Renesas / opencv-lib

openCV library for Renesas RZ/A

Dependents:   RZ_A2M_Mbed_samples

include/opencv2/video/background_segm.hpp@0:0e0631af0305, 2021-01-29 (annotated)

Committer:
RyoheiHagimoto
Date:
Fri Jan 29 04:53:38 2021 +0000
Revision:
0:0e0631af0305
copied from https://github.com/d-kato/opencv-lib.

Who changed what in which revision?

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RyoheiHagimoto 0:0e0631af0305 1 /*M///////////////////////////////////////////////////////////////////////////////////////
RyoheiHagimoto 0:0e0631af0305 2 //
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RyoheiHagimoto 0:0e0631af0305 6 // If you do not agree to this license, do not download, install,
RyoheiHagimoto 0:0e0631af0305 7 // copy or use the software.
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RyoheiHagimoto 0:0e0631af0305 10 // License Agreement
RyoheiHagimoto 0:0e0631af0305 11 // For Open Source Computer Vision Library
RyoheiHagimoto 0:0e0631af0305 12 //
RyoheiHagimoto 0:0e0631af0305 13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
RyoheiHagimoto 0:0e0631af0305 14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
RyoheiHagimoto 0:0e0631af0305 15 // Copyright (C) 2013, OpenCV Foundation, all rights reserved.
RyoheiHagimoto 0:0e0631af0305 16 // Third party copyrights are property of their respective owners.
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RyoheiHagimoto 0:0e0631af0305 20 //
RyoheiHagimoto 0:0e0631af0305 21 // * Redistribution's of source code must retain the above copyright notice,
RyoheiHagimoto 0:0e0631af0305 22 // this list of conditions and the following disclaimer.
RyoheiHagimoto 0:0e0631af0305 23 //
RyoheiHagimoto 0:0e0631af0305 24 // * Redistribution's in binary form must reproduce the above copyright notice,
RyoheiHagimoto 0:0e0631af0305 25 // this list of conditions and the following disclaimer in the documentation
RyoheiHagimoto 0:0e0631af0305 26 // and/or other materials provided with the distribution.
RyoheiHagimoto 0:0e0631af0305 27 //
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RyoheiHagimoto 0:0e0631af0305 29 // derived from this software without specific prior written permission.
RyoheiHagimoto 0:0e0631af0305 30 //
RyoheiHagimoto 0:0e0631af0305 31 // This software is provided by the copyright holders and contributors "as is" and
RyoheiHagimoto 0:0e0631af0305 32 // any express or implied warranties, including, but not limited to, the implied
RyoheiHagimoto 0:0e0631af0305 33 // warranties of merchantability and fitness for a particular purpose are disclaimed.
RyoheiHagimoto 0:0e0631af0305 34 // In no event shall the Intel Corporation or contributors be liable for any direct,
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RyoheiHagimoto 0:0e0631af0305 36 // (including, but not limited to, procurement of substitute goods or services;
RyoheiHagimoto 0:0e0631af0305 37 // loss of use, data, or profits; or business interruption) however caused
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RyoheiHagimoto 0:0e0631af0305 40 // the use of this software, even if advised of the possibility of such damage.
RyoheiHagimoto 0:0e0631af0305 41 //
RyoheiHagimoto 0:0e0631af0305 42 //M*/
RyoheiHagimoto 0:0e0631af0305 43
RyoheiHagimoto 0:0e0631af0305 44 #ifndef OPENCV_BACKGROUND_SEGM_HPP
RyoheiHagimoto 0:0e0631af0305 45 #define OPENCV_BACKGROUND_SEGM_HPP
RyoheiHagimoto 0:0e0631af0305 46
RyoheiHagimoto 0:0e0631af0305 47 #include "opencv2/core.hpp"
RyoheiHagimoto 0:0e0631af0305 48
RyoheiHagimoto 0:0e0631af0305 49 namespace cv
RyoheiHagimoto 0:0e0631af0305 50 {
RyoheiHagimoto 0:0e0631af0305 51
RyoheiHagimoto 0:0e0631af0305 52 //! @addtogroup video_motion
RyoheiHagimoto 0:0e0631af0305 53 //! @{
RyoheiHagimoto 0:0e0631af0305 54
RyoheiHagimoto 0:0e0631af0305 55 /** @brief Base class for background/foreground segmentation. :
RyoheiHagimoto 0:0e0631af0305 56
RyoheiHagimoto 0:0e0631af0305 57 The class is only used to define the common interface for the whole family of background/foreground
RyoheiHagimoto 0:0e0631af0305 58 segmentation algorithms.
