前言
為了減小以后項目的開發效率，本次實驗將OpenNI底層驅動Kinect，OpenCV初步處理OpenNI獲得的原始數據，以及手勢識別中的分割(因為本系統最后是開發手勢識別的)這3個部分的功能單獨做成類，以便以后移植和擴展。其實在前面已經有不少文章涉及到了這3部分的設計，比如說：Kinect+OpenNI學習筆記之3(獲取kinect的數據並在Qt中顯示的類的設計), Kinect+OpenNI學習筆記之11(OpenNI驅動kinect手勢相關的類的設計), Kinect+OpenNI學習筆記之12(簡單手勢所表示的數字的識別) 。這次是綜合前面幾次的設計，優化了下這幾個類。
開發環境：開發環境：QtCreator2.5.1+OpenNI1.5.4.0+Qt4.8.2+OpenCV2.4.3
實驗基礎
OPenNI/OPenCV知識點總結：
Kinect驅動類,OpenCV顯示類和手部預分割類這3個類，單獨來設計其實參考了前面的博文還是很簡單的,但是由於這3個類之間有相互聯系,設計不好就會出現圖像顯示非常卡。這時候，需要注意下面幾點問題（在本程序代碼中，Kinect驅動類為COpenniHand，OpenCV顯示類為CKinectOpenCV, 手部預分割類為CKinectHandSegment）：
因為在kinect驅動類中有完整的kinect驅動程序（這個驅動會占用一部分時間的），而OpenCV顯示類調用了Kinect驅動類中的內容，相當於完成了一次Kinect驅動完整過程，這時候，因為在手部預分割過程中，要獲得手部的中心點，如果在該類中再次執行kinect的驅動來獲得該中心點，那么整個系統中一個流程的時間其kinect需要驅動兩次，這會浪費很多系統資源，導致圖像顯示不流暢等。因此我們應該在OpenCV顯示類中就返回Kinect驅動類中能夠返回的值，比如說手部中心點的位置
在CKinectOpenCV類中由於要返回手部的中心點位置，本打算在類內部公共部分設置一個獲取手部中心點位置的函數的，但是發現如果這個函數的返回值是map類型時，運行時老出錯誤（理論上應該是不會出錯的），所以后面該為直接返回手部中心點的變量（map類型），但是在這個變量返回前要保證它的值是實時更新的，所以應該在返回前加入kinect驅動程序中的Updata函數，我這里將其設計成了一個開關函數，即如果允許獲取手部中心點，就將開關函數中的參數設置為ture，具體參見代碼部分。
C/C++知識點總結：
定義類的對象並使用該對象后，一般會先調用該類的初始化函數，該函數的作用一般是為類成員變量進行一些初始設置，但如果類中其它函數的調用前每次都初始化某些變量時，這些變量的初始化不宜放在類的初始化函數中，而應該單獨給個私有函數，在那些需要調用它的函數前面進行被調用，達到初始化某些變量的目的。
類的設計的目的一是為了方便，而是為了提高效率，有時候不能夠光為了方便而去設計，比如說在本次類設計中要獲得分割好了的圖像，或者原始圖像，或者深度圖像等等，確實是可以直接使用一個函數每一幅圖像，不過每次獲得圖像就要更新一個下kinect驅動中的數據，因此這樣的效率就非常低了，在實際設計中，我把那些kinect驅動設備的程序寫在了一個函數中，但是這個函數又不能被獲取圖像的每個函數去調用，否則還是相當於驅動了多次，因此只能由類所定義的對象來調用了。結果是每一個主函數循環中，我們在定義了類的對象后多調用一個函數，再去獲得所需的圖像，這樣只是多了一句代碼，卻節省了不少時間消耗。
實驗結果
本次實驗完成的功能依舊是獲取kinect的深度圖，顏色圖，手勢分割圖，手勢輪廓圖等。下面是手勢分割圖和輪廓處理圖的結果：
實驗代碼及注釋：
copennihand.h:
#ifndef COpenniHand_H #define COpenniHand_H #include <XnCppWrapper.h> #include <iostream> #include <vector> #include <map> using namespace xn; using namespace std; class COpenniHand { public: COpenniHand(); ~COpenniHand(); /*OpenNI的內部初始化，屬性設置*/ bool Initial(); /*啟動OpenNI讀取Kinect數據*/ bool Start(); /*更新OpenNI讀取到的數據*/ bool UpdateData(); /*得到色彩圖像的node*/ ImageGenerator& getImageGenerator(); /*得到深度圖像的node*/ DepthGenerator& getDepthGenerator(); /*得到手勢姿勢的node*/ GestureGenerator& getGestureGenerator(); /*得到手部的node*/ HandsGenerator& getHandGenerator(); DepthMetaData depth_metadata_; //返回深度圖像數據 ImageMetaData image_metadata_; //返回彩色圖像數據 std::map<XnUserID, XnPoint3D> hand_points_; //為了存儲不同手的實時點而設置的 std::map< XnUserID, vector<XnPoint3D> > hands_track_points_; //為了繪畫后面不同手部的跟蹤軌跡而設定的 private: /*該函數返回真代表出現了錯誤，返回假代表正確*/ bool CheckError(const char* error); /*表示某個手勢動作已經完成檢測的回調函數*/ static void XN_CALLBACK_TYPE CBGestureRecognized(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition, void *pCookie); /*表示檢測到某個手勢開始的回調函數*/ static void XN_CALLBACK_TYPE CBGestureProgress(xn::GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie); /*手部開始建立的回調函數*/ static void XN_CALLBACK_TYPE HandCreate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime, void* pCookie); /*手部開始更新的回調函數*/ static void XN_CALLBACK_TYPE HandUpdate(HandsGenerator& rHands, XnUserID xUID, const XnPoint3D* pPosition, XnFloat fTime, void* pCookie); /*手部銷毀的回調函數*/ static void XN_CALLBACK_TYPE HandDestroy(HandsGenerator& rHands, XnUserID xUID, XnFloat fTime, void* pCookie); XnStatus status_; Context context_; XnMapOutputMode xmode_; ImageGenerator image_generator_; DepthGenerator depth_generator_; GestureGenerator gesture_generator_; HandsGenerator hand_generator_; }; #endif // COpenniHand_H
