KINECT+opencv(2)基于骨骼信息对视频进行动作识别
KINECT+opencv(2)基于骨骼信息对视频进行动作识别
环境：kinect1.7+opencv2.4+vc2015
- 使用kinect获取并按批处理三维空间内的骨骼信息
- 基于视频帧差计算各关节运动向量并与本地模板匹配
目录
- KINECTopencv2基于骨骼信息对视频进行动作识别
- 目录
- 写在前面
- 对当前帧处理并匹配
- kinect对帧的处理
- 与模板的向量余弦计算
- 根据动态时间规划法匹配
- 记录并保存模板到本地
- 使用opencv的FileStorage类生成xml文件
写在前面
- 自前一篇过去一周了。这次开始对视频流进行识别匹配。大体的框架是：kinect按批读入视频帧，然后将这一批视频流与模板视频流进行匹配识别。即，kinect先读入NUM_OF_FRAME（120）帧的骨骼信息，然后每一帧减去后一帧计算出各关节点的位移向量，将这些位移向量与模板匹配。
- 同样又写了两个程序，一个对当前视频处理并匹配，另一个记录并保存模板到本地。
1.对当前帧处理并匹配
#include (i)[j * 3] = now.ptr(i + 1)[j * 3] - now.ptr(i)[j * 3];
temp.ptr(i)[j * 3 + 1] = now.ptr(i + 1)[j * 3 + 1] - now.ptr(i)[j * 3 + 1];
temp.ptr(i)[j * 3 + 2] = now.ptr(i + 1)[j * 3 + 2] - now.ptr(i)[j * 3 + 2];
}
}
return temp;
}
void drawSkeleton(Mat &image, CvPoint pointSet[], NUI_SKELETON_FRAME now,int userid)//画出骨骼，推断出来的关节点用灰色表示
{
CvScalar color;
color = cvScalar(255);
if ((pointSet[NUI_SKELETON_POSITION_HEAD].x != 0 || pointSet[NUI_SKELETON_POSITION_HEAD].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_HEAD], pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_SPINE].x != 0 || pointSet[NUI_SKELETON_POSITION_SPINE].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER], pointSet[NUI_SKELETON_POSITION_SPINE], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_SPINE].x != 0 || pointSet[NUI_SKELETON_POSITION_SPINE].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_HIP_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_CENTER].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_SPINE], pointSet[NUI_SKELETON_POSITION_HIP_CENTER], color, 2);
//左上肢
if ((pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_SHOULDER_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER], pointSet[NUI_SKELETON_POSITION_SHOULDER_LEFT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_SHOULDER_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_LEFT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_ELBOW_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_ELBOW_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_SHOULDER_LEFT], pointSet[NUI_SKELETON_POSITION_ELBOW_LEFT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_ELBOW_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_ELBOW_LEFT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_WRIST_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_WRIST_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_ELBOW_LEFT], pointSet[NUI_SKELETON_POSITION_WRIST_LEFT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_WRIST_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_WRIST_LEFT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_HAND_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_HAND_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_WRIST_LEFT], pointSet[NUI_SKELETON_POSITION_HAND_LEFT], color, 2);
//右上肢
if ((pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_SHOULDER_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_SHOULDER_CENTER], pointSet[NUI_SKELETON_POSITION_SHOULDER_RIGHT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_SHOULDER_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_SHOULDER_RIGHT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_ELBOW_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_ELBOW_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_SHOULDER_RIGHT], pointSet[NUI_SKELETON_POSITION_ELBOW_RIGHT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_ELBOW_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_ELBOW_RIGHT