OpenCV
3.0.0
Open Source Computer Vision
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the Fast Self-tuning Background Subtraction Algorithm from [130] More...
#include "saliencySpecializedClasses.hpp"
Public Member Functions | |
MotionSaliencyBinWangApr2014 () | |
virtual | ~MotionSaliencyBinWangApr2014 () |
int | getImageHeight () const |
int | getImageWidth () const |
bool | init () |
This function allows the correct initialization of all data structures that will be used by the algorithm. More... | |
void | setImageHeight (int val) |
void | setImagesize (int W, int H) |
This is a utility function that allows to set the correct size (taken from the input image) in the corresponding variables that will be used to size the data structures of the algorithm. More... | |
void | setImageWidth (int val) |
Public Member Functions inherited from cv::saliency::Saliency | |
virtual | ~Saliency () |
Destructor. More... | |
bool | computeSaliency (InputArray image, OutputArray saliencyMap) |
Compute the saliency. More... | |
String | getClassName () const |
Get the name of the specific saliency type. More... | |
Public Member Functions inherited from cv::Algorithm | |
Algorithm () | |
virtual | ~Algorithm () |
virtual void | clear () |
Clears the algorithm state. More... | |
virtual bool | empty () const |
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More... | |
virtual String | getDefaultName () const |
virtual void | read (const FileNode &fn) |
Reads algorithm parameters from a file storage. More... | |
virtual void | save (const String &filename) const |
virtual void | write (FileStorage &fs) const |
Stores algorithm parameters in a file storage. More... | |
Protected Member Functions | |
bool | computeSaliencyImpl (InputArray image, OutputArray saliencyMap) |
Performs all the operations and calls all internal functions necessary for the accomplishment of the Fast Self-tuning Background Subtraction Algorithm algorithm. More... | |
Additional Inherited Members | |
Static Public Member Functions inherited from cv::saliency::Saliency | |
static Ptr< Saliency > | create (const String &saliencyType) |
Create Saliency by saliency type. More... | |
Static Public Member Functions inherited from cv::Algorithm | |
template<typename _Tp > | |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
Loads algorithm from the file. More... | |
template<typename _Tp > | |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
Loads algorithm from a String. More... | |
template<typename _Tp > | |
static Ptr< _Tp > | read (const FileNode &fn) |
Reads algorithm from the file node. More... | |
Protected Attributes inherited from cv::saliency::Saliency | |
String | className |
the Fast Self-tuning Background Subtraction Algorithm from [130]
A Fast Self-tuning Background Subtraction Algorithm.
This background subtraction algorithm is inspired to the work of B. Wang and P. Dudek [2] [2] B. Wang and P. Dudek "A Fast Self-tuning Background Subtraction Algorithm", in proc of IEEE Workshop on Change Detection, 2014
cv::saliency::MotionSaliencyBinWangApr2014::MotionSaliencyBinWangApr2014 | ( | ) |
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Performs all the operations and calls all internal functions necessary for the accomplishment of the Fast Self-tuning Background Subtraction Algorithm algorithm.
image | input image. According to the needs of this specialized algorithm, the param image is a single Mat. |
saliencyMap | Saliency Map. Is a binarized map that, in accordance with the nature of the algorithm, highlights the moving objects or areas of change in the scene. The saliency map is given by a single Mat (one for each frame of an hypothetical video stream). |
Implements cv::saliency::MotionSaliency.
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bool cv::saliency::MotionSaliencyBinWangApr2014::init | ( | ) |
This function allows the correct initialization of all data structures that will be used by the algorithm.
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void cv::saliency::MotionSaliencyBinWangApr2014::setImagesize | ( | int | W, |
int | H | ||
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This is a utility function that allows to set the correct size (taken from the input image) in the corresponding variables that will be used to size the data structures of the algorithm.
W | width of input image |
H | height of input image |
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