Adding a .tex document for the dynamic feature detectors
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@ -299,46 +299,8 @@ protected:
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};
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\end{lstlisting}
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\cvclass{DynamicDetectorAdaptor}
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An adaptively adjusting detector that iteratively detects until the desired number
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of features are found.
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Adapters can easily be implemented for any detector through the creation of an Adjuster
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object.
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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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\begin{lstlisting}
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template<typename Adjuster>
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class DynamicDetectorAdaptor: public FeatureDetector {
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public:
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DynamicDetectorAdaptor(int min_features, int max_features, int max_iters,
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const Adjuster& a = Adjuster());
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...
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};
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//expected Adjuster interface
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class MyAdjuster {
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public:
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//this should call a FeatureDetector and populate keypoints
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//e.g. FASTFeatureDetector(thresh).detect(img,mask,keypoints)
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void detect(const Mat& img, const Mat& mask, std::vector<KeyPoint>& keypoints) const;
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//called if there are too few features detected, should adjust feature detector params
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//accordingly
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void tooFew(int min, int n_detected);
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//called if there are too many features detected, should adjust feature detector params
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//accordingly
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void tooMany(int max, int n_detected);
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//return whether or not the threshhold is beyond
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//a useful point
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bool good() const;
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\end{lstlisting}
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%dynamic detectors doc
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\input{features2d_dynamic_detectors}
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\cvCppFunc{createFeatureDetector}
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Feature detector factory that creates \cvCppCross{FeatureDetector} of given type with
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94
doc/features2d_dynamic_detectors.tex
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94
doc/features2d_dynamic_detectors.tex
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@ -0,0 +1,94 @@
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\cvclass{DynamicDetector}
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An adaptively adjusting detector that iteratively detects until the desired number
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of features are found.
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Adapters can easily be implemented for any detector through the creation of an Adjuster
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object.
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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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\begin{lstlisting}
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//sample usage:
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//will create a detector that attempts to find 100 - 110 FAST Keypoints, and will at most run
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//FAST feature detection 10 times until that number of keypoints are found
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Ptr<FeatureDetector> detector(new DynamicDetector (100, 110, 10,new FastAdjuster(20,true)));
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class CV_EXPORTS DynamicDetector: public FeatureDetector {
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public:
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/**min_features the minimum desired features
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* max_features the maximum desired number of features
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* max_iters the maximum number of times to try to adjust the feature detector params
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* for the FastAdjuster this can be high, but with Star or Surf this can get time consuming
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* a an AdjusterAdapter that will do the detection and parameter adjustment
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*/
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DynamicDetector(int min_features, int max_features, int max_iters,
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const Ptr<AdjusterAdapter>& a);
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...
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};
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\end{lstlisting}
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\cvclass{AdjusterAdapter}
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A feature detector parameter adjuster interface, this is used by the \cvCppCross{DynamicDetector}
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and is a wrapper for \cvCppCross{FeatureDetecto}r that allow them to be adjusted after a detection.
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See \cvCppCross{FastAdjuster}, \cvCppCross{StarAdjuster}, \cvCppCross{SurfAdjuster} for concrete implementations.
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\begin{lstlisting}
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class AdjusterAdapter: public FeatureDetector {
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public:
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/** pure virtual interface
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*/
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virtual ~AdjusterAdapter() {
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}
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/** too few features were detected so, adjust the detector params accordingly
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* \param min the minimum number of desired features
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* \param n_detected the number previously detected
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*/
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virtual void tooFew(int min, int n_detected) = 0;
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/** too many features were detected so, adjust the detector params accordingly
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* \param max the maximum number of desired features
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* \param n_detected the number previously detected
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*/
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virtual void tooMany(int max, int n_detected) = 0;
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/** are params maxed out or still valid?
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* \return false if the parameters can't be adjusted any more
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*/
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virtual bool good() const = 0;
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};
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\end{lstlisting}
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\cvclass{FastAdjuster}
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An \cvCppCross{AdjusterAdapter} for the \cvCppCross{FastFeatureDetector}. This will basically decrement or increment the
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threshhold by 1
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\begin{lstlisting}
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class FastAdjuster FastAdjuster: public AdjusterAdapter {
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public:
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/**\param init_thresh the initial threshhold to start with, default = 20
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* \param nonmax whether to use non max or not for fast feature detection
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*/
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FastAdjuster(int init_thresh = 20, bool nonmax = true);
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...
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};
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\end{lstlisting}
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\cvclass{StarAdjuster}
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An \cvCppCross{AdjusterAdapter} for the \cvCppCross{StarFeatureDetector}. This adjusts the responseThreshhold of
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StarFeatureDetector.
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\begin{lstlisting}
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class StarAdjuster: public AdjusterAdapter {
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StarAdjuster(double initial_thresh = 30.0);
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...
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};
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\end{lstlisting}
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\cvclass{SurfAdjuster}
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An \cvCppCross{AdjusterAdapter} for the \cvCppCross{SurfFeatureDetector}. This adjusts the responseThreshhold of
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SurfFeatureDetector.
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\begin{lstlisting}
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class SurfAdjuster: public SurfAdjuster {
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SurfAdjuster();
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...
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};
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\end{lstlisting}
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