#include <stdio.h>
#include <iostream>
#include <cv.hpp>
#include <highgui\highgui.hpp>
#include <objdetect\objdetect.hpp>
#include <imgproc\imgproc.hpp>
#include <NuiApi.h>
#define RGB_WIDTH 640
#define RGB_HEIGHT 480
#define DEPTH_WIDTH 320
#define DEPTH_HEIGHT 240
#define RGB_CHANNELS 3
#define RGBA_CHANNELS 4
class CVKinect
{
public:
CVKinect( );
~CVKinect( );
int getColor( );
int getDepth( );
int getSkeleton( );
int getFace( );
RGBQUAD Nui_ShortToQuad_Depth( unsigned short s );
HRESULT init( CVKinect * );
void uninit( );
private:
cv::String face_cascade_name;// = "haarcascade_frontalface_alt.xml";
cv::String eyes_cascade_name;// = "haarcascade_eye_tree_eyeglasses.xml";
cv::CascadeClassifier face_cascade;
cv::CascadeClassifier eyes_cascade;
cv::RNG rng;
IplImage* rgb;
IplImage* depth;
IplImage* skeleton;
HANDLE rgbStream;
HANDLE rgbEvent;
HANDLE depthStream;
HANDLE depthEvent;
HANDLE skeletonStream;
HANDLE skeletonEvent;
};
using namespace std;
using namespace cv;
unsigned char imageBuffer[DEPTH_WIDTH*DEPTH_HEIGHT*RGB_CHANNELS];
CVKinect myCVKinect;
CVKinect::CVKinect( )
{
rgbEvent = CreateEvent( NULL, TRUE, FALSE, NULL );
rgbStream = 0;
depthEvent = CreateEvent( NULL, TRUE, FALSE, NULL );
depthStream = 0;
skeletonEvent = 0;//CreateEvent( NULL, TRUE, FALSE, NULL );
rng = RNG(12345);
face_cascade_name = "C:\\Program Files\\OpenCV2.3\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
eyes_cascade_name = "C:\\Program Files\\OpenCV2.3\\data\\haarcascades\\haarcascade_eye_tree_eyeglasses.xml";
}
CVKinect::~CVKinect( )
{
}
HRESULT CVKinect::init( CVKinect * myCVKinect )
{
rgb = cvCreateImageHeader(
cvSize( RGB_WIDTH, RGB_HEIGHT ),
IPL_DEPTH_8U,
RGBA_CHANNELS);
depth = cvCreateImageHeader(
cvSize( DEPTH_WIDTH, DEPTH_HEIGHT ),
IPL_DEPTH_8U,
RGB_CHANNELS);
HRESULT hr = NuiInitialize( NUI_INITIALIZE_FLAG_USES_COLOR | NUI_INITIALIZE_FLAG_USES_DEPTH );
if ( FAILED ( hr ) )
{
printf( "Error: The kinect sensor failed to initialize!\n" );
Sleep(1000);
return hr;
}
hr = NuiImageStreamOpen( NUI_IMAGE_TYPE_COLOR,
NUI_IMAGE_RESOLUTION_640x480,
0,
2,
myCVKinect->rgbEvent,
&myCVKinect->rgbStream);
if ( FAILED ( hr ) )
{
printf( "Error: The color stream failed to open!\n" );
return hr;
}
hr = NuiImageStreamOpen( NUI_IMAGE_TYPE_DEPTH,
NUI_IMAGE_RESOLUTION_320x240,
0,
2,
myCVKinect->depthEvent,
&myCVKinect->depthStream );
if ( FAILED ( hr ) )
{
printf( "Error: The depth stream failed to open!\n" );
return hr;
}
while (1)
{
WaitForSingleObject( rgbEvent, INFINITE );
myCVKinect->getFace( );
WaitForSingleObject( depthEvent, INFINITE );
myCVKinect->getDepth( );
int c = cvWaitKey(1);
if ( c == 'ESC' )
break;
}
return 1;
}
void CVKinect::uninit( )
{
cvReleaseImageHeader(&rgb);
cvReleaseImageHeader(&depth);
cvDestroyWindow("Video");
cvDestroyWindow("Depth");
NuiShutdown( );
}
int CVKinect::getColor( )
{
const NUI_IMAGE_FRAME * imageFrame = NULL;
HRESULT hr = NuiImageStreamGetNextFrame( rgbStream, 0, &imageFrame );
if ( FAILED ( hr ) )
{
return hr;
}
INuiFrameTexture * texture = imageFrame->pFrameTexture;
NUI_LOCKED_RECT lr;
texture->LockRect( 0, &lr, NULL, 0 );
if ( lr.Pitch != 0 )
{
BYTE * buffer = (BYTE *) lr.pBits;
cvSetData( rgb, buffer, lr.Pitch );
}
NuiImageStreamReleaseFrame( rgbStream, imageFrame );
cvShowImage("RGB Image", rgb);
return 1;
}
int CVKinect::getDepth( )
{
const NUI_IMAGE_FRAME * imageFrame = NULL;
HRESULT hr = NuiImageStreamGetNextFrame( depthStream, 0, &imageFrame );