copennihand.cpp:
#include "copennihand.h" #include <XnCppWrapper.h> #include <iostream> #include <map> using namespace xn; using namespace std; COpenniHand::COpenniHand() { } COpenniHand::~COpenniHand() { } bool COpenniHand::Initial() { status_ = context_.Init(); if(CheckError("Context initial failed!")) { return false; } context_.SetGlobalMirror(true);//設置鏡像 xmode_.nXRes = 640; xmode_.nYRes = 480; xmode_.nFPS = 30; //產生顏色node status_ = image_generator_.Create(context_); if(CheckError("Create image generator error!")) { return false; } //設置顏色圖片輸出模式 status_ = image_generator_.SetMapOutputMode(xmode_); if(CheckError("SetMapOutputMdoe error!")) { return false; } //產生深度node status_ = depth_generator_.Create(context_); if(CheckError("Create depth generator error!")) { return false; } //設置深度圖片輸出模式 status_ = depth_generator_.SetMapOutputMode(xmode_); if(CheckError("SetMapOutputMdoe error!")) { return false; } //產生手勢node status_ = gesture_generator_.Create(context_); if(CheckError("Create gesture generator error!")) { return false; } /*添加手勢識別的種類*/ gesture_generator_.AddGesture("Wave", NULL); gesture_generator_.AddGesture("click", NULL); gesture_generator_.AddGesture("RaiseHand", NULL); gesture_generator_.AddGesture("MovingHand", NULL); //產生手部的node status_ = hand_generator_.Create(context_); if(CheckError("Create hand generaotr error!")) { return false; } //視角校正 status_ = depth_generator_.GetAlternativeViewPointCap().SetViewPoint(image_generator_); if(CheckError("Can't set the alternative view point on depth generator!")) { return false; } //設置與手勢有關的回調函數 XnCallbackHandle gesture_cb; gesture_generator_.RegisterGestureCallbacks(CBGestureRecognized, CBGestureProgress, this, gesture_cb); //設置於手部有關的回調函數 XnCallbackHandle hands_cb; hand_generator_.RegisterHandCallbacks(HandCreate, HandUpdate, HandDestroy, this, hands_cb); return true; } bool COpenniHand::Start() { status_ = context_.StartGeneratingAll(); if(CheckError("Start generating error!")) { return false; } return true; } bool COpenniHand::UpdateData() { status_ = context_.WaitNoneUpdateAll(); if(CheckError("Update date error!")) { return false; } //獲取數據 image_generator_.GetMetaData(image_metadata_); depth_generator_.GetMetaData(depth_metadata_); return true; } ImageGenerator &COpenniHand::getImageGenerator() { return image_generator_; } DepthGenerator &COpenniHand::getDepthGenerator() { return depth_generator_; } GestureGenerator &COpenniHand::getGestureGenerator() { return gesture_generator_; } HandsGenerator &COpenniHand::getHandGenerator() { return hand_generator_; } bool COpenniHand::CheckError(const char *error) { if(status_ != XN_STATUS_OK) { cerr << error << ": " << xnGetStatusString( status_ ) << endl; return true; } return false; } void COpenniHand::CBGestureRecognized(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pIDPosition, const XnPoint3D *pEndPosition, void *pCookie) { COpenniHand *openni = (COpenniHand*)pCookie; openni->hand_generator_.StartTracking(*pEndPosition); } void COpenniHand::CBGestureProgress(GestureGenerator &generator, const XnChar *strGesture, const XnPoint3D *pPosition, XnFloat fProgress, void *pCookie) { } void COpenniHand::HandCreate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie) { COpenniHand *openni = (COpenniHand*)pCookie; XnPoint3D project_pos; openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos); pair<XnUserID, XnPoint3D> hand_point_pair(xUID, XnPoint3D());//在進行pair類型的定義時，可以將第2個設置為空 hand_point_pair.second = project_pos; openni->hand_points_.insert(hand_point_pair);//將檢測到的手部存入map類型的hand_points_中。 pair<XnUserID, vector<XnPoint3D>> hand_track_point(xUID, vector<XnPoint3D>()); hand_track_point.second.push_back(project_pos); openni->hands_track_points_.insert(hand_track_point); } void COpenniHand::HandUpdate(HandsGenerator &rHands, XnUserID xUID, const XnPoint3D *pPosition, XnFloat fTime, void *pCookie) { COpenniHand *openni = (COpenniHand*)pCookie; XnPoint3D project_pos; openni->depth_generator_.ConvertRealWorldToProjective(1, pPosition, &project_pos); openni->hand_points_.find(xUID)->second = project_pos; openni->hands_track_points_.find(xUID)->second.push_back(project_pos); } void COpenniHand::HandDestroy(HandsGenerator &rHands, XnUserID xUID, XnFloat fTime, void *pCookie) { COpenniHand *openni = (COpenniHand*)pCookie; openni->hand_points_.erase(openni->hand_points_.find(xUID)); openni->hands_track_points_.erase(openni->hands_track_points_.find(xUID )); }
ckinectopencv.h:
#ifndef CKINECTOPENCV_H #define CKINECTOPENCV_H #include <opencv2/core/core.hpp> #include "copennihand.h" using namespace cv; class CKinectOpenCV { public: CKinectOpenCV(); ~CKinectOpenCV(); void GetAllInformation(); //在返回有用信息前調用該函數，因為openni的數據在不斷更新，信息的處理最好放在一個函數中 Mat GetColorImage() ; Mat GetDepthImage() ; std::map<XnUserID, XnPoint3D> GetHandPoints(); private: COpenniHand openni_hand_; std::map<XnUserID, XnPoint3D> hand_points_; //為了存儲不同手的實時點而設置的 Mat color_image_; //顏色圖像 Mat depth_image_; //深度圖像 }; #endif // CKINECTOPENCV_H
ckinectopencv.cpp:
#include "ckinectopencv.h" #include <opencv2/imgproc/imgproc.hpp> #include <map> using namespace cv; using namespace std; #define DEPTH_SCALE_FACTOR 255./4096. CKinectOpenCV::CKinectOpenCV() { /*初始化openni對應的設備*/ CV_Assert(openni_hand_.Initial()); /*啟動openni對應的設備*/ CV_Assert(openni_hand_.Start()); } CKinectOpenCV::~CKinectOpenCV() { } void CKinectOpenCV::GetAllInformation() { CV_Assert(openni_hand_.UpdateData()); /*獲取色彩圖像*/ Mat color_image_src(openni_hand_.image_metadata_.YRes(), openni_hand_.image_metadata_.XRes(), CV_8UC3, (char *)openni_hand_.image_metadata_.Data()); cvtColor(color_image_src, color_image_, CV_RGB2BGR); /*獲取深度圖像*/ Mat