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Purpose: updated the feature2d chapter
This commit is contained in:
Elena Fedotova
parent
d3a159d3cc
commit
916ec81d09
@ -3,10 +3,10 @@ Common Interfaces of Feature Detectors
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.. highlight:: cpp
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Feature detectors in OpenCV have wrappers with common interface that enables to switch easily
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Feature detectors 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. All objects that implement keypoint detectors
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inherit
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:func:`FeatureDetector` interface.
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inherit the
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:ref:`FeatureDetector` interface.
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.. index:: KeyPoint
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@ -16,7 +16,7 @@ KeyPoint
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--------
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.. c:type:: KeyPoint
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Data structure for salient point detectors. ::
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Data structure for salient point detectors ::
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class KeyPoint
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{
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@ -39,7 +39,7 @@ Data structure for salient point detectors. ::
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std::vector<Point2f>& points2f,
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const std::vector<int>& keypointIndexes=std::vector<int>());
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// converts vector of points to the vector of keypoints, where each
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// keypoint is assigned the same size and the same orientation
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// keypoint is assigned to the same size and the same orientation
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static void convert(const std::vector<Point2f>& points2f,
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std::vector<KeyPoint>& keypoints,
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float size=1, float response=1, int octave=0,
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@ -47,14 +47,14 @@ Data structure for salient point detectors. ::
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// computes overlap for pair of keypoints;
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// overlap is a ratio between area of keypoint regions intersection and
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// area of keypoint regions union (now keypoint region is circle)
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// area of keypoint regions union (now keypoint region is a circle)
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static float overlap(const KeyPoint& kp1, const KeyPoint& kp2);
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Point2f pt; // coordinates of the keypoints
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float size; // diameter of the meaningfull keypoint neighborhood
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float size; // diameter of the meaningful keypoint neighborhood
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float angle; // computed orientation of the keypoint (-1 if not applicable)
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float response; // the response by which the most strong keypoints
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// have been selected. Can be used for the further sorting
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// have been selected. Can be used for further sorting
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// or subsampling
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int octave; // octave (pyramid layer) from which the keypoint has been extracted
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int class_id; // object class (if the keypoints need to be clustered by
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@ -77,7 +77,7 @@ FeatureDetector
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---------------
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.. c:type:: FeatureDetector
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Abstract base class for 2D image feature detectors. ::
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Abstract base class for 2D image feature detectors ::
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class CV_EXPORTS FeatureDetector
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{
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@ -107,23 +107,21 @@ FeatureDetector::detect
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---------------------------
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.. c:function:: void FeatureDetector::detect( const Mat\& image, vector<KeyPoint>\& keypoints, const Mat\& mask=Mat() ) const
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Detect keypoints in an image (first variant) or image set (second variant).
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Detects keypoints 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 detected keypoints.
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:param keypoints: Detected keypoints.
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:param mask: Mask specifying where to look for keypoints (optional). Must be a char matrix
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with non-zero values in the region of interest.
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:param mask: Mask specifying where to look for keypoints (optional). It must be a char matrix with non-zero values in the region of interest.
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.. c:function:: void FeatureDetector::detect( const vector<Mat>\& images, vector<vector<KeyPoint> >\& keypoints, const vector<Mat>\& masks=vector<Mat>() ) const
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* **images** Images set.
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:param images: Image set.
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* **keypoints** Collection of keypoints detected in an input images. keypoints[i] is a set of keypoints detected in an images[i].
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:param keypoints: Collection of keypoints detected in input images. ``keypoints[i]`` is a set of keypoints detected in ``images[i]`` .
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* **masks** Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].
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Each element of ``masks`` vector must be a char matrix with non-zero values in the region of interest.
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:param masks: Masks for each input image specifying where to look for keypoints (optional). ``masks[i]`` is a mask for ``images[i]`` . Each element of the ``masks`` vector must be a char matrix with non-zero values in the region of interest.
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.. index:: FeatureDetector::read
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@ -131,9 +129,9 @@ FeatureDetector::read
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-------------------------
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.. c:function:: void FeatureDetector::read( const FileNode\& fn )
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Read feature detector object from file node.
