[−][src]Module opencv::features2d
2D Features Framework
Feature Detection and Description
Descriptor Matchers
Matchers of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. This section is devoted to matching descriptors that are represented as vectors in a multidimensional space. All objects that implement vector descriptor matchers inherit the DescriptorMatcher interface.
Note:
- An example explaining keypoint matching can be found at opencv_source_code/samples/cpp/descriptor_extractor_matcher.cpp
- An example on descriptor matching evaluation can be found at opencv_source_code/samples/cpp/detector_descriptor_matcher_evaluation.cpp
- An example on one to many image matching can be found at opencv_source_code/samples/cpp/matching_to_many_images.cpp
Drawing Function of Keypoints and Matches
Object Categorization
This section describes approaches based on local 2D features and used to categorize objects.
Note:
- A complete Bag-Of-Words sample can be found at opencv_source_code/samples/cpp/bagofwords_classification.cpp
- (Python) An example using the features2D framework to perform object categorization can be found at opencv_source_code/samples/python/find_obj.py
Structs
BFMatcher | Brute-force descriptor matcher. |
BOWImgDescriptorExtractor | Class to compute an image descriptor using the bag of visual words. |
BOWKMeansTrainer | kmeans -based class to train visual vocabulary using the bag of visual words approach. : |
BRISK | Class implementing the BRISK keypoint detector and descriptor extractor, described in LCS11 . |
DrawMatchesFlags |
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FlannBasedMatcher | Flann-based descriptor matcher. |
KeyPointsFilter | A class filters a vector of keypoints. |
SimpleBlobDetector | Class for extracting blobs from an image. : |
SimpleBlobDetector_Params |
Constants
Traits
AKAZE | Class implementing the AKAZE keypoint detector and descriptor extractor, described in ANB13. |
AgastFeatureDetector | Wrapping class for feature detection using the AGAST method. : |
BOWTrainer | Abstract base class for training the bag of visual words vocabulary from a set of descriptors. |
DescriptorMatcher | Abstract base class for matching keypoint descriptors. |
FastFeatureDetector | Wrapping class for feature detection using the FAST method. : |
Feature2D | Abstract base class for 2D image feature detectors and descriptor extractors |
GFTTDetector | Wrapping class for feature detection using the goodFeaturesToTrack function. : |
KAZE | Class implementing the KAZE keypoint detector and descriptor extractor, described in ABD12 . |
MSER | Maximally stable extremal region extractor |
ORB | Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor |
Functions
AGAST | Detects corners using the AGAST algorithm |
AGAST_with_type | Detects corners using the AGAST algorithm |
FAST | Detects corners using the FAST algorithm |
FAST_with_type | Detects corners using the FAST algorithm |
compute_recall_precision_curve | |
draw_keypoints | Draws keypoints. |
draw_matches | Draws the found matches of keypoints from two images. |
draw_vector_matches | Draws the found matches of keypoints from two images. |
evaluate_feature_detector |
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get_nearest_point | |
get_recall |