Purpose: updated the feature2d chapter
This commit is contained in:
Elena Fedotova
@@ -3,11 +3,11 @@ Common Interfaces of Descriptor Extractors
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.. highlight:: cpp
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Extractors of keypoint descriptors in OpenCV have wrappers with common interface that enables to switch easily
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Extractors of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch
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between different algorithms solving the same problem. This section is devoted to computing descriptors
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that are represented as vectors in a multidimensional space. All objects that implement ''vector''
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descriptor extractors inherit
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:func:`DescriptorExtractor` interface.
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that are represented as vectors in a multidimensional space. All objects that implement the ``vector``
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descriptor extractors inherit the
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:ref:`DescriptorExtractor` interface.
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.. index:: DescriptorExtractor
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@@ -15,7 +15,7 @@ DescriptorExtractor
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-------------------
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.. c:type:: DescriptorExtractor
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Abstract base class for computing descriptors for image keypoints. ::
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Abstract base class for computing descriptors for image keypoints ::
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class CV_EXPORTS DescriptorExtractor
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{
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@@ -40,12 +40,12 @@ Abstract base class for computing descriptors for image keypoints. ::
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};
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In this interface we assume a keypoint descriptor can be represented as a
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dense, fixed-dimensional vector of some basic type. Most descriptors used
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in practice follow this pattern, as it makes it very easy to compute
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distances between descriptors. Therefore we represent a collection of
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descriptors as a
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:func:`Mat` , where each row is one keypoint descriptor.
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In this interface, a keypoint descriptor can be represented as a
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dense, fixed-dimensional vector of a basic type. Most descriptors
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follow this pattern as it simplifies computing
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distances between descriptors. Therefore, a collection of
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descriptors is represented as
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:ref:`Mat` , where each row is a keypoint descriptor.
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.. index:: DescriptorExtractor::compute
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@@ -53,24 +53,23 @@ DescriptorExtractor::compute
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--------------------------------
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.. c:function:: void DescriptorExtractor::compute( const Mat\& image, vector<KeyPoint>\& keypoints, Mat\& descriptors ) const
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Compute the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
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Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
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:param image: The image.
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:param image: Image.
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:param keypoints: The keypoints. Keypoints for which a descriptor cannot be computed are removed.
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:param keypoints: Keypoints. Keypoints for which a descriptor cannot be computed are removed.
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:param descriptors: The descriptors. Row i is the descriptor for keypoint i.
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:param descriptors: Descriptors. Row i is the descriptor for keypoint i.
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.. c:function:: void DescriptorExtractor::compute( const vector<Mat>\& images, vector<vector<KeyPoint> >\& keypoints, vector<Mat>\& descriptors ) const
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* **images** The image set.
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:param images: Image set.
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* **keypoints** Input keypoints collection. keypoints[i] is keypoints
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detected in images[i]. Keypoints for which a descriptor
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can not be computed are removed.
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:param keypoints: Input keypoints collection. ``keypoints[i]`` are keypoints
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detected in ``images[i]`` . Keypoints for which a descriptor
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cannot be computed are removed.
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* **descriptors** Descriptor collection. descriptors[i] are descriptors computed for
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a set keypoints[i].
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:param descriptors: Descriptor collection. ``descriptors[i]`` are descriptors computed for a ``keypoints[i]`` set.
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.. index:: DescriptorExtractor::read
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@@ -78,9 +77,9 @@ DescriptorExtractor::read
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-----------------------------
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.. c:function:: void DescriptorExtractor::read( const FileNode\& fn )
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Read descriptor extractor object from file node.
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Reads the object of a descriptor extractor from a file node.
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:param fn: File node from which detector will be read.
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:param fn: File node from which the detector is read.
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.. index:: DescriptorExtractor::write
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@@ -88,30 +87,29 @@ DescriptorExtractor::write
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------------------------------
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.. c:function:: void DescriptorExtractor::write( FileStorage\& fs ) const
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Write descriptor extractor object to file storage.
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Writes the object of a descriptor extractor to a file storage.
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:param fs: File storage in which detector will be written.
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:param fs: File storage where the detector is written.
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.. index:: DescriptorExtractor::create
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DescriptorExtractor::create
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-------------------------------
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:func:`DescriptorExtractor`
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.. c:function:: Ptr<DescriptorExtractor> DescriptorExtractor::create( const string\& descriptorExtractorType )
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Descriptor extractor factory that creates of given type with default parameters (rather using default constructor).
