利用codebook对视频进行运动目标检测.zip

/** 比平均背景法性能更加良好的方法,codeBook模型实现背景减除 核心代码详细解析和实现 by zcube http://hi.baidu.com/zcube/ */ /************************************************************************/ /* A few more thoughts on codebook models In general, the codebook method works quite well across a wide number of conditions, and it is relatively quick to train and to run. It doesn’t deal well with varying patterns of light — such as morning, noon, and evening sunshine — or with someone turning lights on or off indoors. This type of global variability can be taken into account by using several different codebook models, one for each condition, and then allowing the condition to control which model is active. */ /************************************************************************/ #include <stdio.h> #include <cv.h> #include <highgui.h> #include <cxcore.h> #define CHANNELS 3 // 设置处理的图像通道数,要求小于等于图像本身的通道数 /////////////////////////////////////////////////////////////////////////// // 下面为码本码元的数据结构 // 处理图像时每个像素对应一个码本,每个码本中可有若干个码元 // 当涉及一个新领域,通常会遇到一些奇怪的名词,不要被这些名词吓坏,其实思路都是简单的 typedef struct ce { uchar learnHigh[CHANNELS]; // High side threshold for learning // 此码元各通道的阀值上限(学习界限) uchar learnLow[CHANNELS]; // Low side threshold for learning // 此码元各通道的阀值下限 // 学习过程中如果一个新像素各通道值x[i],均有 learnLow[i]<=x[i]<=learnHigh[i],则该像素可合并于此码元 uchar max[CHANNELS]; // High side of box boundary // 属于此码元的像素中各通道的最大值 uchar min[CHANNELS]; // Low side of box boundary // 属于此码元的像素中各通道的最小值 int t_last_update; // This is book keeping to allow us to kill stale entries // 此码元最后一次更新的时间,每一帧为一个单位时间,用于计算stale int stale; // max negative run (biggest period of inactivity) // 此码元最长不更新时间,用于删除规定时间不更新的码元,精简码本 } code_element; // 码元的数据结构 typedef struct code_book { code_element **cb; // 码元的二维指针,理解为指向码元指针数组的指针,使得添加码元时不需要来回复制码元,只需要简单的指针赋值即可 int numEntries; // 此码本中码元的数目 int t; // count every access // 此码本现在的时间,一帧为一个时间单位 } codeBook; // 码本的数据结构 /////////////////////////////////////////////////////////////////////////////////// // int updateCodeBook(uchar *p, codeBook &c, unsigned cbBounds) // Updates the codebook entry with a new data point // // p Pointer to a YUV pixel // c Codebook for this pixel // cbBounds Learning bounds for codebook (Rule of thumb: 10) // numChannels Number of color channels we're learning // // NOTES: // cvBounds must be of size cvBounds[numChannels] // // RETURN // codebook index int cvupdateCodeBook(uchar *p, codeBook &c, unsigned *cbBounds, int numChannels) { if(c.numEntries == 0) c.t = 0; // 码本中码元为零时初始化时间为0 c.t += 1; // Record learning event // 每调用一次加一,即每一帧图像加一 //SET HIGH AND LOW BOUNDS int n; unsigned int high[3],low[3]; for (n=0; n<numChannels; n++) { high[n] = *(p+n) + *(cbBounds+n); // *(p+n) 和 p[n] 结果等价,经试验*(p+n) 速度更快 if(high[n] > 255) high[n] = 255; low[n] = *(p+n)-*(cbBounds+n); if(low[n] < 0) low[n] = 0; // 用p 所指像素通道数据,加减cbBonds中数值,作为此像素阀值的上下限 } //SEE IF THIS FITS AN EXISTING CODEWORD int matchChannel; int i; for (i=0; i<c.numEntries; i++) { // 遍历此码本每个码元,测试p像素是否满足其中之一 matchChannel = 0; for (n=0; n<numChannels; n++) //遍历每个通道 { if((c.cb[i]->learnLow[n] <= *(p+n)) && (*(p+n) <= c.cb[i]->learnHigh[n])) //Found an entry for this channel // 如果p 像素通道数据在该码元阀值上下限之间 { matchChannel++; } } if (matchChannel == numChannels) // If an entry was found over all channels // 如果p 像素各通道都满足上面条件 { c.cb[i]->t_last_update = c.t; // 更新该码元时间为当前时间 // adjust this codeword for the first channel for (n=0; n<numChannels; n++) //调整该码元各通道最大最小值 { if (c.cb[i]->max[n] < *(p+n)) c.cb[i]->max[n] = *(p+n); else if (c.cb[i]->min[n] > *(p+n)) c.cb[i]->min[n] = *(p+n); } break; } } // ENTER A NEW CODE WORD IF NEEDED if(i == c.numEntries) // No existing code word found, make a new one // p 像素不满足此码本中任何一个码元,下面创建一个新码元 { code_element **foo = new code_element* [c.numEntries+1]; // 申请c.numEntries+1 个指向码元的指针 for(int ii=0; ii<c.numEntries; ii++) // 将前c.numEntries 个指针指向已存在的每个码元 foo[ii] = c.cb[ii]; foo[c.numEntries] = new code_element; // 申请一个新的码元 if(c.numEntries) delete [] c.cb; // 删除c.cb 指针数组 c.cb = foo; // 把foo 头指针赋给c.cb for(n=0; n<numChannels; n++) // 更新新码元各通道数据 { c.cb[c.numEntries]->learnHigh[n] = high[n]; c.cb[c.numEntries]->learnLow[n] = low[n]; c.cb[c.numEntries]->max[n] = *(p+n); c.cb[c.numEntries]->min[n] = *(p+n); } c.cb[c.numEntries]->t_last_update = c.t; c.cb[c.numEntries]->stale = 0; c.numEntries += 1; } // OVERHEAD TO TRACK POTENTIAL STALE ENTRIES for(int s=0; s<c.numEntries; s++) { // This garbage is to track which codebook entries are going stale int negRun = c.t - c.cb[s]->t_last_update; // 计算该码元的不更新时间 if(c.cb[s]->stale < negRun) c.cb[s]->stale = negRun; } // SLOWLY ADJUST LEARNING BOUNDS for(n=0; n<numChannels; n++) // 如果像素通道数据在高低阀值范围内,但在码元阀值之外,则缓慢调整此码元学习界限 { if(c.cb[i]->learnHigh[n] < high[n]) c.cb[i]->learnHigh[n] += 1; if(c.cb[i]->learnLow[n] > low[n]) c.cb[i]->learnLow[n] -= 1; } return(i); } /////////////////////////////////////////////////////////////////////////////////// // uchar cvbackgroundDiff(uchar *p, codeBook &c, int minMod, int maxMod) // Given a pixel and a code book, determine if the pixel is covered by the codebook // // p pixel pointer (YUV interleaved) // c codebook reference // numChannels Number of channels we are testing // maxMod Add this (possibly negative) number onto max level when code_element determining if new pixel is foreground // minMod Subract this (possible negative) number from min level code_element when determining if pixel is foreground // // NOTES: // minMod and maxMod must have length numChannels, e.g. 3 channels => minMod[3], maxMod[3]. // // Return // 0 => background, 255 => foreground uchar cvbackgroundDiff(uchar *p, codeBook &c, int numChannels, int *minMod, int *maxMod) { // 下面步骤和背景学习中查找码元如出一辙 int matchChannel; //SEE IF THIS FITS AN EXISTING CODEWORD int i; for (i=0; i<c.numEntries; i++) { matchChannel = 0; for (int n=0; n<numChannels; n++) { if ((c.cb[i]->min[n] - minMod[n] <= *(p+n)) && (*(p+n) <= c.cb[i]->max[n] + maxMod[n])) matchChannel++; //Found an entry for this channel else break; } if (matchChannel == numChannels) break; //Found an entry that matched all channels } if(i == c.numEntries)