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class | cv::xfeatures2d::AffineFeature2D |
| Class implementing affine adaptation for key points. More...
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class | cv::xfeatures2d::BoostDesc |
| Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [203] and [204]. More...
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class | cv::xfeatures2d::BriefDescriptorExtractor |
| Class for computing BRIEF descriptors described in [39] . More...
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class | cv::xfeatures2d::DAISY |
| Class implementing DAISY descriptor, described in [211]. More...
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class | cv::xfeatures2d::Elliptic_KeyPoint |
| Elliptic region around an interest point. More...
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class | cv::xfeatures2d::FREAK |
| Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in [7] . More...
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class | cv::xfeatures2d::HarrisLaplaceFeatureDetector |
| Class implementing the Harris-Laplace feature detector as described in [156]. More...
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class | cv::xfeatures2d::LATCH |
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class | cv::xfeatures2d::LUCID |
| Class implementing the locally uniform comparison image descriptor, described in [255]. More...
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class | cv::xfeatures2d::MSDDetector |
| Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [212]. More...
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class | cv::xfeatures2d::PCTSignatures |
| Class implementing PCT (position-color-texture) signature extraction as described in [122]. The algorithm is divided to a feature sampler and a clusterizer. Feature sampler produces samples at given set of coordinates. Clusterizer then produces clusters of these samples using k-means algorithm. Resulting set of clusters is the signature of the input image. More...
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class | cv::xfeatures2d::PCTSignaturesSQFD |
| Class implementing Signature Quadratic Form Distance (SQFD). More...
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class | cv::xfeatures2d::StarDetector |
| The class implements the keypoint detector introduced by [2], synonym of StarDetector. : More...
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class | cv::xfeatures2d::VGG |
| Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [194]. More...
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