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Reads a feature detector object 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:: FeatureDetector::write
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@ -141,35 +139,34 @@ FeatureDetector::write
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--------------------------
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.. c:function:: void FeatureDetector::write( FileStorage\& fs ) const
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Write feature detector object to file storage.
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Writes a feature detector object 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:: FeatureDetector::create
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FeatureDetector::create
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---------------------------
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:func:`FeatureDetector`
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.. c:function:: Ptr<FeatureDetector> FeatureDetector::create( const string\& detectorType )
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Feature detector factory that creates of given type with default parameters (rather using default constructor).
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Creates a feature detector of a given type with the default parameters (or using the default constructor).??
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:param detectorType: Feature detector type.
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Now the following detector types are supported:
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\ ``"FAST"`` --
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:func:`FastFeatureDetector`,\ ``"STAR"`` --
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:func:`StarFeatureDetector`,\ ``"SIFT"`` --
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:func:`SiftFeatureDetector`,\ ``"SURF"`` --
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:func:`SurfFeatureDetector`,\ ``"MSER"`` --
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:func:`MserFeatureDetector`,\ ``"GFTT"`` --
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:func:`GfttFeatureDetector`,\ ``"HARRIS"`` --
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:func:`HarrisFeatureDetector` .
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\
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Also combined format is supported: feature detector adapter name ( ``"Grid"`` --
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:func:`GridAdaptedFeatureDetector`,``"Pyramid"`` --
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The following detector types are supported:
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* ``"FAST"`` -- :func:`FastFeatureDetector`
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* ``"STAR"`` -- :func:`StarFeatureDetector`
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* ``"SIFT"`` -- :func:`SiftFeatureDetector`
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* ``"SURF"`` -- :func:`SurfFeatureDetector`
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* ``"MSER"`` -- :func:`MserFeatureDetector`
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* ``"GFTT"`` -- :func:`GfttFeatureDetector`
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* ``"HARRIS"`` -- :func:`HarrisFeatureDetector`
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Also a combined format is supported: feature detector adapter name ( ``"Grid"`` --
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:func:`GridAdaptedFeatureDetector`, ``"Pyramid"`` --
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:func:`PyramidAdaptedFeatureDetector` ) + feature detector name (see above),
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e.g. ``"GridFAST"``,``"PyramidSTAR"`` , etc.
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for example, ``"GridFAST"``, ``"PyramidSTAR"`` .
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.. index:: FastFeatureDetector
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@ -179,8 +176,8 @@ FastFeatureDetector
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-------------------
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.. c:type:: FastFeatureDetector
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Wrapping class for feature detection using
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:func:`FAST` method. ::
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Wrapping class for feature detection using the
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:func:`FAST` method ::
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class FastFeatureDetector : public FeatureDetector
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{
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@ -201,8 +198,8 @@ GoodFeaturesToTrackDetector
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---------------------------
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.. c:type:: GoodFeaturesToTrackDetector
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Wrapping class for feature detection using
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:func:`goodFeaturesToTrack` function. ::
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Wrapping class for feature detection using the
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:func:`goodFeaturesToTrack` function ::
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class GoodFeaturesToTrackDetector : public FeatureDetector
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{
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@ -244,8 +241,8 @@ MserFeatureDetector
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-------------------
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.. c:type:: MserFeatureDetector
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Wrapping class for feature detection using
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:func:`MSER` class. ::
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Wrapping class for feature detection using the
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:func:`MSER` class ::
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class MserFeatureDetector : public FeatureDetector
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{
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@ -270,8 +267,8 @@ StarFeatureDetector
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-------------------
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.. c:type:: StarFeatureDetector
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Wrapping class for feature detection using
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:func:`StarDetector` class. ::
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Wrapping class for feature detection using the
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:func:`StarDetector` class ::
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class StarFeatureDetector : public FeatureDetector
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{
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@ -294,8 +291,8 @@ SiftFeatureDetector
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-------------------
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.. c:type:: SiftFeatureDetector
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Wrapping class for feature detection using
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:func:`SIFT` class. ::
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Wrapping class for feature detection using the
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:func:`SIFT` class ::
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class SiftFeatureDetector : public FeatureDetector
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{
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@ -323,8 +320,8 @@ SurfFeatureDetector
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-------------------
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.. c:type:: SurfFeatureDetector
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Wrapping class for feature detection using
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:func:`SURF` class. ::
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Wrapping class for feature detection using the
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:func:`SURF` class ::
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class SurfFeatureDetector : public FeatureDetector
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{
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@ -346,7 +343,7 @@ GridAdaptedFeatureDetector
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--------------------------
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.. c:type:: GridAdaptedFeatureDetector
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Adapts a detector to partition the source image into a grid and detect points in each cell. ::
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Class adapting a detector to partition the source image into a grid and detect points in each cell ::
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class GridAdaptedFeatureDetector : public FeatureDetector
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{
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@ -354,8 +351,8 @@ Adapts a detector to partition the source image into a grid and detect points in
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/*
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* detector Detector that will be adapted.