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Creates a descriptor extractor of a given type with the default parameters (using the default constructor).??
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:param descriptorExtractorType: Descriptor extractor type.
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Now the following descriptor extractor types are supported:
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The current implementation supports the following types of a descriptor extractor:
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* ``"SIFT"`` -- :func:`SiftFeatureDetector`,
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* ``"SURF"`` -- :func:`SurfFeatureDetector`,
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* ``"BRIEF"`` -- :func:`BriefFeatureDetector` .
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* ``"SIFT"`` -- :func:`SiftFeatureDetector`
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* ``"SURF"`` -- :func:`SurfFeatureDetector`
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* ``"BRIEF"`` -- :func:`BriefFeatureDetector`
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Also combined format is supported: descriptor extractor adapter name ( ``"Opponent"`` --
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:func:`OpponentColorDescriptorExtractor` ) + descriptor extractor name (see above),
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e.g. ``"OpponentSIFT"`` , etc.
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A combined format is also supported: descriptor extractor adapter name ( ``"Opponent"`` --
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:ref:`OpponentColorDescriptorExtractor` ) + descriptor extractor name (see above),
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for example, ``"OpponentSIFT"`` .
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.. index:: SiftDescriptorExtractor
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@@ -119,8 +117,8 @@ SiftDescriptorExtractor
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-----------------------
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.. c:type:: SiftDescriptorExtractor
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Wrapping class for descriptors computing using
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:func:`SIFT` class. ::
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Wrapping class for descriptors computing using the
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:ref:`SIFT` class ::
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class SiftDescriptorExtractor : public DescriptorExtractor
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{
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@@ -149,8 +147,8 @@ SurfDescriptorExtractor
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-----------------------
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.. c:type:: SurfDescriptorExtractor
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Wrapping class for descriptors computing using
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:func:`SURF` class. ::
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Wrapping class for computing descriptors using the
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:ref:`SURF` class ::
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class SurfDescriptorExtractor : public DescriptorExtractor
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{
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@@ -173,8 +171,8 @@ CalonderDescriptorExtractor
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---------------------------
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.. c:type:: CalonderDescriptorExtractor
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Wrapping class for descriptors computing using
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:func:`RTreeClassifier` class. ::
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Wrapping class for computing descriptors using the
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:ref:`RTreeClassifier` class ::
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template<typename T>
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class CalonderDescriptorExtractor : public DescriptorExtractor
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@@ -199,10 +197,10 @@ OpponentColorDescriptorExtractor
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--------------------------------
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.. c:type:: OpponentColorDescriptorExtractor
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Adapts a descriptor extractor to compute descripors in Opponent Color Space
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(refer to van de Sande et al., CGIV 2008 "Color Descriptors for Object Category Recognition").
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Input RGB image is transformed in Opponent Color Space. Then unadapted descriptor extractor
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(set in constructor) computes descriptors on each of the three channel and concatenate
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Class adapting a descriptor extractor to compute descripors in the Opponent Color Space
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(refer to Van de Sande et al., CGIV 2008 *Color Descriptors for Object Category Recognition*).
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Input RGB image is transformed in the Opponent Color Space. Then, an unadapted descriptor extractor
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(set in the constructor) computes descriptors on each of three channels and concatenates
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them into a single color descriptor. ::
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class OpponentColorDescriptorExtractor : public DescriptorExtractor
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@@ -227,9 +225,9 @@ BriefDescriptorExtractor
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------------------------
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.. c:type:: BriefDescriptorExtractor
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Class for computing BRIEF descriptors described in paper of Calonder M., Lepetit V.,
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Strecha C., Fua P.: ''BRIEF: Binary Robust Independent Elementary Features.''
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11th European Conference on Computer Vision (ECCV), Heraklion, Crete. LNCS Springer, September 2010. ::
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Class for computing BRIEF descriptors described in a paper of Calonder M., Lepetit V.,
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Strecha C., Fua P. *BRIEF: Binary Robust Independent Elementary Features* ,
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11th European Conference on Computer Vision (ECCV), Heraklion, Crete. LNCS Springer, September 2010 ::
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class BriefDescriptorExtractor : public DescriptorExtractor
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{
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