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_WRIST_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_WRIST_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_ELBOW_RIGHT], pointSet[NUI_SKELETON_POSITION_WRIST_RIGHT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_WRIST_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_WRIST_RIGHT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_HAND_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_HAND_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_WRIST_RIGHT], pointSet[NUI_SKELETON_POSITION_HAND_RIGHT], color, 2);
//左下肢
if ((pointSet[NUI_SKELETON_POSITION_HIP_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_CENTER].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_HIP_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_HIP_CENTER], pointSet[NUI_SKELETON_POSITION_HIP_LEFT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_HIP_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_LEFT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_KNEE_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_KNEE_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_HIP_LEFT], pointSet[NUI_SKELETON_POSITION_KNEE_LEFT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_KNEE_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_KNEE_LEFT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_ANKLE_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_ANKLE_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_KNEE_LEFT], pointSet[NUI_SKELETON_POSITION_ANKLE_LEFT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_ANKLE_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_ANKLE_LEFT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_FOOT_LEFT].x != 0 || pointSet[NUI_SKELETON_POSITION_FOOT_LEFT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_ANKLE_LEFT], pointSet[NUI_SKELETON_POSITION_FOOT_LEFT], color, 2);
//右下肢
if ((pointSet[NUI_SKELETON_POSITION_HIP_CENTER].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_CENTER].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_HIP_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_HIP_CENTER], pointSet[NUI_SKELETON_POSITION_HIP_RIGHT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_HIP_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_HIP_RIGHT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_KNEE_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_KNEE_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_HIP_RIGHT], pointSet[NUI_SKELETON_POSITION_KNEE_RIGHT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_KNEE_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_KNEE_RIGHT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_ANKLE_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_ANKLE_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_KNEE_RIGHT], pointSet[NUI_SKELETON_POSITION_ANKLE_RIGHT], color, 2);
if ((pointSet[NUI_SKELETON_POSITION_ANKLE_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_ANKLE_RIGHT].y != 0) &&
(pointSet[NUI_SKELETON_POSITION_FOOT_RIGHT].x != 0 || pointSet[NUI_SKELETON_POSITION_FOOT_RIGHT].y != 0))
line(image, pointSet[NUI_SKELETON_POSITION_ANKLE_RIGHT], pointSet[NUI_SKELETON_POSITION_FOOT_RIGHT], color, 2);
for (int i = 0;i < 20 ;i++)
{if(now.SkeletonData[userid].SkeletonPositions[i].x)
if (now.SkeletonData[userid].eSkeletonPositionTrackingState[i] == 1|| now.SkeletonData[userid].eSkeletonPositionTrackingState[i] == 0)
circle(image, pointSet[i], 5, Scalar(128), 2);
