ubuntu14.04安装OpenNI2+驱动XTion PRO Live

来源：互联网发布：淘宝网店出售编辑：程序博客网时间：2024/05/19 02:26

这篇博客将为大家介绍如何在ubuntu14.04下安装OpenNI2，以及驱动华硕的深度摄像头XTion PRO Live。

经过几天搜索资料，发现网上关于安装OpenNI2资料还是较少而且很乱，今天经过测试，终于成功读取XTion摄像头的数据并将其生成点云。

好了，废话少说，正式进入主题

事先准备：
系统：Ubuntu 14.04
摄像头：华硕XTion Pro Live

一、安装OPenNI2

1、安装依赖项

sudo apt-get install -y g++ git python libusb-1.0-0-dev libudev-dev freeglut3-dev doxygen graphviz openjdk-6-jdk

2、创建一个新的文件夹，用于存放从github下载下来的OpenNI2,并移到此文件夹下

mkdir ~/openni2cd ~/openni2

3、从GitHub下载OpenNI2的代码

git clone https://github.com/occipital/OpenNI2.git

4、进入OpenNI2文件夹

cd OpenNI2

5、运行下面代码

find . -iname platform.arm

终端会输出以下信息：
./ThirdParty/PSCommon/BuildSystem/Platform.Arm
6、运行gedit，打开Platform.Arm文件进行修改

gedit ./ThirdParty/PSCommon/BuildSystem/Platform.Arm

找到：
CFLAGS += -march=armv7-a -mtune=cortex-a8 -mfpu=neon -mfloat-abi=hard
修改为：
CFLAGS += -march=armv7-a -mtune=cortex-a15 -mfpu=neon-vfpv4 -mfloat-abi=hard
如下图所示：
这里写图片描述
7、打开gedit，修改CommonCppMakefile文件

gedit ThirdParty/PSCommon/BuildSystem/CommonCppMakefile

找到这两行：
LDFLAGS += -Wl,-rpath ./
OUTPUT_COMMAND = (CXX)−o(OUTPUT_FILE) (OBJFILES)(LDFLAGS)
在这两行代码中间加入以下代码：

ifneq (“$(OSTYPE)”,”Darwin”)    LDFLAGS += -lpthreadendif

如下图所示：
这里写图片描述
保存退出。
8、添加例程以检查安装是否正确

gedit Makefile

在文件末尾添加：

core_samples: $(CORE_SAMPLES)

如下图：
这里写图片描述
保存退出。
9、开始编译

makemake core_samplesGLUT_SUPPORTED=1 make tools

二、OpenNI2测试
1、进入例程所在文件夹

cd ~/openni2/OpenNI2/Bin/x64-Release

2、连接Xtion Pro Live到你的电脑
3、测试例程“SimpleRead”:

./SimpleRead

不出意外，在这里你应该能够看到终端很多数据在更新，当你移动摄像头时，数据会发生明显变化
如下图所示：
这里写图片描述
4、测试例程“NiViewer”:

./NiViewer

这是你应该能够看到深度图了
如下图所示：
这里写图片描述

三、正式安装OpenNI2
1、进入Packaging文件夹

cd ~/openni2/OpenNI2/Packaging/Linux

2、运行安装脚本

sudo sh install.sh

3、将“lib”文件和“include”文件复制到系统路径下

cd ~/openni2/OpenNI2sudo cp -r Include /usr/include/openni2sudo cp -r Bin/x64-Release/OpenNI2 /usr/lib/sudo cp Bin/x64-Release/libOpenNI2.* /usr/lib/

4、更新 library cache:

sudo ldconfig

5、设置传感器权限

sudo usermod -a -G video Ubuntu

注意，Ubuntu为你的用户名
6、创建一个包配置文件

sudo gedit /usr/lib/pkgconfig/libopenni2.pc

7、用一下代码覆盖

prefix=/usrexec_prefix=${prefix}libdir=${exec_prefix}/libincludedir=${prefix}/include/openni2Name: OpenNI2Description: A general purpose driver for all OpenNI cameras.Version: 2.2.0.0Cflags: -I${includedir}Libs: -L${libdir} -lOpenNI2 -L${libdir}/OpenNI2/Drivers -lDummyDevice -lOniFile -lPS1080.so