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* maxTotalKeypoints Maximum count of keypoints detected on the image.
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* Only the strongest keypoints will be keeped.
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* gridRows Grid rows count.
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* Only the strongest keypoints will be kept.
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* gridRows Grid row count.
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* gridCols Grid column count.
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*/
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GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector,
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@ -376,7 +373,7 @@ PyramidAdaptedFeatureDetector
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-----------------------------
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.. c:type:: PyramidAdaptedFeatureDetector
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Adapts a detector to detect points over multiple levels of a Gaussian pyramid. Useful for detectors that are not inherently scaled. ::
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Class adapting a detector to detect points over multiple levels of a Gaussian pyramid. Consider using this class for detectors that are not inherently scaled. ::
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class PyramidAdaptedFeatureDetector : public FeatureDetector
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{
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@ -397,7 +394,7 @@ DynamicAdaptedFeatureDetector
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.. c:type:: DynamicAdaptedFeatureDetector
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An adaptively adjusting detector that iteratively detects until the desired number of features are found. ::
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Adaptively adjusting detector that iteratively detects features until the desired number is found ::
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class DynamicAdaptedFeatureDetector: public FeatureDetector
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{
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@ -408,24 +405,24 @@ DynamicAdaptedFeatureDetector
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};
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If the detector is persisted, it will "remember" the parameters
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used on the last detection. In this way, the detector may be used for consistent numbers
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of keypoints in a sets of images that are temporally related such as video streams or
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used for the last detection. In this case, the detector may be used for consistent numbers
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of keypoints in a set of temporally related images, such as video streams or
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panorama series.
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The DynamicAdaptedFeatureDetector uses another detector such as FAST or SURF to do the dirty work,
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with the help of an AdjusterAdapter.
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After a detection, and an unsatisfactory number of features are detected,
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the AdjusterAdapter will adjust the detection parameters so that the next detection will
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result in more or less features. This is repeated until either the number of desired features are found
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``DynamicAdaptedFeatureDetector`` uses another detector such as FAST or SURF to do the dirty work,
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with the help of ``AdjusterAdapter`` .
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If the detected number of features is not enough,??
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``AdjusterAdapter`` adjusts the detection parameters so that the next detection
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results in more or less features. This is repeated until either the number of desired features are found
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or the parameters are maxed out.
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Adapters can easily be implemented for any detector via the
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AdjusterAdapter interface.
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Adapters can be easily implemented for any detector via the
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``AdjusterAdapter`` interface.
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Beware that this is not thread safe - as the adjustment of parameters breaks the const
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of the detection routine...
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Beware that this is not thread-safe since the adjustment of parameters breaks the const??
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of the detection routine.
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Here is a sample of how to create a DynamicAdaptedFeatureDetector. ::
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Here is a sample of how to create ``DynamicAdaptedFeatureDetector`` : ::
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//sample usage:
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//will create a detector that attempts to find
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@ -436,23 +433,22 @@ Here is a sample of how to create a DynamicAdaptedFeatureDetector. ::
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new FastAdjuster(20,true)));
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.. index:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
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DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
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----------------------------------------------------------------
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.. c:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>\& adjaster, int min_features, int max_features, int max_iters )
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DynamicAdaptedFeatureDetector constructor.
