2011-4-10 增加结果图片，更新代码，将模板改为6个（0-5）
1，原理：读入KINECT深度数据，转换为二值图像，找到轮廓，与轮廓模板比较，找到HU矩阵最小的为匹配结果
2，基础：OPENNI, OPENCV2.2 以及http://blog.163.com/gz_ricky/blog/static/182049118201122311118325/
的例程基础上修改
3，结果：仅仅用于演示利用OPENCV+OPENNI编程，对结果精度，处理速度等没有优化，仅供参考
对0，1和5的比较比较准确
废话少说，一切都在代码中。
Hand detection
1 // KinectOpenCVTest.cpp : 定义控制台应用程序的入口点。
2 //
3
4 #include "stdafx.h"
5
6
7 #include <stdlib.h>
8 #include <iostream>
9 #include <string>
10 #include <XnCppWrapper.h>
11 #include <opencv2/opencv.hpp>
12
13 //#include "opencv/cv.h"
14 //#include "opencv/highgui.h"
15 using namespace std;
16 using namespace cv;
17
18 #define SAMPLE_XML_PATH "http://www.cnblogs.com/Data/SamplesConfig.xml"
19
20 //全局模板轮廓
21 vector<vector<Point>> g_TemplateContours;
22
23 //模板个数
24 int g_handTNum = 6;
25
26 void CheckOpenNIError( XnStatus eResult, string sStatus )
27 {
28 if( eResult != XN_STATUS_OK )
29 {
30 cerr << sStatus << " Error: " << xnGetStatusString( eResult ) << endl;
31 return;
32 }
33 }
34
35 //载入模板的轮廓
36 void init_hand_template()
37 {
38 //int handTNum = 10;
39 string temp = "HandTemplate/";
40
41 int i = 0;
42
43
44 for(i=0; i<g_handTNum; i++)
45 {
46 stringstream ss;
47 ss << i << ".bmp";
48
49 string fileName = temp + ss.str();
50
51 //读入灰度图像
52 Mat src = imread(fileName, 0);
53
54 if(!src.data)
55 {
56 printf("未找到文件: %s\n", fileName);
57 continue;
58 }
59
60 vector<vector<Point>> contours;
61 vector<Vec4i> hierarchy;
62
63 findContours(src, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
64 //findContours(src, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
65
66 g_TemplateContours.push_back(contours[0]);
67 }
68 }
69
70 //模板匹配手
71 int hand_template_match(Mat& hand)
72 {
73 //int handTNum = 10;
74 int minId = -1;
75 double minHu = 1;
76
77 double hu;
78 int method = CV_CONTOURS_MATCH_I1;
79
80 //match_num = 0;
81
82 for(int i=0; i<g_handTNum; i++){
83
84 Mat temp(g_TemplateContours.at(i));
85 hu = matchShapes(temp, hand, method, 0);
86
87 //找到hu矩最小的模板
88 if(hu < minHu){
89 minHu = hu;
90 minId = i;
91 }
92
93 //printf("%f ", hu);
94 }
95
96 //显示匹配结果
97 int Hmatch_value = 25;//模板匹配系数
98
99 if(minHu<((double)Hmatch_value)/100)
100 return minId;
101 else
102 return -1;
103 }
104
105 void findHand(Mat& src, Mat& dst)
106 {
107 vector<vector<Point>> contours;
108 vector<Vec4i> hierarchy;
109
110 //找到外部轮廓
111 //findContours(src, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
112 findContours(src, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE); //CV_CHAIN_APPROX_NONE);
113 //findContours(src, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
114
115 Mat dst_r = Mat::zeros(src.rows, src.cols, CV_8UC3);
116 dst_r.copyTo(dst);
117
118 // iterate through all the top-level contours,
119 // draw each connected component with its own random color
120 int idx = 0;
121 double maxArea = 0.0;