8、确保其能被正确找到，运行：

pkg-config --modversion libopenni2

此时，终端会有2.2.0.0回复
如下图所示：
这里写图片描述

至此，OpenNI2已经安装好了，并可以驱动Xtion了

四、测试
那么接下来就是测试一下，看看能否读取Xtion摄像头，并将其生成点云（前提有安装Opencv-2.4.9和PCL1.7）
1、新建一个test文件夹并移至该文件夹

mkdir ~/testcd ~/test

2、再新建一个build文件夹，用于存放编译文件

mkdir build

3、在test文件夹新建CMakeLists.txt

# This CmakeLists include both OpenNI and OpenCV Libraries  cmake_minimum_required(VERSION 2.8)  project( TestOpenNI )  # OpenCV  find_package( OpenCV REQUIRED )  include_directories( ${OpenCV_INCLUDE_DIRS} )  MESSAGE(STATUS "The Opencv's include directory is:" ${OpenCV_INCLUDE_DIRS})  #OpenNI  FIND_PATH(OpenNI2_INCLUDE_DIRS OpenNI.h HINTS  $ENV{OPENNI2_INCLUDE} PATH_SUFFIXES openni2)  FIND_LIBRARY(OpenNI2_LIBRARY NAMES OpenNI2 HINTS  $ENV{OPENNI2_LIB} $ENV{OPENNI2_REDIST})  include_directories( ${OpenNI2_INCLUDE_DIRS} )  IF (OpenNI2_INCLUDE_DIRS AND OpenNI2_LIBRARY)     SET(OpenNI2_FOUND TRUE)  ENDIF (OpenNI2_INCLUDE_DIRS AND OpenNI2_LIBRARY)  IF (OpenNI2_FOUND)     # show which OpenNI2 was found only if not quiet     SET(OpenNI2_LIBRARIES ${OpenNI2_LIBRARY})     MESSAGE(STATUS "Found OpenNI2: ${OpenNI2_LIBRARIES}")  ELSE (OpenNI2_FOUND)     # fatal error if OpenNI2 is required but not found     IF (OpenNI2_FIND_REQUIRED)        MESSAGE(FATAL_ERROR "Could not find OpenNI2. Environment variables OPENNI2_INCLUDE (directory containing OpenNI.h) and OPENNI2_LIB (directory containing OpenNI2 library) could bet set.")     ENDIF (OpenNI2_FIND_REQUIRED)  ENDIF (OpenNI2_FOUND)  set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")  #set (OPENNI_H /usr/include/openni2/OpenNI.h)  # ---------------------------------------------------------  #PCL  find_package(PCL 1.8 REQUIRED)  include_directories(${PCL_INCLUDE_DIRS})  link_directories(${PCL_LIBRARY_DIRS})  add_definitions(${PCL_DEFINITIONS})  add_executable(TestOpenNI test.cpp)  target_link_libraries(TestOpenNI ${OpenNI2_LIBRARIES} ${OpenCV_LIBS} ${PCL_COMMON_LIBRARIES} ${PCL_IO_LIBRARIES})

