *ORB* local features using them to find matches between 134 *ORB* statistics:
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/external/opencv3/samples/cpp/tutorial_code/features2D/AKAZE_tracking/ |
D | planar_tracking.cpp | 142 Ptr<ORB> orb = ORB::create(); in main()
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/external/opencv3/doc/tutorials/calib3d/ |
D | table_of_content_calib3d.markdown | 31 Real time pose estimation of a textured object using ORB features, FlannBased matcher, PnP
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/external/opencv3/doc/tutorials/calib3d/real_time_pose/ |
D | real_time_pose.markdown | 23 - Extract ORB features and descriptors from the scene. 77 The application starts up extracting the ORB features and descriptors from the input image and 92 structure explained in the model registration program. From the scene, the ORB features and 240 -# **Extract ORB features and descriptors from the scene** 247 …@ref cv::ORB features because is based on @ref cv::FAST to detect the keypoints and cv::xfeatures2… 249 detailed information about *ORB* in the documentation. 256 …tor * detector = new cv::OrbFeatureDetector(numKeyPoints); // instatiate ORB feature detector 257 …tor * extractor = new cv::OrbDescriptorExtractor(); // instatiate ORB descriptor extractor 274 Similarity Search* due to *ORB* descriptors are binary. 326 // 1a. Detection of the ORB features [all …]
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/external/opencv3/modules/stitching/include/opencv2/stitching/detail/ |
D | matchers.hpp | 130 Ptr<ORB> orb;
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/external/opencv3/modules/features2d/include/opencv2/ |
D | features2d.hpp | 254 class CV_EXPORTS_W ORB : public Feature2D class 289 …CV_WRAP static Ptr<ORB> create(int nfeatures=500, float scaleFactor=1.2f, int nlevels=8, int edgeT… 290 …int firstLevel=0, int WTA_K=2, int scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshol…
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/external/opencv3/modules/features2d/misc/java/test/ |
D | ORBDescriptorExtractorTest.java | 36 extractor = DescriptorExtractor.create(DescriptorExtractor.ORB); in setUp()
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/external/opencv3/doc/tutorials/features2d/ |
D | table_of_content_features2d.markdown | 95 Using *AKAZE* and *ORB* for planar object tracking.
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/external/opencv3/samples/gpu/performance/ |
D | tests.cpp | 337 TEST(ORB) in TEST() argument 342 Ptr<ORB> orb = ORB::create(4000); in TEST() 353 Ptr<cuda::ORB> d_orb = cuda::ORB::create(); in TEST()
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