RyoheiHagimoto 0:0e0631af0305 59 */
RyoheiHagimoto 0:0e0631af0305 60 class CV_EXPORTS_W BackgroundSubtractor : public Algorithm
RyoheiHagimoto 0:0e0631af0305 61 {
RyoheiHagimoto 0:0e0631af0305 62 public:
RyoheiHagimoto 0:0e0631af0305 63 /** @brief Computes a foreground mask.
RyoheiHagimoto 0:0e0631af0305 64
RyoheiHagimoto 0:0e0631af0305 65 @param image Next video frame.
RyoheiHagimoto 0:0e0631af0305 66 @param fgmask The output foreground mask as an 8-bit binary image.
RyoheiHagimoto 0:0e0631af0305 67 @param learningRate The value between 0 and 1 that indicates how fast the background model is
RyoheiHagimoto 0:0e0631af0305 68 learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
RyoheiHagimoto 0:0e0631af0305 69 rate. 0 means that the background model is not updated at all, 1 means that the background model
RyoheiHagimoto 0:0e0631af0305 70 is completely reinitialized from the last frame.
RyoheiHagimoto 0:0e0631af0305 71 */
RyoheiHagimoto 0:0e0631af0305 72 CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) = 0;
RyoheiHagimoto 0:0e0631af0305 73
RyoheiHagimoto 0:0e0631af0305 74 /** @brief Computes a background image.
RyoheiHagimoto 0:0e0631af0305 75
RyoheiHagimoto 0:0e0631af0305 76 @param backgroundImage The output background image.
RyoheiHagimoto 0:0e0631af0305 77
RyoheiHagimoto 0:0e0631af0305 78 @note Sometimes the background image can be very blurry, as it contain the average background
RyoheiHagimoto 0:0e0631af0305 79 statistics.
RyoheiHagimoto 0:0e0631af0305 80 */
RyoheiHagimoto 0:0e0631af0305 81 CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const = 0;
RyoheiHagimoto 0:0e0631af0305 82 };
RyoheiHagimoto 0:0e0631af0305 83
RyoheiHagimoto 0:0e0631af0305 84
RyoheiHagimoto 0:0e0631af0305 85 /** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
RyoheiHagimoto 0:0e0631af0305 86
RyoheiHagimoto 0:0e0631af0305 87 The class implements the Gaussian mixture model background subtraction described in @cite Zivkovic2004
RyoheiHagimoto 0:0e0631af0305 88 and @cite Zivkovic2006 .
RyoheiHagimoto 0:0e0631af0305 89 */
RyoheiHagimoto 0:0e0631af0305 90 class CV_EXPORTS_W BackgroundSubtractorMOG2 : public BackgroundSubtractor
RyoheiHagimoto 0:0e0631af0305 91 {
RyoheiHagimoto 0:0e0631af0305 92 public:
RyoheiHagimoto 0:0e0631af0305 93 /** @brief Returns the number of last frames that affect the background model
RyoheiHagimoto 0:0e0631af0305 94 */
RyoheiHagimoto 0:0e0631af0305 95 CV_WRAP virtual int getHistory() const = 0;
RyoheiHagimoto 0:0e0631af0305 96 /** @brief Sets the number of last frames that affect the background model
RyoheiHagimoto 0:0e0631af0305 97 */
RyoheiHagimoto 0:0e0631af0305 98 CV_WRAP virtual void setHistory(int history) = 0;
RyoheiHagimoto 0:0e0631af0305 99
RyoheiHagimoto 0:0e0631af0305 100 /** @brief Returns the number of gaussian components in the background model
RyoheiHagimoto 0:0e0631af0305 101 */
RyoheiHagimoto 0:0e0631af0305 102 CV_WRAP virtual int getNMixtures() const = 0;
RyoheiHagimoto 0:0e0631af0305 103 /** @brief Sets the number of gaussian components in the background model.
RyoheiHagimoto 0:0e0631af0305 104
RyoheiHagimoto 0:0e0631af0305 105 The model needs to be reinitalized to reserve memory.
RyoheiHagimoto 0:0e0631af0305 106 */
RyoheiHagimoto 0:0e0631af0305 107 CV_WRAP virtual void setNMixtures(int nmixtures) = 0;//needs reinitialization!