else
circle(image, pointSet[i], 5, Scalar(255), 2);
}
}
//用于匹配的类
class Process {
private:
Mat framess;
Vector4 mark;//追踪到当前最后一帧人物的中心坐标
int matching;
float disvalsModel[NUM_OF_MODEL][NUM_OF_FRAME] = { 0 };
public:
Process() :matching(0)
{
framess.create(NUM_OF_FRAME, NUM_OF_SKELETONS, CV_32FC3);
mark = { 0 };
}
void classify(Mat &outmark)//将匹配到的动作编号转化为文字保存进mark里
{
float fx, fy;
NuiTransformSkeletonToDepthImage(mark, &fx, &fy);
fx *= 2;
fy *= 2;
circle(outmark, cvPoint((int)fx,(int)fy),2,Scalar(64,255,255 ),3);
const string str = "the pose is " + int2type(matching);
putText(outmark, str, cvPoint((int)fx, (int)fy), CV_FONT_HERSHEY_COMPLEX,1,Scalar(64, 255, 255));
}
void shakeMask(NUI_SKELETON_FRAME past, NUI_SKELETON_FRAME &now, int userid)
{
for (int j = 3;j < NUM_OF_SKELETONS;j++)
{
if (now.SkeletonData[userid].eSkeletonPositionTrackingState[j] == 1 && (
(now.SkeletonData[userid].SkeletonPositions[j].x - past.SkeletonData[userid].SkeletonPositions[j].x)>INERRED_THRESHOLD_VALUE ||
(now.SkeletonData[userid].SkeletonPositions[j].y - past.SkeletonData[userid].SkeletonPositions[j].y) > INERRED_THRESHOLD_VALUE ||
(now.SkeletonData[userid].SkeletonPositions[j].z - past.SkeletonData[userid].SkeletonPositions[j].z) > INERRED_THRESHOLD_VALUE))
{
now.SkeletonData[userid].SkeletonPositions[j].x = past.SkeletonData[userid].SkeletonPositions[j].x;
now.SkeletonData[userid].SkeletonPositions[j].y = past.SkeletonData[userid].SkeletonPositions[j].y;
now.SkeletonData[userid].SkeletonPositions[j].z = past.SkeletonData[userid].SkeletonPositions[j].z;
}
if (now.SkeletonData[userid].SkeletonPositions[j].x - past.SkeletonData[userid].SkeletonPositions[j].x < SHAKE_THRESHOLD_VALUE)
now.SkeletonData[userid].SkeletonPositions[j].x = past.SkeletonData[userid].SkeletonPositions[j].x;
if (now.SkeletonData[userid].SkeletonPositions[j].y - past.SkeletonData[userid].SkeletonPositions[j].y < SHAKE_THRESHOLD_VALUE)
now.SkeletonData[userid].SkeletonPositions[j].y = past.SkeletonData[userid].SkeletonPositions[j].y;
if (now.SkeletonData[userid].SkeletonPositions[j].z - past.SkeletonData[userid].SkeletonPositions[j].z < SHAKE_THRESHOLD_VALUE)
now.SkeletonData[userid].SkeletonPositions[j].z = past.SkeletonData[userid].SkeletonPositions[j].z;
}
}
void setInput(NUI_SKELETON_FRAME past, NUI_SKELETON_FRAME now, int counter, int userid)//前后两帧做差求位移向量
{
if (counter == NUM_OF_FRAME-1)
{
mark.x = now.SkeletonData[userid].Position.x;
mark.y = now.SkeletonData[userid].Position.y;
mark.z = now.SkeletonData[userid].Position.z;
}
for (int j = 0;j < NUM_OF_SKELETONS;j++)
{
framess.ptr(counter)[3 * j] = now.SkeletonData[userid].SkeletonPositions[j].x - past.SkeletonData[userid].SkeletonPositions[j].x;
framess.ptr(counter)[3 * j + 1] = now.SkeletonData[userid].SkeletonPositions[j].y - past.SkeletonData[userid].SkeletonPositions[j].y;
framess.ptr(counter)[3 * j + 2] = now.SkeletonData[userid].SkeletonPositions[j].z - past.SkeletonData[userid].SkeletonPositions[j].z;
}
}
float rtwCal(int flag)
{
float rtwMat[3] = { 0 };
Mat rtwmat(NUM_OF_FRAME, NUM_OF_FRAME, CV_32FC1, Scalar(0));
for (int i = 0;i < NUM_OF_FRAME;i++)
{
for (int j = 0;j < NUM_OF_FRAME;j++)
{
for (int k = 0;k < (NUM_OF_SKELETONS * 3);k++)//多维向量余弦计算
{
rtwMat[0] += framess.ptr(i)[k] * modelskeleton[flag].ptr(j)[k];
rtwMat[1] += framess.ptr(i)[k] * framess.ptr(i)[k];
rtwMat[2] += modelskeleton[flag].ptr(j)[k] * modelskeleton[flag].ptr(j)[k];
}
rtwmat.ptr(i)[j] = rtwMat[0] / (sqrt(rtwMat[1])*sqrt(rtwMat[2])); }
}