depth_image_src(openni_hand_.depth_metadata_.YRes(), openni_hand_.depth_metadata_.XRes(), CV_16UC1, (char *)openni_hand_.depth_metadata_.Data());//因為kinect獲取到的深度圖像實際上是無符號的16位數據 depth_image_src.convertTo(depth_image_, CV_8U, DEPTH_SCALE_FACTOR); hand_points_ = openni_hand_.hand_points_; //返回手部點的位置 return; } Mat CKinectOpenCV::GetColorImage() { return color_image_; } Mat CKinectOpenCV::GetDepthImage() { return depth_image_; } std::map<XnUserID, XnPoint3D> CKinectOpenCV::GetHandPoints() { return hand_points_; }
ckinecthandsegment.h:
#ifndef KINECTHAND_H #define KINECTHAND_H #include "ckinectopencv.h" using namespace cv; #define MAX_HANDS_COLOR 10 #define MAX_HANDS_NUMBER 10 class CKinectHandSegment { public: CKinectHandSegment(); ~CKinectHandSegment(); void Initial(); void StartKinectHand(); //啟動kinect手部設備驅動 Mat GetColorImageWithHandsPoint(); Mat GetHandSegmentImage(); Mat GetHandHandlingImage(); Mat GetColorImage(); Mat GetDepthImage(); private: CKinectOpenCV kinect_opencv_; vector<Scalar> hand_center_color_array_;//采用默認的10種顏色 std::map<XnUserID, XnPoint3D> hand_points_; vector<unsigned int> hand_depth_; vector<Rect> hands_roi_; bool hand_segment_flag_; Mat color_image_with_handspoint_; //帶有手部中心位置的色彩圖 Mat color_image_; //色彩圖 Mat depth_image_; Mat hand_segment_image_; Mat hand_handling_image_; Mat hand_segment_mask_; }; #endif // KINECTHAND_H
ckinecthandsegment.cpp:
#include <opencv2/core/core.hpp> #include <opencv2/imgproc/imgproc.hpp> #include "ckinecthandsegment.h" #include "copennihand.h" #include "ckinectopencv.h" using namespace cv; using namespace std; #define DEPTH_SCALE_FACTOR 255./4096. #define ROI_HAND_WIDTH 140 #define ROI_HAND_HEIGHT 140 #define MEDIAN_BLUR_K 5 #define XRES 640 #define YRES 480 #define DEPTH_SEGMENT_THRESH 5 #define HAND_LIKELY_AREA 2000 CKinectHandSegment::CKinectHandSegment() { } CKinectHandSegment::~CKinectHandSegment() { } void CKinectHandSegment::Initial() { color_image_with_handspoint_ = kinect_opencv_.GetColorImage(); depth_image_ = kinect_opencv_.GetDepthImage(); { hand_center_color_array_.push_back(Scalar(255, 0, 0)); hand_center_color_array_.push_back(Scalar(0, 255, 0)); hand_center_color_array_.push_back(Scalar(0, 0, 255)); hand_center_color_array_.push_back(Scalar(255, 0, 255)); hand_center_color_array_.push_back(Scalar(255, 255, 0)); hand_center_color_array_.push_back(Scalar(0, 255, 255)); hand_center_color_array_.push_back(Scalar(128, 255, 0)); hand_center_color_array_.push_back(Scalar(0, 128, 255)); hand_center_color_array_.push_back(Scalar(255, 0, 128)); hand_center_color_array_.push_back(Scalar(255, 128, 255)); } vector<unsigned int> hand_depth_temp(MAX_HANDS_NUMBER, 0); hand_depth_ = hand_depth_temp; vector<Rect> hands_roi_temp(MAX_HANDS_NUMBER, Rect(XRES/2, YRES/2, ROI_HAND_WIDTH, ROI_HAND_HEIGHT)); hands_roi_ = hands_roi_temp; } void CKinectHandSegment::StartKinectHand() { kinect_opencv_.GetAllInformation(); } Mat CKinectHandSegment::GetColorImage() { return kinect_opencv_.GetColorImage(); } Mat CKinectHandSegment::GetDepthImage() { return