RyoheiHagimoto 0:0e0631af0305 108
RyoheiHagimoto 0:0e0631af0305 109 /** @brief Returns the "background ratio" parameter of the algorithm
RyoheiHagimoto 0:0e0631af0305 110
RyoheiHagimoto 0:0e0631af0305 111 If a foreground pixel keeps semi-constant value for about backgroundRatio\*history frames, it's
RyoheiHagimoto 0:0e0631af0305 112 considered background and added to the model as a center of a new component. It corresponds to TB
RyoheiHagimoto 0:0e0631af0305 113 parameter in the paper.
RyoheiHagimoto 0:0e0631af0305 114 */
RyoheiHagimoto 0:0e0631af0305 115 CV_WRAP virtual double getBackgroundRatio() const = 0;
RyoheiHagimoto 0:0e0631af0305 116 /** @brief Sets the "background ratio" parameter of the algorithm
RyoheiHagimoto 0:0e0631af0305 117 */
RyoheiHagimoto 0:0e0631af0305 118 CV_WRAP virtual void setBackgroundRatio(double ratio) = 0;
RyoheiHagimoto 0:0e0631af0305 119
RyoheiHagimoto 0:0e0631af0305 120 /** @brief Returns the variance threshold for the pixel-model match
RyoheiHagimoto 0:0e0631af0305 121
RyoheiHagimoto 0:0e0631af0305 122 The main threshold on the squared Mahalanobis distance to decide if the sample is well described by
RyoheiHagimoto 0:0e0631af0305 123 the background model or not. Related to Cthr from the paper.
RyoheiHagimoto 0:0e0631af0305 124 */
RyoheiHagimoto 0:0e0631af0305 125 CV_WRAP virtual double getVarThreshold() const = 0;
RyoheiHagimoto 0:0e0631af0305 126 /** @brief Sets the variance threshold for the pixel-model match
RyoheiHagimoto 0:0e0631af0305 127 */
RyoheiHagimoto 0:0e0631af0305 128 CV_WRAP virtual void setVarThreshold(double varThreshold) = 0;
RyoheiHagimoto 0:0e0631af0305 129
RyoheiHagimoto 0:0e0631af0305 130 /** @brief Returns the variance threshold for the pixel-model match used for new mixture component generation
RyoheiHagimoto 0:0e0631af0305 131
RyoheiHagimoto 0:0e0631af0305 132 Threshold for the squared Mahalanobis distance that helps decide when a sample is close to the
RyoheiHagimoto 0:0e0631af0305 133 existing components (corresponds to Tg in the paper). If a pixel is not close to any component, it
RyoheiHagimoto 0:0e0631af0305 134 is considered foreground or added as a new component. 3 sigma =\> Tg=3\*3=9 is default. A smaller Tg
RyoheiHagimoto 0:0e0631af0305 135 value generates more components. A higher Tg value may result in a small number of components but
RyoheiHagimoto 0:0e0631af0305 136 they can grow too large.
RyoheiHagimoto 0:0e0631af0305 137 */
RyoheiHagimoto 0:0e0631af0305 138 CV_WRAP virtual double getVarThresholdGen() const = 0;
RyoheiHagimoto 0:0e0631af0305 139 /** @brief Sets the variance threshold for the pixel-model match used for new mixture component generation
RyoheiHagimoto 0:0e0631af0305 140 */
RyoheiHagimoto 0:0e0631af0305 141 CV_WRAP virtual void setVarThresholdGen(double varThresholdGen) = 0;
RyoheiHagimoto 0:0e0631af0305 142
RyoheiHagimoto 0:0e0631af0305 143 /** @brief Returns the initial variance of each gaussian component
RyoheiHagimoto 0:0e0631af0305 144 */
RyoheiHagimoto 0:0e0631af0305 145 CV_WRAP virtual double getVarInit() const = 0;
RyoheiHagimoto 0:0e0631af0305 146 /** @brief Sets the initial variance of each gaussian component
RyoheiHagimoto 0:0e0631af0305 147 */
RyoheiHagimoto 0:0e0631af0305 148 CV_WRAP virtual void setVarInit(double varInit) = 0;
RyoheiHagimoto 0:0e0631af0305 149
RyoheiHagimoto 0:0e0631af0305 150 CV_WRAP virtual double getVarMin() const = 0;
RyoheiHagimoto 0:0e0631af0305 151 CV_WRAP virtual void setVarMin(double varMin) = 0;
RyoheiHagimoto 0:0e0631af0305 152
RyoheiHagimoto 0:0e0631af0305 153 CV_WRAP virtual double getVarMax() const = 0;
RyoheiHagimoto 0:0e0631af0305 154 CV_WRAP virtual void setVarMax(double varMax) = 0;
RyoheiHagimoto 0:0e0631af0305 155
RyoheiHagimoto 0:0e0631af0305 156 /** @brief Returns the complexity reduction threshold
RyoheiHagimoto 0:0e0631af0305 157
RyoheiHagimoto 0:0e0631af0305 158 This parameter defines the number of samples needed to accept to prove the component exists. CT=0.05
RyoheiHagimoto 0:0e0631af0305 159 is a default value for all the samples. By setting CT=0 you get an algorithm very similar to the
RyoheiHagimoto 0:0e0631af0305 160 standard Stauffer&Grimson algorithm.