float routeVal[NUM_OF_FRAME] = { 0 };
for (int i = 0;i < NUM_OF_FRAME;i++)
{
for (int j = 0;j < NUM_OF_FRAME;j++)
{
routeVal[i] += rtwmat.ptr(j)[(j + i) % NUM_OF_FRAME];
}
}
float result = routeVal[0];
for (int i = 0;i < NUM_OF_FRAME-1;i++)
{
if (result1])
result = routeVal[i + 1];
}
return result;
}
void processBegin()
{
int result = 0;
float rtwDistance[NUM_OF_MODEL] = { 0 };
for (int i = 0;i < NUM_OF_MODEL;i++)
{
rtwDistance[i] = rtwCal(i);
cout << "the distance between " + int2str(i+1) << "is" << rtwDistance[i] << endl;
}
float temp = rtwDistance[0];
for (int i = 0;i < NUM_OF_MODEL - 1;i++)
{
if (temp < rtwDistance[i + 1])
{
temp = rtwDistance[i + 1];
result = i + 1;
}
}
matching = result+1;
if (temp < 0.3)
matching = 0;
cout << "this time is type" << int2str(matching) << endl << endl;
}
};
int main()
{
Mat image(480, 640, CV_8UC3, Scalar(0, 0, 0));
//
HRESULT hr = NuiInitialize(NUI_INITIALIZE_FLAG_USES_SKELETON | NUI_INITIALIZE_FLAG_USES_COLOR);
HANDLE skeletonEvent = CreateEvent(NULL, TRUE, FALSE, NULL);
hr = NuiSkeletonTrackingEnable(skeletonEvent, NUI_SKELETON_TRACKING_FLAG_ENABLE_SEATED_SUPPORT);
//
HANDLE ColorFrameStream = NULL;
HANDLE NextFrameEvent = CreateEvent(NULL, TRUE, FALSE, NULL);
hr = NuiImageStreamOpen(NUI_IMAGE_TYPE_COLOR, NUI_IMAGE_RESOLUTION_640x480, 0, 2, NextFrameEvent, &ColorFrameStream);
if (FAILED(hr))
{
cout << "Could not open image stream video" << endl;
return hr;
}
//
NUI_SKELETON_FRAME pastFrame = { 0 };
NUI_SKELETON_FRAME nowFrame = { 0 };
Mat mark(image.size(), CV_8UC3, Scalar(0, 0, 0));//整个匹配运算的结果保存在mark里，和颜色通道一起叠加输出到屏幕
int userid = 0;
bool bFoundSkeleton = FALSE;
//启动kinect
while (!bFoundSkeleton)
{
if (WaitForSingleObject(skeletonEvent, INFINITE) == 0)
{
hr = NuiSkeletonGetNextFrame(0, &nowFrame);
for (int i = 0;i < NUI_SKELETON_COUNT;i++)
{
NUI_SKELETON_TRACKING_STATE trackingState = nowFrame.SkeletonData[i].eTrackingState;
if (trackingState == NUI_SKELETON_TRACKED)
{
bFoundSkeleton = TRUE;
userid = i;
}
}
}
}
int idcounter = 0;
//读入模板初始化
FileStorage fds("monitor_file.xml", FileStorage::READ);
for (int i = 0;i < NUM_OF_MODEL;i++)
{
modelskeleton[i].create(NUM_OF_FRAME, NUM_OF_SKELETONS, CV_32FC3);
Mat temp1(NUM_OF_FRAME + 1, NUM_OF_SKELETONS, CV_32FC3);
fds["mat_id" + int2str(idcounter)] >> temp1;
modelskeleton[i] = setInput0(temp1, idcounter);
idcounter++;
}
fds.release();
while (1)
{
//
int frameCounter = 0;
Process process=Process();
for (;userid < NUI_SKELETON_COUNT;userid++)
{
if (nowFrame.SkeletonData[userid].eTrackingState == NUI_SKELETON_TRACKED &&
nowFrame.SkeletonData[userid].eSkeletonPositionTrackingState[NUI_SKELETON_POSITION_SHOULDER_CENTER] != NUI_SKELETON_POSITION_NOT_TRACKED)
{
while (frameCounter < NUM_OF_FRAME)
{
//显示颜色通道图像
const NUI_IMAGE_FRAME * pImageFrame = NULL;
if (WaitForSingleObject(skeletonEvent, INFINITE) == 0)
{
NuiImageStreamGetNextFrame(ColorFrameStream, 0, &pImageFrame);
INuiFrameTexture * pTexture = pImageFrame->pFrameTexture;
NUI_LOCKED_RECT LockedRect;
pTexture->LockRect(0, &LockedRect, NULL, 0);
for (int i = 0; i < image.rows; i++)
{
uchar *ptr = image.ptr(i);
uchar *pBuffer = (uchar*)(LockedRect.pBits) + i * LockedRect.Pitch;
for (int j = 0; j < image.cols; j++)
{
ptr[3 * j] = pBuffer[4 * j];
ptr[3 * j + 1] = pBuffer[4 * j + 1];
ptr[3 * j + 2] = pBuffer[4 * j + 2];
}
}
imshow("colorImage", image + mark);
pTexture->UnlockRect(0);
cvWaitKey(33);
NuiImageStreamReleaseFrame(ColorFrameStream, pImageFrame);
//
pastFrame = nowFrame;
hr = NuiSkeletonGetNextFrame(0, &nowFrame);