kinect_opencv_.GetDepthImage(); } /*該函數只是在Kinect獲取的色彩圖片上將手的中心點位置畫出來而已，圖片的其它地方不變*/ Mat CKinectHandSegment::GetColorImageWithHandsPoint() { color_image_with_handspoint_ = kinect_opencv_.GetColorImage(); hand_points_ = kinect_opencv_.GetHandPoints(); for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) { circle(color_image_with_handspoint_, Point(itUser->second.X, itUser->second.Y), 5, hand_center_color_array_.at(itUser->first % hand_center_color_array_.size()), 3, 8); } return color_image_with_handspoint_; } Mat CKinectHandSegment::GetHandSegmentImage() { hand_segment_flag_ = false; color_image_ = kinect_opencv_.GetColorImage(); depth_image_ = kinect_opencv_.GetDepthImage(); hand_points_ = kinect_opencv_.GetHandPoints(); hand_segment_mask_ = Mat::zeros(color_image_.size(), CV_8UC1); // 因為zeros是一個靜態函數，所以不能直接用具體的對象去調用，而需要用類來調用 for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) { /*設置不同手部的深度*/ hand_depth_.at(itUser->first % MAX_HANDS_COLOR) = (unsigned int)(itUser->second.Z* DEPTH_SCALE_FACTOR);//itUser->first會導致程序出現bug /*設置不同手部的不同感興趣區域*/ hands_roi_.at(itUser->first % MAX_HANDS_NUMBER) = Rect(itUser->second.X - ROI_HAND_WIDTH/2, itUser->second.Y - ROI_HAND_HEIGHT/2, ROI_HAND_WIDTH, ROI_HAND_HEIGHT); hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x = itUser->second.X - ROI_HAND_WIDTH/2; hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y = itUser->second.Y - ROI_HAND_HEIGHT/2; hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).width = ROI_HAND_WIDTH; hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).height = ROI_HAND_HEIGHT; if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x <= 0) hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x = 0; if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x > XRES) hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x = XRES; if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y <= 0) hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y = 0; if(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y > YRES) hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y = YRES; } //取出手的mask部分,不管原圖像時多少通道的，mask矩陣聲明為單通道就ok for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) { for(int i = hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x; i < min(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).x+hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).width, XRES); i++) for(int j = hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y; j < min(hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).y+hands_roi_.at(itUser->first % MAX_HANDS_NUMBER).height, YRES); j++) { hand_segment_mask_.at<unsigned char>(j, i) = ((hand_depth_.at(itUser->first % MAX_HANDS_NUMBER)-DEPTH_SEGMENT_THRESH) < depth_image_.at<unsigned char>(j, i)) & ((hand_depth_.at(itUser->first % MAX_HANDS_NUMBER)+DEPTH_SEGMENT_THRESH) > depth_image_.at<unsigned char>(j,i)); hand_segment_mask_.at<unsigned char>(j, i) = 255*hand_segment_mask_.at<unsigned