if ( FAILED ( hr ) )
{
return hr;
}
INuiFrameTexture * texture = imageFrame->pFrameTexture;
NUI_LOCKED_RECT lr;
texture->LockRect( 0, &lr, NULL, 0 );
//13bits of depth data, 3 bits of player data
if ( lr.Pitch != 0 )
{
unsigned short * buffer = (unsigned short *) lr.pBits;
for ( unsigned int i = 0; i < DEPTH_WIDTH*DEPTH_HEIGHT; i ++ )
{
RGBQUAD color = Nui_ShortToQuad_Depth( buffer[i] );
imageBuffer[i*RGB_CHANNELS] = 255 - color.rgbRed;
imageBuffer[(i*RGB_CHANNELS)+1] = 255 - color.rgbGreen;
imageBuffer[(i*RGB_CHANNELS)+2] = 255 - color.rgbBlue;
}
cvSetData( depth, imageBuffer, DEPTH_WIDTH*RGB_CHANNELS );
}
NuiImageStreamReleaseFrame( depthStream, imageFrame );
cvShowImage( "Depth Image", depth );
return 1;
}
int CVKinect::getSkeleton( )
{
return 1;
}
int CVKinect::getFace( )
{
const NUI_IMAGE_FRAME * imageFrame = NULL;
HRESULT hr = NuiImageStreamGetNextFrame( rgbStream, 0, &imageFrame );
if ( FAILED ( hr ) )
{
return hr;
}
INuiFrameTexture * texture = imageFrame->pFrameTexture;
NUI_LOCKED_RECT lr;
texture->LockRect( 0, &lr, NULL, 0 );
if ( lr.Pitch != 0 )
{
BYTE * buffer = (BYTE *) lr.pBits;
cvSetData( rgb, buffer, lr.Pitch );
}
NuiImageStreamReleaseFrame( rgbStream, imageFrame );
//IplImage rgb
Mat frame = rgb;
std::vector<cv::Rect> faces;
Mat frame_gray;
cvtColor( frame, frame_gray, CV_RGB2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale(
frame_gray,
faces,
1.1,
2,
0|CV_HAAR_SCALE_IMAGE,
Size(20, 20)
);
for( int i = 0; i < faces.size(); i++ )
{
Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
ellipse( frame, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );
Mat faceROI = frame_gray( faces[i] );
std::vector<cv::Rect> eyes;
//-- In each face, detect eyes
eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
for( int j = 0; j < eyes.size(); j++ )
{
Point center( faces[i].x + eyes[j].x + eyes[j].width*0.5, faces[i].y + eyes[j].y + eyes[j].height*0.5 );
int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
circle( frame, center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
}
}
cvSetData(rgb, frame.data, frame.step);
cvShowImage("Face Image", rgb);
return 1;
}
RGBQUAD CVKinect::Nui_ShortToQuad_Depth( unsigned short s )
{
unsigned short RealDepth = NuiDepthPixelToDepth(s);
//USHORT Player = NuiDepthPixelToPlayerIndex(s);
// transform 13-bit depth information into an 8-bit intensity appropriate
// for display (we disregard information in most significant bit)
// BYTE intensity = (BYTE)~(s >> 4);
unsigned char intensity1;
unsigned char intensity2;
unsigned char intensity3;
intensity1 = (unsigned char)(s >> 8);
intensity2 = (unsigned char)(s >> 9);
intensity3 = (unsigned char)(s >> 10);
// tint the intensity by dividing by per-player values
RGBQUAD color;
color.rgbRed = intensity1 ;
color.rgbGreen = intensity2 ;
color.rgbBlue = intensity3 ;
return color;
}
int main(int argc, char* argv[])
{
myCVKinect.init( & myCVKinect );
myCVKinect.uninit( );
myCVKinect.~CVKinect( );
}
[2] Yun Tie, Ling Guan, Automatic face detection in video sequences using local normalization and optimal adaptive correlation techniques, Pattern Recognition, Volume 42, Issue 9, September 2009, Pages 1859-1868, ISSN 0031-3203, 10.1016/j.patcog.2008.11.026.
(http://www.sciencedirect.com/science/article/pii/S003132030800486X)
Keywords: Local normalization; Optimal adaptive correlation (OAC); Adaboost algorithm