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``DynamicAdaptedFeatureDetector`` constructor
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:param adjaster: An :func:`AdjusterAdapter` that will do the detection and parameter
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adjustment
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:param adjaster: :func:`AdjusterAdapter` that detects features and adjusts parameters.??parameter formatting is broken here
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:param min_features: This minimum desired number features.
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:param min_features: Minimum desired number features.
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:param max_features: The maximum desired number of features.
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:param max_features: Maximum desired number of features.
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:param max_iters: The maximum number of times to try to adjust the feature detector parameters. For the :func:`FastAdjuster` this number can be high,
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but with Star or Surf, many iterations can get time consuming. At each iteration the detector is rerun, so keep this in mind when choosing this value.
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:param max_iters: Maximum number of times to try adjusting the feature detector parameters. For :func:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf`` , many iterations can be time-comsuming. At each iteration the detector is rerun.
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.. index:: AdjusterAdapter
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@ -461,7 +457,7 @@ AdjusterAdapter
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.. c:type:: AdjusterAdapter
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A feature detector parameter adjuster interface, this is used by the :func:`DynamicAdaptedFeatureDetector` and is a wrapper for :func:`FeatureDetecto` r that allow them to be adjusted after a detection. ::
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Class providing an interface for adjusting parameters of a feature detector. This interface is used by :func:`DynamicAdaptedFeatureDetector` . It is a wrapper for :func:`FeatureDetector` that enables adjusting parameters after detection.?? ::
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class AdjusterAdapter: public FeatureDetector
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{
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@ -474,7 +470,9 @@ AdjusterAdapter
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See
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:func:`FastAdjuster`,:func:`StarAdjuster`,:func:`SurfAdjuster` for concrete implementations.
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:func:`FastAdjuster`,
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:func:`StarAdjuster`,
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:func:`SurfAdjuster` for concrete implementations.
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.. index:: AdjusterAdapter::tooFew
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@ -483,13 +481,13 @@ AdjusterAdapter::tooFew
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---------------------------
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.. c:function:: virtual void tooFew(int min, int n_detected) = 0
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Too few features were detected so, adjust the detector parameters accordingly - so that the next detection detects more features.
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Adjusts the detector parameters to detect more features.
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:param min: This minimum desired number features.
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:param min: Minimum desired number of features.
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:param n_detected: The actual number detected last run.
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:param n_detected: Number of features detected during the latest run.
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An example implementation of this is ::
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Example: ::
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void FastAdjuster::tooFew(int min, int n_detected)
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{
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@ -503,13 +501,13 @@ AdjusterAdapter::tooMany
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----------------------------
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.. c:function:: virtual void tooMany(int max, int n_detected) = 0
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Too many features were detected so, adjust the detector parameters accordingly - so that the next detection detects less features.
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Adjusts the detector parameters detect less features.
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:param max: This maximum desired number features.
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:param max: Maximum desired number of features.
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:param n_detected: The actual number detected last run.
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:param n_detected: Number of features detected during the latest run.
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An example implementation of this is ::
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Example: ::
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void FastAdjuster::tooMany(int min, int n_detected)
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{
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@ -523,7 +521,9 @@ AdjusterAdapter::good
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-------------------------
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.. c:function:: virtual bool good() const = 0
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Are params maxed out or still valid? Returns false if the parameters can't be adjusted any more. An example implementation of this is ::
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Returns false if the detector parameters cannot be adjusted any more.
