最近入手NvidiaTegra 1 开发板，ARM架构的，做室内三维重建用。今天就讲讲的PCL 1.8+ OPENCV3.1 + OPENNI2.0在ubuntu14.04 上的安装与编译。

   更新ubuntu的armhf源，修改source.list，中科大的快！

deb http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty main restricted universe multiverse
deb http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-security main restricted universe multiverse
deb http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-updates main restricted universe multiverse
deb http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-proposed main restricted universe multiverse
deb http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-backports main restricted universe multiverse
deb-src http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty main restricted universe multiverse
deb-src http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-security main restricted universe multiverse
deb-src http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-updates main restricted universe multiverse
deb-src http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-proposed main restricted universe multiverse
deb-src http://mirrors.ustc.edu.cn/ubuntu-ports/ trusty-backports main restricted universe multiverse

一、  Opencv

这个网上有很多教程，

1. 安装依赖包和预备环境

$sudo apt-get install build-essential
$sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
$sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev

2.从官网下载opencv3.1源码，并解压

3.创建编译目录，编译

$cd ~/opencv-3.1.0
$mkdir release
$cd release
$cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
$make
$sudo make install

4.测试opencv

$mkdir ~/opencv-lena
$cd ~/opencv-lena
$gedit DisplayImage.cpp

#include <stdio.h>
#include <opencv2/opencv.hpp>
using namespace cv;
int main(int argc, char** argv )
{
  if ( argc != 2 )
  {
    printf("usage: DisplayImage.out <Image_Path>\n");
    return -1;
  }
  Mat image;
  image = imread( argv[1], 1 );
  if ( !image.data )
  {
    printf("No image data \n");
    return -1;
  }
  namedWindow("Display Image", WINDOW_AUTOSIZE );
  imshow("Display Image", image);
  waitKey(0);
  return 0;
}

创建cmakelist编译文件

cmake_minimum_required(VERSION 2.8)
project( DisplayImage )
find_package( OpenCV REQUIRED )
add_executable( DisplayImage DisplayImage.cpp )
target_link_libraries( DisplayImage ${OpenCV_LIBS} )

执行：

$cd ~/opencv-lena
$cmake .
$make

$./DisplayImage lena.jpg

至此opencv配置完毕

 

二、openni2.0

以下内容是我在youtube上看到的视频：

https://www.youtube.com/watch?v=Bn9WqbYtNBw

 

1.安装 OpenNI2依赖项

$sudo apt-get install -y g++ python libusb-1.0-0-dev freeglut3-dev doxygen graphviz
$sudo apt-get install libudev-dev

2.从github将openni2源码clone下来

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

3.修改两处配置Platform.Arm和CommonCppMakefile，适用于arm设备

$gedit ThirdParty/PSCommon/BuildSystem/Platform.Arm

Change:

CFLAGS+= -march=armv7-a -mtune=cortex-a9 -mfpu=neon -mfloat-abi=softfp#-mcpu=cortex-a8

to:

CFLAGS+= -march=armv7-a -mtune=cortex-a15 -mfpu=neon-vfpv4 -mfloat-abi=hard

$gedit ThirdParty/PSCommon/BuildSystem/CommonCppMakefile

---OpenNI2-2.2.0.30/ThirdParty/PSCommon/BuildSystem/CommonCppMakefile.old2014-03-28 19:09:11.572263107 -0700

+++OpenNI2-2.2.0.30/ThirdParty/PSCommon/BuildSystem/CommonCppMakefile 2014-03-2819:09:55.600261937 -0700

@@-95,6 +95,9 @@

OUTPUT_NAME= $(EXE_NAME)

# Wewant the executables to look for the .so's locally first:

LDFLAGS+= -Wl,-rpath ./

+ifneq ("$(OSTYPE)","Darwin")

+LDFLAGS += -lpthread

+endif

OUTPUT_COMMAND= $(CXX) -o $(OUTPUT_FILE) $(OBJ_FILES) $(LDFLAGS)

endif

ifneq "$(SLIB_NAME)" ""

4.修改makefile，增加sample，即在makefile文件末尾添加：

core_samples: $(CORE_SAMPLES)
tools: $(ALL_TOOLS)

5.编译

$make
$make core_samples # this probably isn't necessary, they should already be built
$GLUT_SUPPORTED=1 make tools#GLUT_SUPPORTED tells the make to compile NiViewer for OpenGL

6.安装libfreenect，否则无法驱动primesensor

安装依赖项

$sudo apt-get install cmake freeglut3-dev pkg-config build-essential libxmu-dev libxi-dev libusb-1.0-0-dev –y

下载源码并编译

$ git clone git://github.com/OpenKinect/libfreenect.git
$ cd libfreenect
$ mkdir build
$ cd build
$ cmake ..
$ make
$ sudo make install
# Build the OpenNI2 driver
$ cmake .. -DBUILD_OPENNI2_DRIVER=ON
$ make