RyoheiHagimoto 0:0e0631af0305 161 */
RyoheiHagimoto 0:0e0631af0305 162 CV_WRAP virtual double getComplexityReductionThreshold() const = 0;
RyoheiHagimoto 0:0e0631af0305 163 /** @brief Sets the complexity reduction threshold
RyoheiHagimoto 0:0e0631af0305 164 */
RyoheiHagimoto 0:0e0631af0305 165 CV_WRAP virtual void setComplexityReductionThreshold(double ct) = 0;
RyoheiHagimoto 0:0e0631af0305 166
RyoheiHagimoto 0:0e0631af0305 167 /** @brief Returns the shadow detection flag
RyoheiHagimoto 0:0e0631af0305 168
RyoheiHagimoto 0:0e0631af0305 169 If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorMOG2 for
RyoheiHagimoto 0:0e0631af0305 170 details.
RyoheiHagimoto 0:0e0631af0305 171 */
RyoheiHagimoto 0:0e0631af0305 172 CV_WRAP virtual bool getDetectShadows() const = 0;
RyoheiHagimoto 0:0e0631af0305 173 /** @brief Enables or disables shadow detection
RyoheiHagimoto 0:0e0631af0305 174 */
RyoheiHagimoto 0:0e0631af0305 175 CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0;
RyoheiHagimoto 0:0e0631af0305 176
RyoheiHagimoto 0:0e0631af0305 177 /** @brief Returns the shadow value
RyoheiHagimoto 0:0e0631af0305 178
RyoheiHagimoto 0:0e0631af0305 179 Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0
RyoheiHagimoto 0:0e0631af0305 180 in the mask always means background, 255 means foreground.
RyoheiHagimoto 0:0e0631af0305 181 */
RyoheiHagimoto 0:0e0631af0305 182 CV_WRAP virtual int getShadowValue() const = 0;
RyoheiHagimoto 0:0e0631af0305 183 /** @brief Sets the shadow value
RyoheiHagimoto 0:0e0631af0305 184 */
RyoheiHagimoto 0:0e0631af0305 185 CV_WRAP virtual void setShadowValue(int value) = 0;
RyoheiHagimoto 0:0e0631af0305 186
RyoheiHagimoto 0:0e0631af0305 187 /** @brief Returns the shadow threshold
RyoheiHagimoto 0:0e0631af0305 188
RyoheiHagimoto 0:0e0631af0305 189 A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
RyoheiHagimoto 0:0e0631af0305 190 the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
RyoheiHagimoto 0:0e0631af0305 191 is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
RyoheiHagimoto 0:0e0631af0305 192 *Detecting Moving Shadows...*, IEEE PAMI,2003.
RyoheiHagimoto 0:0e0631af0305 193 */
RyoheiHagimoto 0:0e0631af0305 194 CV_WRAP virtual double getShadowThreshold() const = 0;
RyoheiHagimoto 0:0e0631af0305 195 /** @brief Sets the shadow threshold
RyoheiHagimoto 0:0e0631af0305 196 */
RyoheiHagimoto 0:0e0631af0305 197 CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
RyoheiHagimoto 0:0e0631af0305 198 };
RyoheiHagimoto 0:0e0631af0305 199
RyoheiHagimoto 0:0e0631af0305 200 /** @brief Creates MOG2 Background Subtractor
RyoheiHagimoto 0:0e0631af0305 201
RyoheiHagimoto 0:0e0631af0305 202 @param history Length of the history.
RyoheiHagimoto 0:0e0631af0305 203 @param varThreshold Threshold on the squared Mahalanobis distance between the pixel and the model
RyoheiHagimoto 0:0e0631af0305 204 to decide whether a pixel is well described by the background model. This parameter does not
RyoheiHagimoto 0:0e0631af0305 205 affect the background update.