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Example: ::
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bool FastAdjuster::good() const
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{
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@ -538,7 +538,7 @@ FastAdjuster
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.. c:type:: FastAdjuster
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:func:`AdjusterAdapter` for the :func:`FastFeatureDetector`. This will basically decrement or increment the threshhold by 1 ::
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:func:`AdjusterAdapter` for :func:`FastFeatureDetector`. This class decrements or increments the threshhold by 1.?? ::
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class FastAdjuster FastAdjuster: public AdjusterAdapter
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{
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@ -554,7 +554,7 @@ StarAdjuster
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.. c:type:: StarAdjuster
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:func:`AdjusterAdapter` for the :func:`StarFeatureDetector` . This adjusts the responseThreshhold of StarFeatureDetector. ::
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:func:`AdjusterAdapter` for :func:`StarFeatureDetector` . This class adjusts the ``responseThreshhold`` of ``StarFeatureDetector`` . ::
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class StarAdjuster: public AdjusterAdapter
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{
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@ -569,7 +569,7 @@ SurfAdjuster
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.. c:type:: SurfAdjuster
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:func:`AdjusterAdapter` for the :func:`SurfFeatureDetector` . This adjusts the hessianThreshold of SurfFeatureDetector. ::
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:func:`AdjusterAdapter` for :func:`SurfFeatureDetector` . This class adjusts the ``hessianThreshold`` of ``SurfFeatureDetector`` . ::
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class SurfAdjuster: public SurfAdjuster
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{
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@ -583,7 +583,7 @@ FeatureDetector
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---------------
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.. c:type:: FeatureDetector
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Abstract base class for 2D image feature detectors. ::
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Abstract base class for 2D image feature detectors ::
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class CV_EXPORTS FeatureDetector
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{
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@ -613,22 +613,22 @@ FeatureDetector::detect
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---------------------------
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.. c:function:: void FeatureDetector::detect( const Mat\& image, vector<KeyPoint>\& keypoints, const Mat\& mask=Mat() ) const
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Detect keypoints in an image (first variant) or image set (second variant).
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Detects keypoints 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 detected keypoints.
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:param keypoints: Detected keypoints.
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:param mask: Mask specifying where to look for keypoints (optional). Must be a char matrix
|
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:param mask: Mask specifying where to look for keypoints (optional). It must be a char matrix
|
||||
with non-zero values in the region of interest.
|
||||
|
||||
.. c:function:: void FeatureDetector::detect( const vector<Mat>\& images, vector<vector<KeyPoint> >\& keypoints, const vector<Mat>\& masks=vector<Mat>() ) const
|
||||
|
||||
* **images** Images set.
|
||||
:param images: Image set.
|
||||
|
||||
* **keypoints** Collection of keypoints detected in an input images. keypoints[i] is a set of keypoints detected in an images[i].
|
||||
:param keypoints: Collection of keypoints detected in an input image. ``keypoints[i]`` is a set of keypoints detected in ``images[i]`` .
|
||||
|
||||
* **masks** Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].
|
||||
:param masks: Masks for each input image specifying where to look for keypoints (optional). ``masks[i]`` is a mask for ``images[i]`` .
|
||||
Each element of ``masks`` vector must be a char matrix with non-zero values in the region of interest.
|
||||
|
||||
.. index:: FeatureDetector::read
|
||||
@ -637,9 +637,9 @@ FeatureDetector::read
|
||||
-------------------------
|
||||
.. c:function:: void FeatureDetector::read( const FileNode\& fn )
|
||||
|
||||
Read feature detector object from file node.
|
||||
Reads a feature detector object from a file node.
|
||||
|
||||
:param fn: File node from which detector will be read.
|
||||
:param fn: File node from which the detector is read.
|
||||
|
||||
.. index:: FeatureDetector::write
|
||||
|
||||
@ -647,34 +647,33 @@ FeatureDetector::write
|
||||
--------------------------
|
||||
.. c:function:: void FeatureDetector::write( FileStorage\& fs ) const
|
||||
|
||||
Write feature detector object to file storage.
|
||||
Writes a feature detector object to a file storage.
|
||||
|
||||
:param fs: File storage in which detector will be written.
|
||||
:param fs: File storage where the detector is written.
|
||||
|
||||
.. index:: FeatureDetector::create
|
||||
|
||||
FeatureDetector::create
|
||||
---------------------------
|
||||
:func:`FeatureDetector`
|
||||
.. c:function:: Ptr<FeatureDetector> FeatureDetector::create( const string\& detectorType )
|
||||
.. c:function:: Ptr<FeatureDetector> FeatureDetector::create( const string\& detectorType )??
