cvoptflowlk.cpp

opencv库在TI DM6437上的移植,目前包括两个库cv.lib和cxcore.lib的工程

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#include "_cv.h"

typedef struct
{
    float xx;
    float xy;
    float yy;
    float xt;
    float yt;
}
icvDerProduct;


#define CONV( A, B, C)  ((float)( A +  (B<<1)  + C ))
/*F///////////////////////////////////////////////////////////////////////////////////////
//    Name: icvCalcOpticalFlowLK_8u32fR ( Lucas & Kanade method )
//    Purpose: calculate Optical flow for 2 images using Lucas & Kanade algorithm
//    Context:
//    Parameters:
//            imgA,         // pointer to first frame ROI
//            imgB,         // pointer to second frame ROI
//            imgStep,      // width of single row of source images in bytes
//            imgSize,      // size of the source image ROI
//            winSize,      // size of the averaging window used for grouping
//            velocityX,    // pointer to horizontal and
//            velocityY,    // vertical components of optical flow ROI
//            velStep       // width of single row of velocity frames in bytes
//
//    Returns: CV_OK         - all ok
//             CV_OUTOFMEM_ERR  - insufficient memory for function work
//             CV_NULLPTR_ERR - if one of input pointers is NULL
//             CV_BADSIZE_ERR   - wrong input sizes interrelation
//
//    Notes:  1.Optical flow to be computed for every pixel in ROI
//            2.For calculating spatial derivatives we use 3x3 Sobel operator.
//            3.We use the following border mode.
//              The last row or column is replicated for the border
//              ( IPL_BORDER_REPLICATE in IPL ).
//
//
//F*/
static CvStatus CV_STDCALL
icvCalcOpticalFlowLK_8u32fR( uchar * imgA,
                             uchar * imgB,
                             int imgStep,
                             CvSize imgSize,
                             CvSize winSize,
                             float *velocityX,
                             float *velocityY, int velStep )
{
    /* Loops indexes */
    int i, j, k;

    /* Gaussian separable kernels */
    float GaussX[16];
    float GaussY[16];
    float *KerX;
    float *KerY;

    /* Buffers for Sobel calculations */
    float *MemX[2];
    float *MemY[2];

    float ConvX, ConvY;
    float GradX, GradY, GradT;

    int winWidth = winSize.width;
    int winHeight = winSize.height;

    int imageWidth = imgSize.width;
    int imageHeight = imgSize.height;

    int HorRadius = (winWidth - 1) >> 1;
    int VerRadius = (winHeight - 1) >> 1;

    int PixelLine;
    int ConvLine;

    int BufferAddress;

    int BufferHeight = 0;
    int BufferWidth;
    int BufferSize;

    /* buffers derivatives product */
    icvDerProduct *II;

    /* buffers for gaussian horisontal convolution */
    icvDerProduct *WII;

    /* variables for storing number of first pixel of image line */
    int Line1;
    int Line2;
    int Line3;

    /* we must have 2*2 linear system coeffs
       | A1B2  B1 |  {u}   {C1}   {0}
       |          |  { } + {  } = { }
       | A2  A1B2 |  {v}   {C2}   {0}
     */
    float A1B2, A2, B1, C1, C2;

    int pixNumber;

    /* auxiliary */
    int NoMem = 0;

    velStep /= sizeof(velocityX[0]);

    /* Checking bad arguments */
    if( imgA == NULL )
        return CV_NULLPTR_ERR;
    if( imgB == NULL )
        return CV_NULLPTR_ERR;

    if( imageHeight < winHeight )
        return CV_BADSIZE_ERR;
    if( imageWidth < winWidth )
        return CV_BADSIZE_ERR;

    if( winHeight >= 16 )
        return CV_BADSIZE_ERR;
    if( winWidth >= 16 )
        return CV_BADSIZE_ERR;

    if( !(winHeight & 1) )
        return CV_BADSIZE_ERR;
    if( !(winWidth & 1) )
        return CV_BADSIZE_ERR;

    BufferHeight = winHeight;
    BufferWidth = imageWidth;