NuiTransformSmooth(&nowFrame, NULL);
Mat skeletonimg(240, 320, CV_8UC1, Scalar(0));
Vector4 cpoint[20] = { 0 };
CvPoint cvp[20];
for (int j = 0;j < 20;j++)
{
cpoint[j].x = nowFrame.SkeletonData[userid].SkeletonPositions[j].x;
cpoint[j].y = nowFrame.SkeletonData[userid].SkeletonPositions[j].y;
cpoint[j].z = nowFrame.SkeletonData[userid].SkeletonPositions[j].z;
}
float fx, fy;
for (int i = 0;i < 20;i++)
{
NuiTransformSkeletonToDepthImage(cpoint[i], &fx, &fy);
cvp[i].x = (int)fx;
cvp[i].y = (int)fy;
}
drawSkeleton(skeletonimg, cvp,nowFrame,userid);
imshow("skeleton", skeletonimg);
process.setInput(pastFrame, nowFrame, frameCounter, userid);
frameCounter++;
}
}
process.processBegin();
Mat mark1(image.size(), CV_8UC3, Scalar(0, 0, 0));
process.classify(mark1);
mark = mark1;
imshow("colorImage", mark1);
waitKey(33);
break;
}
}
}
NuiShutdown();
return 0;
}
kinect对帧的处理
kinect每读入一帧骨骼数据，消除抖动后，与上一帧做差，得到这一帧里发生的位移向量，存入Mat framess(NUM_OF_FRAME,NUM_OF_SKELETONS,CV_32FC3)矩阵中。
与模板的向量余弦计算
获得了NUM_OF_FRAME帧数据，即framess写满了后，计算framess中每一帧的位移向量分别与模板的各帧位移向量的夹角余弦。当前程序里一批读入120帧，framess是120*10*3的结构，匹配用的模板计算后也是120*10*3的结构，两个结构按行求夹角余弦，即30维向量与30维向量的运算。得到的余弦值放入用于动态时间规划的120*120的矩阵中。
根据动态时间规划法匹配
因为对于两个相同的动作，如果他们存在相位差，且无法判断用以匹配的动作的起始点在哪里时，对动态时间规划的矩阵求其各条斜率为1的直线上的矩阵元素的和。要注意这个方法只适合用一对一对应的动态时间规划。
2. 记录并保存模板到本地
//@这个程序就是随便写的专门用来采集模板动作的程序
#include (i);
uchar *pBuffer = (uchar*)(LockedRect.pBits) + i * LockedRect.Pitch;
for (int j = 0; j < image.cols; j++)
{
ptr[3 * j] = pBuffer[4 * j];
ptr[3 * j + 1] = pBuffer[4 * j + 1];
ptr[3 * j + 2] = pBuffer[4 * j + 2];
}
}
imshow("colorImage", image);
pTexture->UnlockRect(0);
NuiImageStreamReleaseFrame(ColorFrameStream, pImageFrame);
cvWaitKey(33);
//
hr = NuiSkeletonGetNextFrame(0, &nowFrame);
NuiTransformSmooth(&nowFrame, 0);
Mat skeletonimg(240, 320, CV_8UC1, Scalar(0));//接下来kinect读取到的骨骼数据转换为深度空间图像后保存在image中
Vector4 cpoint[20] = { 0 };
CvPoint cvp[20];
for (int j = 0;j < 20;j++)//kinect一共获取20个关节的空间坐标
{
cpoint[j].x = nowFrame.SkeletonData[userid].SkeletonPositions[j].x;
cpoint[j].y = nowFrame.SkeletonData[userid].SkeletonPositions[j].y;
cpoint[j].z = nowFrame.SkeletonData[userid].SkeletonPositions[j].z;
}
float fx, fy;
for (int i = 0;i < 20;i++)
{
NuiTransformSkeletonToDepthImage(cpoint[i], &fx, &fy);
cvp[i].x = (int)fx;
cvp[i].y = (int)fy;
}
drawSkeleton(skeletonimg, cvp);//使用函数drawSkeleton将关节的点连成线
imshow("skeleton", skeletonimg);
if (FAILED(hr))
{
cout << "Could not get next skeleton stream " << endl;
return hr;
}
for (int j = 0;j < NUM_OF_SKELETONS;j++)
{
temp.ptr(frameCounter)[3*j] = nowFrame.SkeletonData[userid].SkeletonPositions[j].x;
temp.ptr(frameCounter)[3 * j+1] = nowFrame.SkeletonData[userid].SkeletonPositions[j].y;
temp.ptr(frameCounter)[3 * j+2] = nowFrame.SkeletonData[userid].SkeletonPositions[j].z;
//cout << "model" + int2str(counter) << " frame" + int2str(frameCounter) << "data is: " << nowFrame.SkeletonData[userid].SkeletonPositions[j].x << nowFrame.SkeletonData[userid].SkeletonPositions[j].y << nowFrame.SkeletonData[userid].SkeletonPositions[j].z << endl;
}
}
frameCounter++;
}
FileStorage fs("monitor_file.xml", FileStorage::APPEND);
fs << "mat_id" + int2str(counter) << temp;
fs.release();
counter++;
break;
}
}
if (counter == 3)
getdata = TRUE;
imshow("colorImage", Mat(480, 640, CV_8UC3, Scalar(255, 64, 255)));
waitKey(1000);
}
NuiShutdown();
return 0;
} 使用opencv的FileStorage类生成xml文件
值得一提的是如果直接用WRITE方式连续写三个数据进去，比如：
fs<<”mat_”<< image1<< image2<< image3;
那么读取的时候出现打开了xml文件却读不到任何数据的情况，所以我在外部先把xml用write方式打开，初始化掉，在循环里用append的方式追加写入。