|
||||
|
||||
Feature detector factory that creates of given type with default parameters (rather using default constructor).
|
||||
Creates a feature detector of a given type with the default parameters (or using the default constructor).??
|
||||
|
||||
:param detectorType: Feature detector type.
|
||||
|
||||
Now the following detector types are supported:
|
||||
* ``"FAST"`` -- :func:`FastFeatureDetector`,
|
||||
* ``"STAR"`` -- :func:`StarFeatureDetector`,
|
||||
* ``"SIFT"`` -- :func:`SiftFeatureDetector`,
|
||||
* ``"SURF"`` -- :func:`SurfFeatureDetector`,
|
||||
* ``"MSER"`` -- :func:`MserFeatureDetector`,
|
||||
* ``"GFTT"`` -- :func:`GfttFeatureDetector`,
|
||||
* ``"HARRIS"`` -- :func:`HarrisFeatureDetector` .
|
||||
* ``"FAST"`` -- :func:`FastFeatureDetector`
|
||||
* ``"STAR"`` -- :func:`StarFeatureDetector`
|
||||
* ``"SIFT"`` -- :func:`SiftFeatureDetector`
|
||||
* ``"SURF"`` -- :func:`SurfFeatureDetector`
|
||||
* ``"MSER"`` -- :func:`MserFeatureDetector`
|
||||
* ``"GFTT"`` -- :func:`GfttFeatureDetector`
|
||||
* ``"HARRIS"`` -- :func:`HarrisFeatureDetector`
|
||||
|
||||
Also combined format is supported: feature detector adapter name ( ``"Grid"`` --
|
||||
:func:`GridAdaptedFeatureDetector`,``"Pyramid"`` --
|
||||
A combined format is also supported: feature detector adapter name ( ``"Grid"`` --
|
||||
:func:`GridAdaptedFeatureDetector` , ``"Pyramid"`` --
|
||||
:func:`PyramidAdaptedFeatureDetector` ) + feature detector name (see above),
|
||||
e.g. ``"GridFAST"``,``"PyramidSTAR"`` , etc.
|
||||
for example, ``"GridFAST"`` , ``"PyramidSTAR"`` .
|
||||
|
||||
.. index:: FastFeatureDetector
|
||||
|
||||
@ -682,8 +681,8 @@ FastFeatureDetector
|
||||
-------------------
|
||||
.. c:type:: FastFeatureDetector
|
||||
|
||||
Wrapping class for feature detection using
|
||||
:func:`FAST` method. ::
|
||||
Wrapping class for feature detection using the
|
||||
:func:`FAST` method ::
|
||||
|
||||
class FastFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -702,7 +701,7 @@ GoodFeaturesToTrackDetector
|
||||
---------------------------
|
||||
.. c:type:: GoodFeaturesToTrackDetector
|
||||
|
||||
Wrapping class for feature detection using :func:`goodFeaturesToTrack` function. ::
|
||||
Wrapping class for feature detection using the :func:`goodFeaturesToTrack` function ::
|
||||
|
||||
class GoodFeaturesToTrackDetector : public FeatureDetector
|
||||
{
|
||||
@ -742,7 +741,7 @@ MserFeatureDetector
|
||||
-------------------
|
||||
.. c:type:: MserFeatureDetector
|
||||
|
||||
Wrapping class for feature detection using :func:`MSER` class. ::
|
||||
Wrapping class for feature detection using the :func:`MSER` class ::
|
||||
|
||||
class MserFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -765,7 +764,7 @@ StarFeatureDetector
|
||||
-------------------
|
||||
.. c:type:: StarFeatureDetector
|
||||
|
||||
Wrapping class for feature detection using :func:`StarDetector` class. ::
|
||||
Wrapping class for feature detection using the :func:`StarDetector` class ::
|
||||
|
||||
class StarFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -786,7 +785,7 @@ SiftFeatureDetector
|
||||
-------------------
|
||||
.. c:type:: SiftFeatureDetector
|
||||
|
||||
Wrapping class for feature detection using :func:`SIFT` class. ::
|
||||
Wrapping class for feature detection using the :func:`SIFT` class ::
|
||||
|
||||
class SiftFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -812,7 +811,7 @@ SurfFeatureDetector
|
||||
-------------------
|
||||
.. c:type:: SurfFeatureDetector
|
||||
|
||||
Wrapping class for feature detection using :func:`SURF` class. ::
|
||||
Wrapping class for feature detection using the :func:`SURF` class ::
|
||||
|
||||
class SurfFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -832,7 +831,7 @@ GridAdaptedFeatureDetector
|
||||
--------------------------
|
||||
.. c:type:: GridAdaptedFeatureDetector
|
||||
|
||||
Adapts a detector to partition the source image into a grid and detect points in each cell. ::
|
||||
Class adapting a detector to partition the source image into a grid and detect points in each cell ::
|
||||
|
||||
class GridAdaptedFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -840,8 +839,8 @@ GridAdaptedFeatureDetector
|
||||
/*
|
||||
* detector Detector that will be adapted.