RyoheiHagimoto 0:0e0631af0305 206 @param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the
RyoheiHagimoto 0:0e0631af0305 207 speed a bit, so if you do not need this feature, set the parameter to false.
RyoheiHagimoto 0:0e0631af0305 208 */
RyoheiHagimoto 0:0e0631af0305 209 CV_EXPORTS_W Ptr<BackgroundSubtractorMOG2>
RyoheiHagimoto 0:0e0631af0305 210 createBackgroundSubtractorMOG2(int history=500, double varThreshold=16,
RyoheiHagimoto 0:0e0631af0305 211 bool detectShadows=true);
RyoheiHagimoto 0:0e0631af0305 212
RyoheiHagimoto 0:0e0631af0305 213 /** @brief K-nearest neigbours - based Background/Foreground Segmentation Algorithm.
RyoheiHagimoto 0:0e0631af0305 214
RyoheiHagimoto 0:0e0631af0305 215 The class implements the K-nearest neigbours background subtraction described in @cite Zivkovic2006 .
RyoheiHagimoto 0:0e0631af0305 216 Very efficient if number of foreground pixels is low.
RyoheiHagimoto 0:0e0631af0305 217 */
RyoheiHagimoto 0:0e0631af0305 218 class CV_EXPORTS_W BackgroundSubtractorKNN : public BackgroundSubtractor
RyoheiHagimoto 0:0e0631af0305 219 {
RyoheiHagimoto 0:0e0631af0305 220 public:
RyoheiHagimoto 0:0e0631af0305 221 /** @brief Returns the number of last frames that affect the background model
RyoheiHagimoto 0:0e0631af0305 222 */
RyoheiHagimoto 0:0e0631af0305 223 CV_WRAP virtual int getHistory() const = 0;
RyoheiHagimoto 0:0e0631af0305 224 /** @brief Sets the number of last frames that affect the background model
RyoheiHagimoto 0:0e0631af0305 225 */
RyoheiHagimoto 0:0e0631af0305 226 CV_WRAP virtual void setHistory(int history) = 0;
RyoheiHagimoto 0:0e0631af0305 227
RyoheiHagimoto 0:0e0631af0305 228 /** @brief Returns the number of data samples in the background model
RyoheiHagimoto 0:0e0631af0305 229 */
RyoheiHagimoto 0:0e0631af0305 230 CV_WRAP virtual int getNSamples() const = 0;
RyoheiHagimoto 0:0e0631af0305 231 /** @brief Sets the number of data samples in the background model.
RyoheiHagimoto 0:0e0631af0305 232
RyoheiHagimoto 0:0e0631af0305 233 The model needs to be reinitalized to reserve memory.
RyoheiHagimoto 0:0e0631af0305 234 */
RyoheiHagimoto 0:0e0631af0305 235 CV_WRAP virtual void setNSamples(int _nN) = 0;//needs reinitialization!
RyoheiHagimoto 0:0e0631af0305 236
RyoheiHagimoto 0:0e0631af0305 237 /** @brief Returns the threshold on the squared distance between the pixel and the sample
RyoheiHagimoto 0:0e0631af0305 238
RyoheiHagimoto 0:0e0631af0305 239 The threshold on the squared distance between the pixel and the sample to decide whether a pixel is
RyoheiHagimoto 0:0e0631af0305 240 close to a data sample.
RyoheiHagimoto 0:0e0631af0305 241 */
RyoheiHagimoto 0:0e0631af0305 242 CV_WRAP virtual double getDist2Threshold() const = 0;
RyoheiHagimoto 0:0e0631af0305 243 /** @brief Sets the threshold on the squared distance
RyoheiHagimoto 0:0e0631af0305 244 */
RyoheiHagimoto 0:0e0631af0305 245 CV_WRAP virtual void setDist2Threshold(double _dist2Threshold) = 0;
RyoheiHagimoto 0:0e0631af0305 246
RyoheiHagimoto 0:0e0631af0305 247 /** @brief Returns the number of neighbours, the k in the kNN.
RyoheiHagimoto 0:0e0631af0305 248
RyoheiHagimoto 0:0e0631af0305 249 K is the number of samples that need to be within dist2Threshold in order to decide that that
RyoheiHagimoto 0:0e0631af0305 250 pixel is matching the kNN background model.
RyoheiHagimoto 0:0e0631af0305 251 */
RyoheiHagimoto 0:0e0631af0305 252 CV_WRAP virtual int getkNNSamples() const = 0;
RyoheiHagimoto 0:0e0631af0305 253 /** @brief Sets the k in the kNN. How many nearest neigbours need to match.