4、在build文件夹下新建TestOpenNI.cpp

#include <pcl/io/pcd_io.h>  #include <pcl/io/ply_io.h>  #include <pcl/point_types.h>  // 标准库头文件  #include <iostream>  #include <string>  #include <vector>   // OpenCV头文件  #include <opencv2/photo.hpp>  #include <opencv2/highgui.hpp>   // OpenNI头文件  #include <OpenNI.h>   typedef unsigned char uint8_t;  // namespace  using namespace std;  using namespace openni;  using namespace cv;  using namespace pcl;  void CheckOpenNIError( Status result, string status )    {         if( result != STATUS_OK )             cerr << status << " Error: " << OpenNI::getExtendedError() << endl;    }   int main( int argc, char **argv )  {      Status result = STATUS_OK;      int i,j;      float x=0.0,y=0.0,z=0.0,xx=0.0;        //IplImage *test,*test2;      IplImage *test2;      char filename[20] = {0};      //point cloud       PointCloud<PointXYZ> cloud;      PointCloud<PointXYZRGB> color_cloud;      //opencv image      Mat cvBGRImg;       Mat cvDepthImg;        //OpenNI2 image        VideoFrameRef oniDepthImg;        VideoFrameRef oniColorImg;      namedWindow("depth");        namedWindow("image");       char key=0;      // 初始化OpenNI        result = OpenNI::initialize();      CheckOpenNIError( result, "initialize context" );       // open device          Device device;        result = device.open( openni::ANY_DEVICE );       CheckOpenNIError( result, "open device" );      // create depth stream         VideoStream oniDepthStream;        result = oniDepthStream.create( device, openni::SENSOR_DEPTH );      CheckOpenNIError( result, "create depth stream" );      // set depth video mode        VideoMode modeDepth;        modeDepth.setResolution( 640, 480 );        modeDepth.setFps( 30 );        modeDepth.setPixelFormat( PIXEL_FORMAT_DEPTH_1_MM );        oniDepthStream.setVideoMode(modeDepth);        // start depth stream        result = oniDepthStream.start();       CheckOpenNIError( result, "start depth stream" );      // create color stream        VideoStream oniColorStream;        result = oniColorStream.create( device, openni::SENSOR_COLOR );        CheckOpenNIError( result, "create color stream" );      // set color video mode        VideoMode modeColor;        modeColor.setResolution( 640, 480 );        modeColor.setFps( 30 );        modeColor.setPixelFormat( PIXEL_FORMAT_RGB888 );        oniColorStream.setVideoMode( modeColor);       // start color stream        result = oniColorStream.start();       CheckOpenNIError( result, "start color stream" );      int count = 0;      while(true)      {          // read frame            if( oniColorStream.readFrame( &oniColorImg ) == STATUS_OK )            {                // convert data into OpenCV type                Mat cvRGBImg( oniColorImg.getHeight(), oniColorImg.getWidth(), CV_8UC3, (void*)oniColorImg.getData() );                cvtColor( cvRGBImg, cvBGRImg, CV_RGB2BGR );                imshow( "image", cvBGRImg );            }            if( oniDepthStream.readFrame( &oniDepthImg ) == STATUS_OK )            {                Mat cvRawImg16U( oniDepthImg.getHeight(), oniDepthImg.getWidth(), CV_16UC1, (void*)oniDepthImg.getData() );                cvRawImg16U.convertTo( cvDepthImg, CV_8U, 255.0/(oniDepthStream.getMaxPixelValue()));                  imshow( "depth", cvDepthImg );            }       char input = waitKey(1);           // quit          if( input == 'q' )                    break;          // capture  depth and color data             if( input == 'c' )          {              //get data              DepthPixel *pDepth = (DepthPixel*)oniDepthImg.getData();              //create point cloud              cloud.width = oniDepthImg.getWidth();              cloud.height = oniDepthImg.getHeight();              cloud.is_dense = false;              cloud.points.resize(cloud.width * cloud.height);              color_cloud.width = oniDepthImg.getWidth();              color_cloud.height = oniDepthImg.getHeight();              color_cloud.is_dense = false;              color_cloud.points.resize(color_cloud.width * color_cloud.height);              //test = cvCreateImage(cvSize(cloud.width,cloud.height),IPL_DEPTH_8U,3);              IplImage temp11 = (IplImage)cvBGRImg;              //test2 = &IplImage(cvBGRImg);              test2 = &temp11;                          for(i=0;i<oniDepthImg.getHeight();i++)              {                   for(j=0;j<oniDepthImg.getWidth();j++)                   {                       float k = i;                         float m = j;                        xx = pDepth[i*oniDepthImg.getWidth()+j];                       CoordinateConverter::convertDepthToWorld (oniDepthStream,m,k,xx,&x,&y,&z);                        cloud[i*cloud.width+j].x = x/1000;                       cloud[i*cloud.width+j].y = y/1000;                       cloud[i*cloud.width+j].z = z/1000;                       color_cloud[i*cloud.width+j].x = x/1000;                       color_cloud[i*cloud.width+j].y = y/1000;                       color_cloud[i*cloud.width+j].z = z/1000;                       color_cloud[i*cloud.width+j].b = (uint8_t)test2->imageData[i*test2->widthStep+j*3+0];                       color_cloud[i*cloud.width+j].g = (uint8_t)test2->imageData[i*test2->widthStep+j*3+1];                       color_cloud[i*cloud.width+j].r = (uint8_t)test2->imageData[i*test2->widthStep+j*3+2];                      /* test->imageData[i*test->widthStep+j*3+0] = test2->imageData[i*test2->widthStep+j*3+0];                       test->imageData[i*test->widthStep+j*3+1] = test2->imageData[i*test2->widthStep+j*3+1];                       test->imageData[i*test->widthStep+j*3+2] = test2->imageData[i*test2->widthStep+j*3+2];*/                   }               }              //cvSaveImage("test.jpg",test);              //pcl::io::savePLYFileBinary("test_plyc.ply",cloud);              cout<<"the "<<count<<" is saved"<<endl;              sprintf(filename,"./data/%d.pcd",count);              pcl::io::savePCDFileBinaryCompressed(filename,cloud);              cerr<<"Saved "<<cloud.points.size()<<" data points to xyz pcd."<<endl;              sprintf(filename,"./data/color_%d.pcd",count);              pcl::io::savePCDFileBinaryCompressed(filename,color_cloud);              cerr<<"Saved "<<color_cloud.points.size()<<" data points to xyzrgb pcd."<<endl;              sprintf(filename,"./data/color_%d.jpg",count);              imwrite(filename,cvBGRImg);              sprintf(filename,"./data/depth_%d.jpg",count++);              imwrite(filename,cvDepthImg);              /*for(size_t i=0;i<cloud.points.size();++i)              cerr<<"    "<<cloud.points[i].x<<" "<<cloud.points[i].y<<" "<<cloud.points[i].z<<endl;*/          }      }  }

5、在build的文件夹下进行编译

cmake ..make

不出问题在build的文件夹下就能产生可执行文件TestOpenNI
6、运行可执行文件TestOpenNI
如下图：
这里写图片描述

主要参考blog：
http://myzharbot.robot-home.it/blog/software/configuration-nvidia-jetson-tk1/asus-xtion-pro-live-openni2-compilation-install-instructions/

http://blog.csdn.net/u013294888/article/details/51244736

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