|
||||
* maxTotalKeypoints Maximum count of keypoints detected on the image.
|
||||
* Only the strongest keypoints will be keeped.
|
||||
* gridRows Grid rows count.
|
||||
* Only the strongest keypoints are kept.
|
||||
* gridRows Grid row count.
|
||||
* gridCols Grid column count.
|
||||
*/
|
||||
GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector,
|
||||
@ -860,7 +859,7 @@ PyramidAdaptedFeatureDetector
|
||||
-----------------------------
|
||||
.. c:type:: PyramidAdaptedFeatureDetector
|
||||
|
||||
Adapts a detector to detect points over multiple levels of a Gaussian pyramid. Useful for detectors that are not inherently scaled. ::
|
||||
Class adapting a detector to detect points over multiple levels of a Gaussian pyramid. Consider using this class for detectors that are not inherently scaled. ::
|
||||
|
||||
class PyramidAdaptedFeatureDetector : public FeatureDetector
|
||||
{
|
||||
@ -881,7 +880,7 @@ DynamicAdaptedFeatureDetector
|
||||
|
||||
.. c:type:: DynamicAdaptedFeatureDetector
|
||||
|
||||
An adaptively adjusting detector that iteratively detects until the desired number of features are found. ::
|
||||
Adaptively adjusting detector that iteratively detects features until the desired number is found. ::
|
||||
|
||||
class DynamicAdaptedFeatureDetector: public FeatureDetector
|
||||
{
|
||||
@ -892,25 +891,25 @@ DynamicAdaptedFeatureDetector
|
||||
};
|
||||
|
||||
|
||||
If the detector is persisted, it will "remember" the parameters
|
||||
used on the last detection. In this way, the detector may be used for consistent numbers
|
||||
of keypoints in a sets of images that are temporally related such as video streams or
|
||||
If the detector is persisted, it "remembers" the parameters
|
||||
used on the last detection. In this case, the detector may be used for consistent numbers
|
||||
of keypoints in a set of images that are temporally related, such as video streams or
|
||||
panorama series.
|
||||
|
||||
The DynamicAdaptedFeatureDetector uses another detector such as FAST or SURF to do the dirty work,
|
||||
with the help of an AdjusterAdapter.
|
||||
After a detection, and an unsatisfactory number of features are detected,
|
||||
the AdjusterAdapter will adjust the detection parameters so that the next detection will
|
||||
result in more or less features. This is repeated until either the number of desired features are found
|
||||
``DynamicAdaptedFeatureDetector`` uses another detector such as FAST or SURF to do the dirty work,
|
||||
with the help of ``AdjusterAdapter`` .
|
||||
If the number of detected features is not enough,
|
||||
``AdjusterAdapter`` adjusts the detection parameters so that the next detection
|
||||
results in a bigger or smaller number of features. This is repeated until either the number of desired features are found
|
||||
or the parameters are maxed out.
|
||||
|
||||
Adapters can easily be implemented for any detector via the
|
||||
AdjusterAdapter interface.
