Vibe-CPP.rar_ ViBe_ViBe前景检测_vibe_视频 背景建模

#include "ViBe.h" using namespace std; using namespace cv; int c_xoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0}; //x的邻居点 int c_yoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0}; //y的邻居点 ViBe_BGS::ViBe_BGS(void) { } ViBe_BGS::~ViBe_BGS(void) { } /**************** Assign space and init ***************************/ void ViBe_BGS::init(const Mat _image) { //动态分配三维数组，samples[][][NUM_SAMPLES]存储前景被连续检测的次数 samples=new unsigned char **[_image.rows]; for (int i=0;i<_image.rows;i++) { samples[i]=new unsigned char *[1024]; for (int j=0;j<_image.cols;j++) { samples[i][j]=new unsigned char [NUM_SAMPLES+1]; for (int k=0;k<NUM_SAMPLES+1;k++) { samples[i][j][k]=0; } } } m_mask = Mat::zeros(_image.size(),CV_8UC1); } /**************** Init model from first frame ********************/ void ViBe_BGS::processFirstFrame(const Mat _image) { RNG rng; int row, col; for(int i = 0; i < _image.rows; i++) { for(int j = 0; j < _image.cols; j++) { for(int k = 0 ; k < NUM_SAMPLES; k++) { // Random pick up NUM_SAMPLES pixel in neighbourhood to construct the model int random = rng.uniform(0, 9); row = i + c_yoff[random]; if (row < 0) row = 0; if (row >= _image.rows) row = _image.rows - 1; col = j + c_xoff[random]; if (col < 0) col = 0; if (col >= _image.cols) col = _image.cols - 1; samples[i][j][k]=_image.at<uchar>(row, col); } } } } /**************** Test a new frame and update model ********************/ void ViBe_BGS::testAndUpdate(const Mat _image) { RNG rng; for(int i = 0; i < _image.rows; i++) { for(int j = 0; j < _image.cols; j++) { int matches(0), count(0); int dist; while(matches < MIN_MATCHES && count < NUM_SAMPLES) { dist = abs(samples[i][j][count] - _image.at<uchar>(i, j)); if (dist < RADIUS) matches++; count++; } if (matches >= MIN_MATCHES) { // It is a background pixel samples[i][j][NUM_SAMPLES]=0; // Set background pixel to 0 m_mask.at<uchar>(i, j) = 0; // 如果一个像素是背景点，那么它有 1 / defaultSubsamplingFactor 的概率去更新自己的模型样本值 int random = rng.uniform(0, SUBSAMPLE_FACTOR); if (random == 0) { random = rng.uniform(0, NUM_SAMPLES); samples[i][j][random]=_image.at<uchar>(i, j); } // 同时也有 1 / defaultSubsamplingFactor 的概率去更新它的邻居点的模型样本值 random = rng.uniform(0, SUBSAMPLE_FACTOR); if (random == 0) { int row, col; random = rng.uniform(0, 9); row = i + c_yoff[random]; if (row < 0) row = 0; if (row >= _image.rows) row = _image.rows - 1; random = rng.uniform(0, 9); col = j + c_xoff[random]; if (col < 0) col = 0; if (col >= _image.cols) col = _image.cols - 1; random = rng.uniform(0, NUM_SAMPLES); samples[i][j][random]=_image.at<uchar>(i, j); } } else { // It is a foreground pixel samples[i][j][NUM_SAMPLES]++; // Set background pixel to 255 m_mask.at<uchar>(i, j) = 255; //如果某个像素点连续N次被检测为前景，则认为一块静止区域被误判为运动，将其更新为背景点 if(samples[i][j][NUM_SAMPLES]>50) { int random = rng.uniform(0, NUM_SAMPLES); if (random == 0) { random = rng.uniform(0, NUM_SAMPLES); samples[i][j][random]=_image.at<uchar>(i, j); } } } } } }