    /****************************************************************************************/
    /* Computing Gaussian coeffs                                                            */
    /****************************************************************************************/
    GaussX[0] = 1;
    GaussY[0] = 1;
    for( i = 1; i < winWidth; i++ )
    {
        GaussX[i] = 1;
        for( j = i - 1; j > 0; j-- )
        {
            GaussX[j] += GaussX[j - 1];
        }
    }
    for( i = 1; i < winHeight; i++ )
    {
        GaussY[i] = 1;
        for( j = i - 1; j > 0; j-- )
        {
            GaussY[j] += GaussY[j - 1];
        }
    }
    KerX = &GaussX[HorRadius];
    KerY = &GaussY[VerRadius];

    /****************************************************************************************/
    /* Allocating memory for all buffers                                                    */
    /****************************************************************************************/
    for( k = 0; k < 2; k++ )
    {
        MemX[k] = (float *) cvAlloc( (imgSize.height) * sizeof( float ));

        if( MemX[k] == NULL )
            NoMem = 1;
        MemY[k] = (float *) cvAlloc( (imgSize.width) * sizeof( float ));

        if( MemY[k] == NULL )
            NoMem = 1;
    }

    BufferSize = BufferHeight * BufferWidth;

    II = (icvDerProduct *) cvAlloc( BufferSize * sizeof( icvDerProduct ));
    WII = (icvDerProduct *) cvAlloc( BufferSize * sizeof( icvDerProduct ));


    if( (II == NULL) || (WII == NULL) )
        NoMem = 1;

    if( NoMem )
    {
        for( k = 0; k < 2; k++ )
        {
            if( MemX[k] )
                cvFree( &MemX[k] );

            if( MemY[k] )
                cvFree( &MemY[k] );
        }
        if( II )
            cvFree( &II );
        if( WII )
            cvFree( &WII );

        return CV_OUTOFMEM_ERR;
    }

    /****************************************************************************************/
    /*        Calculate first line of memX and memY                                         */
    /****************************************************************************************/
    MemY[0][0] = MemY[1][0] = CONV( imgA[0], imgA[0], imgA[1] );
    MemX[0][0] = MemX[1][0] = CONV( imgA[0], imgA[0], imgA[imgStep] );

    for( j = 1; j < imageWidth - 1; j++ )
    {
        MemY[0][j] = MemY[1][j] = CONV( imgA[j - 1], imgA[j], imgA[j + 1] );
    }

    pixNumber = imgStep;
    for( i = 1; i < imageHeight - 1; i++ )
    {
        MemX[0][i] = MemX[1][i] = CONV( imgA[pixNumber - imgStep],
                                        imgA[pixNumber], imgA[pixNumber + imgStep] );
        pixNumber += imgStep;
    }

    MemY[0][imageWidth - 1] =
        MemY[1][imageWidth - 1] = CONV( imgA[imageWidth - 2],
                                        imgA[imageWidth - 1], imgA[imageWidth - 1] );

    MemX[0][imageHeight - 1] =
        MemX[1][imageHeight - 1] = CONV( imgA[pixNumber - imgStep],
                                         imgA[pixNumber], imgA[pixNumber] );


    /****************************************************************************************/
    /*    begin scan image, calc derivatives and solve system                               */
    /****************************************************************************************/

    PixelLine = -VerRadius;
    ConvLine = 0;
    BufferAddress = -BufferWidth;

    while( PixelLine < imageHeight )
    {
        if( ConvLine < imageHeight )
        {
            /*Here we calculate derivatives for line of image */
            int address;

            i = ConvLine;
            int L1 = i - 1;
            int L2 = i;
            int L3 = i + 1;

            int memYline = L3 & 1;

            if( L1 < 0 )
                L1 = 0;
            if( L3 >= imageHeight )
                L3 = imageHeight - 1;

            BufferAddress += BufferWidth;
            BufferAddress -= ((BufferAddress >= BufferSize) ? 0xffffffff : 0) & BufferSize;

            address = BufferAddress;

            Line1 = L1 * imgStep;
            Line2 = L2 * imgStep;
            Line3 = L3 * imgStep;

            /* Process first pixel */
            ConvX = CONV( imgA[Line1 + 1], imgA[Line2 + 1], imgA[Line3 + 1] );
            ConvY = CONV( imgA[Line3], imgA[Line3], imgA[Line3 + 1] );