|
||||
``AdjusterAdapter`` interface.
|
||||
|
||||
Beware that this is not thread safe - as the adjustment of parameters breaks the const
|
||||
of the detection routine...
|
||||
Beware that this is not thread safe as the adjustment of parameters breaks the const??
|
||||
of the detection routine.
|
||||
|
||||
Here is a sample of how to create a DynamicAdaptedFeatureDetector. ::
|
||||
Example of creating ``DynamicAdaptedFeatureDetector``: ::
|
||||
|
||||
//sample usage:
|
||||
//will create a detector that attempts to find
|
||||
@ -926,17 +925,15 @@ DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
|
||||
----------------------------------------------------------------
|
||||
.. c:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>\& adjaster, int min_features, int max_features, int max_iters )
|
||||
|
||||
DynamicAdaptedFeatureDetector constructor.
|
||||
Provides the ``DynamicAdaptedFeatureDetector`` constructor.??
|
||||
|
||||
:param adjaster: An :func:`AdjusterAdapter` that will do the detection and parameter
|
||||
adjustment
|
||||
:param adjaster: :func:`AdjusterAdapter` that detects features and adjusts parameters.??formatting issue again
|
||||
|
||||
:param min_features: This minimum desired number features.
|
||||
:param min_features: Minimum desired number features.
|
||||
|
||||
:param max_features: The maximum desired number of features.
|
||||
:param max_features: Maximum desired number of features.
|
||||
|
||||
:param max_iters: The maximum number of times to try to adjust the feature detector parameters. For the :func:`FastAdjuster` this number can be high,
|
||||
but with Star or Surf, many iterations can get time consuming. At each iteration the detector is rerun, so keep this in mind when choosing this value.
|
||||
:param max_iters: Maximum number of times to try adjusting the feature detector parameters. For :func:`FastAdjuster` , this number can be high, but with ``Star`` or ``Surf`` , many iterations can be time-consuming. At each iteration the detector is rerun.
|
||||
|
||||
.. index:: AdjusterAdapter
|
||||
|
||||
@ -945,7 +942,7 @@ AdjusterAdapter
|
||||
|
||||
.. c:type:: AdjusterAdapter
|
||||
|
||||
A feature detector parameter adjuster interface, this is used by the :func:`DynamicAdaptedFeatureDetector` and is a wrapper for :func:`FeatureDetecto` r that allow them to be adjusted after a detection. ::
|
||||
Class providing an interface for adjusting parameters of a feature detector. This interface is used by :func:`DynamicAdaptedFeatureDetector` . It is a wrapper for :func:`FeatureDetector` that enables adjusting parameters after detection. ::
|
||||
|
||||
class AdjusterAdapter: public FeatureDetector
|
||||
{
|
||||
@ -957,7 +954,9 @@ AdjusterAdapter
|
||||
};
|
||||
|
||||
See
|
||||
:func:`FastAdjuster`,:func:`StarAdjuster`,:func:`SurfAdjuster` for concrete implementations.
|
||||
:func:`FastAdjuster`,
|
||||
:func:`StarAdjuster`,
|
||||
:func:`SurfAdjuster` for concrete implementations.
|
||||
|
||||
.. index:: AdjusterAdapter::tooFew
|
||||
|
||||
@ -965,13 +964,13 @@ AdjusterAdapter::tooFew
|
||||
---------------------------
|
||||
.. c:function:: virtual void tooFew(int min, int n_detected) = 0
|
||||
|
||||
Too few features were detected so, adjust the detector parameters accordingly - so that the next detection detects more features.
|
||||
Adjusts the detector parameters to detect more features.
|
||||
|
||||
:param min: This minimum desired number features.
|
||||
:param min: Minimum desired number of features.
|
||||
|
||||
:param n_detected: The actual number detected last run.
|
||||
:param n_detected: Number of features detected during the latest run.
|
||||
|
||||
An example implementation of this is ::
|
||||
Example: ::
|
||||
|
||||
void FastAdjuster::tooFew(int min, int n_detected)
|
||||
{
|
||||
|
||||
Loading…
Reference in New Issue
Block a user