122 int maxId = -1;
123
124 for(unsigned int i = 0; i<contours.size(); i++)
125 {
126 Mat temp(contours.at(i));
127 double area = fabs(contourArea(temp));
128 if(area > maxArea)
129 {
130 maxId = i;
131 maxArea = area;
132 }
133 }
134
135 //for( ; idx >= 0; idx = hierarchy[idx][0] )
136 //{
137 // //Scalar color( rand()&255, rand()&255, rand()&255 );
138 // //drawContours(dst, contours, idx, color, CV_FILLED, 8, hierarchy );
139
140 // double area = contourArea(contours.at(idx));
141 // if(area > maxArea)
142 // {
143 // maxId = idx;
144 // maxArea = area;
145 // }
146 //}
147
148 //显示最大轮廓外形，以及最佳匹配的模板ID
149 if(contours.size() > 0)
150 {
151 Scalar color(0, 255, 255 );
152 drawContours(dst, contours, maxId, color);
153
154 Mat hand(contours.at(maxId));
155 int value = hand_template_match(hand);
156
157 if(value >= 0)
158 {
159 Scalar templateColor(255, 0, 255 );
160 drawContours(dst, g_TemplateContours, value, templateColor);
161
162 printf("Match %d \r\n", value);
163
164 stringstream ss;
165 ss << "Match " << value;
166 string text = ss.str();
167 putText(dst, text, Point(300, 30), FONT_HERSHEY_SIMPLEX, 1.0, templateColor);
168 }
169 }
170 }
171
172
173 int HandDetect()
174 {
175 init_hand_template();
176
177 XnStatus eResult = XN_STATUS_OK;
178
179 // 1. initial val
180 xn::DepthMetaData m_DepthMD;
181 xn::ImageMetaData m_ImageMD;
182
183 // for opencv Mat
184 Mat m_depth16u( 480,640,CV_16UC1);
185 Mat m_rgb8u( 480,640,CV_8UC3);
186 Mat m_DepthShow( 480,640,CV_8UC1);
187 Mat m_ImageShow( 480,640,CV_8UC3);
188
189 Mat m_DepthThreshShow( 480,640,CV_8UC1);
190 Mat m_HandShow( 480,640,CV_8UC3);
191
192 //cvNamedWindow("depth");
193 //cvNamedWindow("image");
194 //cvNamedWindow("depthThresh");
195
196 char key=0;
197
198 // 2. initial context
199 xn::Context mContext;
200
201 eResult = mContext.Init();
202
203 //xn::EnumerationErrors errors;
204 //eResult = mContext.InitFromXmlFile(SAMPLE_XML_PATH, &errors);
205
206 CheckOpenNIError( eResult, "initialize context" );
207
208 //Set mirror
209 mContext.SetGlobalMirror(!mContext.GetGlobalMirror());
210
211 // 3. create depth generator
212 xn::DepthGenerator mDepthGenerator;
213 eResult = mDepthGenerator.Create( mContext );
214 CheckOpenNIError( eResult, "Create depth generator" );
215
216 // 4. create image generator
217 xn::ImageGenerator mImageGenerator;
218 eResult = mImageGenerator.Create( mContext );
219 CheckOpenNIError( eResult, "Create image generator" );
220
221 // 5. set map mode
222 XnMapOutputMode mapMode;
223 mapMode.nXRes = 640;
224 mapMode.nYRes = 480;
225 mapMode.nFPS = 30;
226 eResult = mDepthGenerator.SetMapOutputMode( mapMode );
227 eResult = mImageGenerator.SetMapOutputMode( mapMode );
228
229 //由于 Kinect 的深度摄像机和彩色摄像机是在不同的位置，而且镜头本身的参数也不完全相同，所以两个摄像机所取得的画面会有些微的差异
230 //将深度摄像机的视角调整到RGB摄像机位置
231 // 6. correct view port
