the Fast Self-tuning Background Subtraction Algorithm from [293]
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#include <opencv2/saliency/saliencySpecializedClasses.hpp>
the Fast Self-tuning Background Subtraction Algorithm from [293]
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
◆ MotionSaliencyBinWangApr2014()
| cv::saliency::MotionSaliencyBinWangApr2014::MotionSaliencyBinWangApr2014 |
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◆ ~MotionSaliencyBinWangApr2014()
| virtual cv::saliency::MotionSaliencyBinWangApr2014::~MotionSaliencyBinWangApr2014 |
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virtual |
◆ computeSaliency()
| bool cv::saliency::MotionSaliencyBinWangApr2014::computeSaliency |
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InputArray | image, |
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OutputArray | saliencyMap ) |
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| cv.saliency.MotionSaliencyBinWangApr2014.computeSaliency( | image[, saliencyMap] | ) -> | retval, saliencyMap |
◆ computeSaliencyImpl()
| bool cv::saliency::MotionSaliencyBinWangApr2014::computeSaliencyImpl |
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InputArray | image, |
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OutputArray | saliencyMap ) |
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protectedvirtual |
Performs all the operations and calls all internal functions necessary for the accomplishment of the Fast Self-tuning Background Subtraction Algorithm algorithm.
- Parameters
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| 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.
◆ create()
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| cv.saliency.MotionSaliencyBinWangApr2014.create( | | ) -> | retval |
| cv.saliency.MotionSaliencyBinWangApr2014_create( | | ) -> | retval |
◆ getImageHeight()
| int cv::saliency::MotionSaliencyBinWangApr2014::getImageHeight |
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const |
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| cv.saliency.MotionSaliencyBinWangApr2014.getImageHeight( | | ) -> | retval |
◆ getImageWidth()
| int cv::saliency::MotionSaliencyBinWangApr2014::getImageWidth |
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const |
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| cv.saliency.MotionSaliencyBinWangApr2014.getImageWidth( | | ) -> | retval |
◆ init()
| bool cv::saliency::MotionSaliencyBinWangApr2014::init |
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| cv.saliency.MotionSaliencyBinWangApr2014.init( | | ) -> | retval |
This function allows the correct initialization of all data structures that will be used by the algorithm.
◆ setImageHeight()
| void cv::saliency::MotionSaliencyBinWangApr2014::setImageHeight |
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int | val | ) |
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| cv.saliency.MotionSaliencyBinWangApr2014.setImageHeight( | val | ) -> | None |
◆ setImagesize()
| void cv::saliency::MotionSaliencyBinWangApr2014::setImagesize |
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int | W, |
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int | H ) |
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| cv.saliency.MotionSaliencyBinWangApr2014.setImagesize( | W, H | ) -> | None |
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.
- Parameters
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| W | width of input image |
| H | height of input image |
◆ setImageWidth()
| void cv::saliency::MotionSaliencyBinWangApr2014::setImageWidth |
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int | val | ) |
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| cv.saliency.MotionSaliencyBinWangApr2014.setImageWidth( | val | ) -> | None |
The documentation for this class was generated from the following file: