487 lines
17 KiB
C++
487 lines
17 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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/* motion templates */
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CV_IMPL void
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cvUpdateMotionHistory( const void* silhouette, void* mhimg,
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double timestamp, double mhi_duration )
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{
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CvMat silhstub, *silh = cvGetMat(silhouette, &silhstub);
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CvMat mhistub, *mhi = cvGetMat(mhimg, &mhistub);
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if( !CV_IS_MASK_ARR( silh ))
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CV_Error( CV_StsBadMask, "" );
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if( CV_MAT_TYPE( mhi->type ) != CV_32FC1 )
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CV_Error( CV_StsUnsupportedFormat, "" );
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if( !CV_ARE_SIZES_EQ( mhi, silh ))
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CV_Error( CV_StsUnmatchedSizes, "" );
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CvSize size = cvGetMatSize( mhi );
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if( CV_IS_MAT_CONT( mhi->type & silh->type ))
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{
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size.width *= size.height;
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size.height = 1;
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}
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float ts = (float)timestamp;
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float delbound = (float)(timestamp - mhi_duration);
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int x, y;
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#if CV_SSE2
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volatile bool useSIMD = cv::checkHardwareSupport(CV_CPU_SSE2);
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#endif
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for( y = 0; y < size.height; y++ )
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{
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const uchar* silhData = silh->data.ptr + silh->step*y;
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float* mhiData = (float*)(mhi->data.ptr + mhi->step*y);
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x = 0;
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#if CV_SSE2
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if( useSIMD )
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{
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__m128 ts4 = _mm_set1_ps(ts), db4 = _mm_set1_ps(delbound);
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for( ; x <= size.width - 8; x += 8 )
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{
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__m128i z = _mm_setzero_si128();
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__m128i s = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(silhData + x)), z);
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__m128 s0 = _mm_cvtepi32_ps(_mm_unpacklo_epi16(s, z)), s1 = _mm_cvtepi32_ps(_mm_unpackhi_epi16(s, z));
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__m128 v0 = _mm_loadu_ps(mhiData + x), v1 = _mm_loadu_ps(mhiData + x + 4);
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__m128 fz = _mm_setzero_ps();
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v0 = _mm_and_ps(v0, _mm_cmpge_ps(v0, db4));
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v1 = _mm_and_ps(v1, _mm_cmpge_ps(v1, db4));
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__m128 m0 = _mm_and_ps(_mm_xor_ps(v0, ts4), _mm_cmpneq_ps(s0, fz));
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__m128 m1 = _mm_and_ps(_mm_xor_ps(v1, ts4), _mm_cmpneq_ps(s1, fz));
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v0 = _mm_xor_ps(v0, m0);
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v1 = _mm_xor_ps(v1, m1);
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_mm_storeu_ps(mhiData + x, v0);
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_mm_storeu_ps(mhiData + x + 4, v1);
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}
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}
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#endif
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for( ; x < size.width; x++ )
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{
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float val = mhiData[x];
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val = silhData[x] ? ts : val < delbound ? 0 : val;
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mhiData[x] = val;
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}
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}
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}
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CV_IMPL void
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cvCalcMotionGradient( const CvArr* mhiimg, CvArr* maskimg,
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CvArr* orientation,
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double delta1, double delta2,
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int aperture_size )
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{
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cv::Ptr<CvMat> dX_min, dY_max;
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CvMat mhistub, *mhi = cvGetMat(mhiimg, &mhistub);
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CvMat maskstub, *mask = cvGetMat(maskimg, &maskstub);
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CvMat orientstub, *orient = cvGetMat(orientation, &orientstub);
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CvMat dX_min_row, dY_max_row, orient_row, mask_row;
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CvSize size;
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int x, y;
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float gradient_epsilon = 1e-4f * aperture_size * aperture_size;
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float min_delta, max_delta;
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if( !CV_IS_MASK_ARR( mask ))