232 mDepthGenerator.GetAlternativeViewPointCap().SetViewPoint( mImageGenerator );
233
234 // 7. start generate data
235 eResult = mContext.StartGeneratingAll();
236
237 // 8. read data
238 eResult = mContext.WaitNoneUpdateAll();
239 while( (key!=27) && !(eResult = mContext.WaitNoneUpdateAll( )) )
240 {
241 // 9a. get the depth map
242 mDepthGenerator.GetMetaData(m_DepthMD);
243 memcpy(m_depth16u.data,m_DepthMD.Data(), 640*480*2);
244
245 // 9b. get the image map
246 mImageGenerator.GetMetaData(m_ImageMD);
247 memcpy(m_rgb8u.data,m_ImageMD.Data(),640*480*3);
248
249 //将未知深度转为白色，便于在OPENCV中分析
250 XnDepthPixel* pDepth = (XnDepthPixel*)m_depth16u.data;
251
252 for (XnUInt y = 0; y < m_DepthMD.YRes(); ++y)
253 {
254 for (XnUInt x = 0; x < m_DepthMD.XRes(); ++x, ++pDepth)
255 {
256 if (*pDepth == 0)
257 {
258 *pDepth = 0xFFFF;
259 }
260 }
261 }
262
263
264 //由于OpenNI获得的深度图片是16位无符号整数，而OpenCV显示的是8位的，所以要作转换。
265
266 //将距离转换为灰度值（0-2550mm 转换到 0-255），例如1000毫米转换为 1000×255/2550 = 100
267 //m_depth16u.convertTo(m_DepthShow,CV_8U, 255/2096.0);
268 m_depth16u.convertTo(m_DepthShow,CV_8U, 255/2550.0);
269
270 //可以考虑根据数据缩减图像大小到有效范围
271
272 //在此对灰度图像进行处理，平滑和去噪声
273 //medianBlur(m_DepthShow, m_DepthThreshShow, 3);
274 //m_DepthThreshShow.copyTo(m_DepthShow);
275 //medianBlur(m_DepthThreshShow, m_DepthShow, 3);
276 blur(m_DepthShow, m_DepthThreshShow, Size(3, 3));
277 //m_DepthThreshShow.copyTo(m_DepthShow);
278 blur(m_DepthThreshShow, m_DepthShow, Size(3, 3));
279
280 Mat pyrTemp( 240,320,CV_8UC1);
281 pyrDown(m_DepthShow, pyrTemp);
282 pyrUp(pyrTemp, m_DepthShow);
283
284 //dilate(m_DepthShow, m_DepthThreshShow, Mat(), Point(-1,-1), 3);
285 //erode(m_DepthThreshShow, m_DepthShow, Mat(), Point(-1,-1), 3);
286
287 //for(int i = 0; i < m_depth16u.rows; i++)
288 // for(int j = 0; j < m_depth16u.cols; j++)
289 // {
290 // if(m_depth16u.at<unsigned short>(i,j) < 1)
291 // m_depth16u.at<unsigned short>(i,j) == 0xFFFF;
292
293 // //m_depth16u.at<double>(i,j)=1./(i+j+1);
294 // }
295
296 //RGB和BGR在内存对应的位置序列不同，所以也要转换。
297 cvtColor(m_rgb8u,m_ImageShow,CV_RGB2BGR);
298
299 //imshow("depth", m_DepthShow);
300 //imshow("image", m_ImageShow);
301
302 double thd_max = 0xFFFF;
303 double thd_val = 100.0;
304
305 //反转黑白图像，以便找到最大外部轮廓
306 //threshold(m_DepthShow, m_DepthThreshShow, thd_val, thd_max, CV_THRESH_BINARY);
307 threshold(m_DepthShow, m_DepthThreshShow, thd_val, thd_max, CV_THRESH_BINARY_INV);
308 imshow("depthThresh", m_DepthThreshShow);
309
310 findHand(m_DepthThreshShow, m_HandShow);
311 imshow( "Hand", m_HandShow );
312
313 key=cvWaitKey(20);
314 }
315
316 // 10. stop
317 mContext.StopGeneratingAll();
318 mContext.Shutdown();
319
320 return 0;
321 }
322
323 int _tmain(int argc, _TCHAR* argv[])
324 {
325 HandDetect();
326 }
trackback: http://blog.csdn.net/firefight/archive/2011/04/06/6304050.aspx