将libfreenect的so拷贝到OpenNI的驱动文件夹下

$ Repository=../../Bin/Arm-Release/OpenNI2/Drivers
$ cp -L lib/OpenNI2-FreenectDriver/libFreenectDriver* ${Repository}

设置使用传感器的权限

$ sudo usermod -a -G video Ubuntu

7.回到openni2目录，将头文件和so文件拷贝到/usr目录下

$ sudo cp -r Include /usr/include/openni2
$ sudo cp -r Bin/Arm-Release/OpenNI2 /usr/lib/
$ sudo cp Bin/Arm-Release/libOpenNI2.* /usr/lib/

8.创建packageconfig文件

# this will enable ubuntu to find the location of the drivers, libraries and include files.
$ sudo gedit /usr/lib/pkgconfig/libopenni2.pc

and fill it with this:

prefix=/usr
exec_prefix=${prefix}
libdir=${exec_prefix}/lib
includedir=${prefix}/include/openni2

Name: OpenNI2
Description: A general purpose driver for all OpenNI cameras.
Version: 2.2.0.0
Cflags: -I${includedir}
Libs: -L${libdir} -lOpenNI2 -L${libdir}/OpenNI2/Drivers -lDummyDevice -lOniFile -lPS1080.so

检验：

# To make sure it is correctly found, run
$ pkg-config --modversion libopenni2

# which should give the same version as defined in the file above (2.2.0.0)

最后一步：

# Linux has used the udev system to handle devices such as USB connected peripherals.

$ cd Packaging/Linux
$ sudo cp primesense-usb.rules /etc/udev/rules.d/557-primesense-usb.rules

翻译的如果卡不懂和其他注意事项，

请直接看：http://jetsonhacks.com/2014/08/28/building-openni2-structure-sensor/

运行结果：

三、PCL安装

参考：

http://larrylisky.com/2014/03/03/installing-pcl-on-ubuntu/

安装依赖环境

sudo apt-get install g++
sudo apt-get install cmake cmake-gui
sudo apt-get install doxygen  
sudo apt-get install mpi-default-dev openmpi-bin openmpi-common  
sudo apt-get install libflann1 libflann-dev
sudo apt-get install libeigen3-dev
sudo apt-get install libboost-all-dev
sudo apt-get install libvtk5.8-qt4 libvtk5.8 libvtk5-dev
sudo apt-get install libqhull*
sudo apt-get install libusb-dev
sudo apt-get install libgtest-dev
sudo apt-get install git-core freeglut3-dev pkg-config
sudo apt-get install build-essential libxmu-dev libxi-dev 
sudo apt-get install libusb-1.0-0-dev graphviz mono-complete
sudo apt-get install qt-sdk openjdk-7-jdk openjdk-7-jre
sudo apt-get install phonon-backend-gstreamer
sudo apt-get install phonon-backend-vlc

从github上下载pcl最新版本并编译

$git clone https://github.com/PointCloudLibrary/pcl.git pcl-trunk ln -s pcl-trunk pcl(我是直接下载了压缩包，解压的，不然太慢了)
$mkdir release
$cd release
$cmake -DCMAKE_BUILD_TYPE=None -DBUILD_GPU=ON -DBUILD_apps=ON -DBUILD_examples=ON ..
$make
$sudo make install

至此完成安装，但是是VTK有问题的，留着下次解决---->这么解决：

大家如何cmake时，发现有类似The imported target "vtk***" reference the file "/usr/bin/vtk**"的错误，需要安装如下两个东西：

sudo apt-get install libvtk-java
sudo apt-get install python-vtk

然后再重新编译，时间非常久

cmake -DCMAKE_BUILD_TYPE=None -DBUILD_GPU=ON -DBUILD_apps=ON -DBUILD_examples=ON ..
make
make install

编译完成后，执行他的pcd_viewer，结果如下：

#include <pcl/visualization/cloud_viewer.h>
#include <iostream>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
using namespace std;
using namespace pcl;
    
int main ()
{
	pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGB>);

	if(pcl::io::loadPCDFile<pcl::PointXYZRGB>("color_5.pcd",*cloud)==-1)//*打开点云文件
	{
		PCL_ERROR("Couldn't read file test_pcd.pcd\n");
		return(-1);
	}
	std::cout<<"Loaded "<<cloud->width*cloud->height<<" data points from test_pcd.pcd with the following fields: "<<std::endl;

	pcl::visualization::CloudViewer viewer("My First Cloud Viewer");
	viewer.showCloud(cloud);
	while(!viewer.wasStopped())
	{

	}
}

CMakeLists.txt

cmake_minimum_required(VERSION 2.8 FATAL_ERROR)

project(cloud_viewer)

find_package(PCL 1.8 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (cloud_viewer test.cpp)
target_link_libraries (cloud_viewer ${PCL_LIBRARIES})

四、最后再给出三个库同时使用的情形：

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})

c++文件：

#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;*/
		}
	}
}

运行结果：

键盘输入c抓取数据，按q退出