Ogre中使用Opencv加载视频作为纹理贴图

增强现实中经常要用到真实的2D视频图片再配合虚拟对象（如三维模型）结合，以达到增强现实的效果。这里使用Ogre结合Opencv来实现

在开始前要先了解到纹理贴图的长宽必须是2的n次方，所以假如加载的视频没有达到这个值，必须做一下resize

1.创建动态纹理、背景框矩形，并添加到场景

在CreateScene中加入如下代码

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void CreateScene()

{

MaterialPtr material = MaterialManager::getSingleton().create(

"DynamicTextureMaterial", // name

ResourceGroupManager::DEFAULT_RESOURCE_GROUP_NAME);

material->getTechnique(0)->getPass(0)->createTextureUnitState("DynamicBg");

material->getTechnique(0)->getPass(0)->setDepthCheckEnabled(false);

material->getTechnique(0)->getPass(0)->setDepthWriteEnabled(false);

material->getTechnique(0)->getPass(0)->setLightingEnabled(false);

// Create background rectangle covering the whole screen

Rectangle2D* rect = new Rectangle2D(true);

rect->setCorners(-1.0, 1.0, 1.0, -1.0);

rect->setMaterial("DynamicTextureMaterial");

// Render the background before everything else

rect->setRenderQueueGroup(RENDER_QUEUE_BACKGROUND);

// Hacky, but we need to set the bounding box to something big

// NOTE: If you are using Eihort (v1.4), please see the note below on setting the bounding box

rect->setBoundingBox(AxisAlignedBox(-100000.0*Vector3::UNIT_SCALE, 100000.0*Vector3::UNIT_SCALE));

// Attach background to the scene

SceneNode* node = mSceneMgr->getRootSceneNode()->createChildSceneNode("Background");

node->attachObject(rect);

//add other scene node here

}

2.初始化视频图像获取相关数据

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<pre name="code" class="cpp">void InitVideoQuery(char *szVideoPath)

{

m_szVideoPath = szVideoPath;

m_pFileCamer=cvCreateFileCapture(szVideoPath );

m_pVideoImage=cvQueryFrame(m_pFileCamer);

m_pDrawImage=cvCreateImage(cvSize(1024,1024),8,3);

m_pTex=TextureManager::getSingleton().createManual("DynamicBg","General",

TEX_TYPE_2D,m_pDrawImage->width,m_pDrawImage->height,1,0,PF_A8B8G8R8,TU_WRITE_ONLY);</pre>}<br>

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<p> </p>

<p>3.更新顶点缓存</p>

<pre class="cpp" name="code">void UpdateTextureImage()

{

m_pVideoImage=cvQueryFrame(m_pFileCamer);

if(m_pDrawImage==0)

{

cvReleaseCapture(&m_pFileCamer);

m_pFileCamer=cvCreateFileCapture(m_szVideoPath);

m_pVideoImage=cvQueryFrame(m_pFileCamer);

}

cvShowImage("img",m_pVideoImage);

cvResize(m_pVideoImage,m_pDrawImage);

HardwarePixelBufferSharedPtr buffer=m_pTex->getBuffer(0,0);

buffer->lock(HardwareBuffer::HBL_DISCARD);

const PixelBox &pb = buffer->getCurrentLock();

uint32 *data = static_cast<uint32*>(pb.data);

size_t height = pb.getHeight();

size_t width = pb.getWidth();

size_t pitch = pb.rowPitch; // Skip between rows of image

for(size_t y=0; y<m_pDrawImage->height; ++y)

{

unsigned char *pImgLine=(unsigned char *)(m_pDrawImage->imageData+y*m_pDrawImage->widthStep);

for(size_t x=0; x<m_pDrawImage->width; ++x)

{

// 0xRRGGBB -> fill the buffer with yellow pixels

unsigned char B=pImgLine[3*x];

unsigned char G=pImgLine[3*x+1];

unsigned char R=pImgLine[3*x+2];

uint32 pixel=(R<<16)+(G<<8)+(B);

data[pitch*y + x] =pixel ;

}

}

buffer->unlock();

}</pre>

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<p>值得一提的是，在更新顶点缓存的过程中，即lock到unlock之间，由于操作硬件缓存效率低，为了提高效率，应该尽量减少代码的操作量，可选的做法是在外面将数据打包好，然后在更新的时候直接memcpy</p>

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