char>(j, i); } } medianBlur(hand_segment_mask_, hand_segment_mask_, MEDIAN_BLUR_K); hand_segment_image_.convertTo(hand_segment_image_, CV_8UC3, 0, 0 ); // 需要清零 color_image_.copyTo(hand_segment_image_, hand_segment_mask_); hand_segment_flag_ = true; //返回之前將分割標志置位為1，表示已經完成分割函數 return hand_segment_image_; } Mat CKinectHandSegment::GetHandHandlingImage() { /*對mask圖像進行輪廓提取,並在手勢識別圖像中畫出來*/ std::vector< std::vector<Point> > contours; CV_Assert(hand_segment_flag_); // 因為后面要用到分割函數的mask圖，所以這里先要保證調用過分割函數 findContours(hand_segment_mask_, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);//找出mask圖像的輪廓 hand_handling_image_ = Mat::zeros(color_image_.rows, color_image_.cols, CV_8UC3); for(int i = 0; i < contours.size(); i++) { //只有在檢測到輪廓時才會去求它的多邊形，凸包集，凹陷集 /*找出輪廓圖像多邊形擬合曲線*/ Mat contour_mat = Mat(contours[i]); if(contourArea(contour_mat) > HAND_LIKELY_AREA) { //比較有可能像手的區域 std::vector<Point> approx_poly_curve; approxPolyDP(contour_mat, approx_poly_curve, 10, true);//找出輪廓的多邊形擬合曲線 std::vector< std::vector<Point> > approx_poly_curve_debug; approx_poly_curve_debug.push_back(approx_poly_curve); drawContours(hand_handling_image_, contours, i, Scalar(255, 0, 0), 1, 8); //畫出輪廓 // drawContours(hand_handling_image_, approx_poly_curve_debug, 0, Scalar(256, 128, 128), 1, 8); //畫出多邊形擬合曲線 /*對求出的多邊形擬合曲線求出其凸包集*/ vector<int> hull; convexHull(Mat(approx_poly_curve), hull, true); for(int i = 0; i < hull.size(); i++) { circle(hand_handling_image_, approx_poly_curve[hull[i]], 2, Scalar(0, 255, 0), 2, 8); } /*對求出的多邊形擬合曲線求出凹陷集*/ std::vector<Vec4i> convexity_defects; if(Mat(approx_poly_curve).checkVector(2, CV_32S) > 3) convexityDefects(approx_poly_curve, Mat(hull), convexity_defects); for(int i = 0; i < convexity_defects.size(); i++) { circle(hand_handling_image_, approx_poly_curve[convexity_defects[i][2]] , 2, Scalar(0, 0, 255), 2, 8); } } } /**畫出手勢的中心點**/ for(auto itUser = hand_points_.cbegin(); itUser != hand_points_.cend(); ++itUser) { circle(hand_handling_image_, Point(itUser->second.X, itUser->second.Y), 3, Scalar(0, 255, 255), 3, 8); } return hand_handling_image_; }
main.cpp:
#include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "ckinectopencv.h" #include "ckinecthandsegment.h" using namespace std; using namespace cv; int main() { CKinectHandSegment kinect_hand_segment; Mat color_image ; Mat depth_image ; Mat hand_segment; Mat hand_handling_image; kinect_hand_segment.Initial(); while(1) { kinect_hand_segment.StartKinectHand(); color_image = kinect_hand_segment.GetColorImageWithHandsPoint(); hand_segment = kinect_hand_segment.GetHandSegmentImage(); hand_handling_image = kinect_hand_segment.GetHandHandlingImage(); depth_image = kinect_hand_segment.GetDepthImage(); imshow("color_image", color_image); imshow("depth_image", depth_image); imshow("hand_segment", hand_segment); imshow("hand_handling", hand_handling_image); waitKey(30); } return 0; }
實驗總結：把這些基本功能類設計好了后，就可以更方面測試我后面的手勢識別算法了，加油！
參考資料：
Kinect+OpenNI學習筆記之3(獲取kinect的數據並在Qt中顯示的類的設計)
Kinect+OpenNI學習筆記之11(OpenNI驅動kinect手勢相關的類的設計)
Kinect+OpenNI學習筆記之12(簡單手勢所表示的數字的識別)