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CV_Error( CV_StsBadMask, "" );
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if( aperture_size < 3 || aperture_size > 7 || (aperture_size & 1) == 0 )
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CV_Error( CV_StsOutOfRange, "aperture_size must be 3, 5 or 7" );
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if( delta1 <= 0 || delta2 <= 0 )
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CV_Error( CV_StsOutOfRange, "both delta's must be positive" );
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if( CV_MAT_TYPE( mhi->type ) != CV_32FC1 || CV_MAT_TYPE( orient->type ) != CV_32FC1 )
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CV_Error( CV_StsUnsupportedFormat,
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"MHI and orientation must be single-channel floating-point images" );
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if( !CV_ARE_SIZES_EQ( mhi, mask ) || !CV_ARE_SIZES_EQ( orient, mhi ))
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CV_Error( CV_StsUnmatchedSizes, "" );
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if( orient->data.ptr == mhi->data.ptr )
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CV_Error( CV_StsInplaceNotSupported, "orientation image must be different from MHI" );
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if( delta1 > delta2 )
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{
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double t;
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CV_SWAP( delta1, delta2, t );
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}
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size = cvGetMatSize( mhi );
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min_delta = (float)delta1;
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max_delta = (float)delta2;
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dX_min = cvCreateMat( mhi->rows, mhi->cols, CV_32F );
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dY_max = cvCreateMat( mhi->rows, mhi->cols, CV_32F );
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// calc Dx and Dy
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cvSobel( mhi, dX_min, 1, 0, aperture_size );
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cvSobel( mhi, dY_max, 0, 1, aperture_size );
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cvGetRow( dX_min, &dX_min_row, 0 );
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cvGetRow( dY_max, &dY_max_row, 0 );
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cvGetRow( orient, &orient_row, 0 );
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cvGetRow( mask, &mask_row, 0 );
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// calc gradient
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for( y = 0; y < size.height; y++ )
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{
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dX_min_row.data.ptr = dX_min->data.ptr + y*dX_min->step;
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dY_max_row.data.ptr = dY_max->data.ptr + y*dY_max->step;
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orient_row.data.ptr = orient->data.ptr + y*orient->step;
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mask_row.data.ptr = mask->data.ptr + y*mask->step;
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cvCartToPolar( &dX_min_row, &dY_max_row, 0, &orient_row, 1 );
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// make orientation zero where the gradient is very small
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for( x = 0; x < size.width; x++ )
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{
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float dY = dY_max_row.data.fl[x];
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float dX = dX_min_row.data.fl[x];
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if( fabs(dX) < gradient_epsilon && fabs(dY) < gradient_epsilon )
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{
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mask_row.data.ptr[x] = 0;
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orient_row.data.i[x] = 0;
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}
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else
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mask_row.data.ptr[x] = 1;
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}
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}
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cvErode( mhi, dX_min, 0, (aperture_size-1)/2);
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cvDilate( mhi, dY_max, 0, (aperture_size-1)/2);
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// mask off pixels which have little motion difference in their neighborhood
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for( y = 0; y < size.height; y++ )
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{
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dX_min_row.data.ptr = dX_min->data.ptr + y*dX_min->step;
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dY_max_row.data.ptr = dY_max->data.ptr + y*dY_max->step;
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mask_row.data.ptr = mask->data.ptr + y*mask->step;
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orient_row.data.ptr = orient->data.ptr + y*orient->step;
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for( x = 0; x < size.width; x++ )
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{
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float d0 = dY_max_row.data.fl[x] - dX_min_row.data.fl[x];
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if( mask_row.data.ptr[x] == 0 || d0 < min_delta || max_delta < d0 )
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{
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mask_row.data.ptr[x] = 0;
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orient_row.data.i[x] = 0;
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}
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}
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}
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}
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CV_IMPL double
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cvCalcGlobalOrientation( const void* orientation, const void* maskimg, const void* mhiimg,
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double curr_mhi_timestamp, double mhi_duration )
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{
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int hist_size = 12;
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cv::Ptr<CvHistogram> hist;
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CvMat mhistub, *mhi = cvGetMat(mhiimg, &mhistub);
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CvMat maskstub, *mask = cvGetMat(maskimg, &maskstub);
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CvMat orientstub, *orient = cvGetMat(orientation, &orientstub);
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void* _orient;
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float _ranges[] = { 0, 360 };
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float* ranges = _ranges;
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int base_orient;
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float shift_orient = 0, shift_weight = 0;
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float a, b, fbase_orient;
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float delbound;
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CvMat mhi_row, mask_row, orient_row;
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int x, y, mhi_rows, mhi_cols;
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if( !CV_IS_MASK_ARR( mask ))
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CV_Error( CV_StsBadMask, "" );
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if( CV_MAT_TYPE( mhi->type ) != CV_32FC1 || CV_MAT_TYPE( orient->type ) != CV_32FC1 )
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CV_Error( CV_StsUnsupportedFormat,
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"MHI and orientation must be single-channel floating-point images" );
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if( !CV_ARE_SIZES_EQ( mhi, mask ) || !CV_ARE_SIZES_EQ( orient, mhi ))
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CV_Error( CV_StsUnmatchedSizes, "" );
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if( mhi_duration <= 0 )
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CV_Error( CV_StsOutOfRange, "MHI duration must be positive" );
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if( orient->data.ptr == mhi->data.ptr )
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CV_Error( CV_StsInplaceNotSupported, "orientation image must be different from MHI" );
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// calculate histogram of different orientation values
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hist = cvCreateHist( 1, &hist_size, CV_HIST_ARRAY, &ranges );
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_orient = orient;
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cvCalcArrHist( &_orient, hist, 0, mask );
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// find the maximum index (the dominant orientation)
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cvGetMinMaxHistValue( hist, 0, 0, 0, &base_orient );
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fbase_orient = base_orient*360.f/hist_size;
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// override timestamp with the maximum value in MHI
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cvMinMaxLoc( mhi, 0, &curr_mhi_timestamp, 0, 0, mask );
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// find the shift relative to the dominant orientation as weighted sum of relative angles
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a = (float)(254. / 255. / mhi_duration);
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b = (float)(1. - curr_mhi_timestamp * a);
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delbound = (float)(curr_mhi_timestamp - mhi_duration);
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mhi_rows = mhi->rows;
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mhi_cols = mhi->cols;
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if( CV_IS_MAT_CONT( mhi->type & mask->type & orient->type ))
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{
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mhi_cols *= mhi_rows;
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mhi_rows = 1;
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}
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cvGetRow( mhi, &mhi_row, 0 );
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cvGetRow( mask, &mask_row, 0 );
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cvGetRow( orient, &orient_row, 0 );
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/*
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a = 254/(255*dt)
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b = 1 - t*a = 1 - 254*t/(255*dur) =
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(255*dt - 254*t)/(255*dt) =
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(dt - (t - dt)*254)/(255*dt);
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--------------------------------------------------------
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ax + b = 254*x/(255*dt) + (dt - (t - dt)*254)/(255*dt) =
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(254*x + dt - (t - dt)*254)/(255*dt) =
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((x - (t - dt))*254 + dt)/(255*dt) =
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(((x - (t - dt))/dt)*254 + 1)/255 = (((x - low_time)/dt)*254 + 1)/255
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*/
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for( y = 0; y < mhi_rows; y++ )
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{
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mhi_row.data.ptr = mhi->data.ptr + mhi->step*y;
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mask_row.data.ptr = mask->data.ptr + mask->step*y;
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orient_row.data.ptr = orient->data.ptr + orient->step*y;
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for( x = 0; x < mhi_cols; x++ )
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if( mask_row.data.ptr[x] != 0 && mhi_row.data.fl[x] > delbound )
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{
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/*
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orient in 0..360, base_orient in 0..360
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-> (rel_angle = orient - base_orient) in -360..360.