RyoheiHagimoto 0:0e0631af0305 254 */
RyoheiHagimoto 0:0e0631af0305 255 CV_WRAP virtual void setkNNSamples(int _nkNN) = 0;
RyoheiHagimoto 0:0e0631af0305 256
RyoheiHagimoto 0:0e0631af0305 257 /** @brief Returns the shadow detection flag
RyoheiHagimoto 0:0e0631af0305 258
RyoheiHagimoto 0:0e0631af0305 259 If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for
RyoheiHagimoto 0:0e0631af0305 260 details.
RyoheiHagimoto 0:0e0631af0305 261 */
RyoheiHagimoto 0:0e0631af0305 262 CV_WRAP virtual bool getDetectShadows() const = 0;
RyoheiHagimoto 0:0e0631af0305 263 /** @brief Enables or disables shadow detection
RyoheiHagimoto 0:0e0631af0305 264 */
RyoheiHagimoto 0:0e0631af0305 265 CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0;
RyoheiHagimoto 0:0e0631af0305 266
RyoheiHagimoto 0:0e0631af0305 267 /** @brief Returns the shadow value
RyoheiHagimoto 0:0e0631af0305 268
RyoheiHagimoto 0:0e0631af0305 269 Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0
RyoheiHagimoto 0:0e0631af0305 270 in the mask always means background, 255 means foreground.
RyoheiHagimoto 0:0e0631af0305 271 */
RyoheiHagimoto 0:0e0631af0305 272 CV_WRAP virtual int getShadowValue() const = 0;
RyoheiHagimoto 0:0e0631af0305 273 /** @brief Sets the shadow value
RyoheiHagimoto 0:0e0631af0305 274 */
RyoheiHagimoto 0:0e0631af0305 275 CV_WRAP virtual void setShadowValue(int value) = 0;
RyoheiHagimoto 0:0e0631af0305 276
RyoheiHagimoto 0:0e0631af0305 277 /** @brief Returns the shadow threshold
RyoheiHagimoto 0:0e0631af0305 278
RyoheiHagimoto 0:0e0631af0305 279 A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
RyoheiHagimoto 0:0e0631af0305 280 the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
RyoheiHagimoto 0:0e0631af0305 281 is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
RyoheiHagimoto 0:0e0631af0305 282 *Detecting Moving Shadows...*, IEEE PAMI,2003.
RyoheiHagimoto 0:0e0631af0305 283 */
RyoheiHagimoto 0:0e0631af0305 284 CV_WRAP virtual double getShadowThreshold() const = 0;
RyoheiHagimoto 0:0e0631af0305 285 /** @brief Sets the shadow threshold
RyoheiHagimoto 0:0e0631af0305 286 */
RyoheiHagimoto 0:0e0631af0305 287 CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
RyoheiHagimoto 0:0e0631af0305 288 };
RyoheiHagimoto 0:0e0631af0305 289
RyoheiHagimoto 0:0e0631af0305 290 /** @brief Creates KNN Background Subtractor
RyoheiHagimoto 0:0e0631af0305 291
RyoheiHagimoto 0:0e0631af0305 292 @param history Length of the history.
RyoheiHagimoto 0:0e0631af0305 293 @param dist2Threshold Threshold on the squared distance between the pixel and the sample to decide
RyoheiHagimoto 0:0e0631af0305 294 whether a pixel is close to that sample. This parameter does not affect the background update.
RyoheiHagimoto 0:0e0631af0305 295 @param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the
RyoheiHagimoto 0:0e0631af0305 296 speed a bit, so if you do not need this feature, set the parameter to false.
RyoheiHagimoto 0:0e0631af0305 297 */
RyoheiHagimoto 0:0e0631af0305 298 CV_EXPORTS_W Ptr<BackgroundSubtractorKNN>
RyoheiHagimoto 0:0e0631af0305 299 createBackgroundSubtractorKNN(int history=500, double dist2Threshold=400.0,
RyoheiHagimoto 0:0e0631af0305 300 bool detectShadows=true);
RyoheiHagimoto 0:0e0631af0305 301
RyoheiHagimoto 0:0e0631af0305 302 //! @} video_motion
RyoheiHagimoto 0:0e0631af0305 303
RyoheiHagimoto 0:0e0631af0305 304 } // cv
RyoheiHagimoto 0:0e0631af0305 305
RyoheiHagimoto 0:0e0631af0305 306 #endif