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rel_angle is translated to -180..180
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*/
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float weight = mhi_row.data.fl[x] * a + b;
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float rel_angle = orient_row.data.fl[x] - fbase_orient;
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rel_angle += (rel_angle < -180 ? 360 : 0);
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rel_angle += (rel_angle > 180 ? -360 : 0);
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if( fabs(rel_angle) < 45 )
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{
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shift_orient += weight * rel_angle;
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shift_weight += weight;
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}
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}
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}
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// add the dominant orientation and the relative shift
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if( shift_weight == 0 )
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shift_weight = 0.01f;
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fbase_orient += shift_orient / shift_weight;
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fbase_orient -= (fbase_orient < 360 ? 0 : 360);
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fbase_orient += (fbase_orient >= 0 ? 0 : 360);
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return fbase_orient;
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}
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CV_IMPL CvSeq*
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cvSegmentMotion( const CvArr* mhiimg, CvArr* segmask, CvMemStorage* storage,
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double timestamp, double seg_thresh )
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{
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CvSeq* components = 0;
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cv::Ptr<CvMat> mask8u;
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CvMat mhistub, *mhi = cvGetMat(mhiimg, &mhistub);
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CvMat maskstub, *mask = cvGetMat(segmask, &maskstub);
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Cv32suf v, comp_idx;
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int stub_val, ts;
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int x, y;
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if( !storage )
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CV_Error( CV_StsNullPtr, "NULL memory storage" );
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mhi = cvGetMat( mhi, &mhistub );
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mask = cvGetMat( mask, &maskstub );
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if( CV_MAT_TYPE( mhi->type ) != CV_32FC1 || CV_MAT_TYPE( mask->type ) != CV_32FC1 )
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CV_Error( CV_BadDepth, "Both MHI and the destination mask" );
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if( !CV_ARE_SIZES_EQ( mhi, mask ))
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CV_Error( CV_StsUnmatchedSizes, "" );
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mask8u = cvCreateMat( mhi->rows + 2, mhi->cols + 2, CV_8UC1 );
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cvZero( mask8u );
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cvZero( mask );
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components = cvCreateSeq( CV_SEQ_KIND_GENERIC, sizeof(CvSeq),
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sizeof(CvConnectedComp), storage );
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v.f = (float)timestamp; ts = v.i;
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v.f = FLT_MAX*0.1f; stub_val = v.i;
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comp_idx.f = 1;
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for( y = 0; y < mhi->rows; y++ )
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{
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int* mhi_row = (int*)(mhi->data.ptr + y*mhi->step);
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for( x = 0; x < mhi->cols; x++ )
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{
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if( mhi_row[x] == 0 )
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mhi_row[x] = stub_val;
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}
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}
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for( y = 0; y < mhi->rows; y++ )
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{
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int* mhi_row = (int*)(mhi->data.ptr + y*mhi->step);
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uchar* mask8u_row = mask8u->data.ptr + (y+1)*mask8u->step + 1;
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for( x = 0; x < mhi->cols; x++ )
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{
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if( mhi_row[x] == ts && mask8u_row[x] == 0 )
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{
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CvConnectedComp comp;
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int x1, y1;
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CvScalar _seg_thresh = cvRealScalar(seg_thresh);
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CvPoint seed = cvPoint(x,y);
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cvFloodFill( mhi, seed, cvRealScalar(0), _seg_thresh, _seg_thresh,
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&comp, CV_FLOODFILL_MASK_ONLY + 2*256 + 4, mask8u );
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for( y1 = 0; y1 < comp.rect.height; y1++ )
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{
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int* mask_row1 = (int*)(mask->data.ptr +
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(comp.rect.y + y1)*mask->step) + comp.rect.x;
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uchar* mask8u_row1 = mask8u->data.ptr +
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(comp.rect.y + y1+1)*mask8u->step + comp.rect.x+1;
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for( x1 = 0; x1 < comp.rect.width; x1++ )
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{
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if( mask8u_row1[x1] > 1 )
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{
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mask8u_row1[x1] = 1;
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mask_row1[x1] = comp_idx.i;
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}
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}
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}
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comp_idx.f++;
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cvSeqPush( components, &comp );
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}
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}
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}
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for( y = 0; y < mhi->rows; y++ )
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{
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int* mhi_row = (int*)(mhi->data.ptr + y*mhi->step);
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for( x = 0; x < mhi->cols; x++ )
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{
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if( mhi_row[x] == stub_val )
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mhi_row[x] = 0;
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}
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}
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return components;
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}
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void cv::updateMotionHistory( InputArray _silhouette, InputOutputArray _mhi,
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double timestamp, double duration )
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{
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Mat silhouette = _silhouette.getMat();
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CvMat c_silhouette = silhouette, c_mhi = _mhi.getMat();
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cvUpdateMotionHistory( &c_silhouette, &c_mhi, timestamp, duration );
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}
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void cv::calcMotionGradient( InputArray _mhi, OutputArray _mask,
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OutputArray _orientation,
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double delta1, double delta2,
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int aperture_size )
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{
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Mat mhi = _mhi.getMat();
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_mask.create(mhi.size(), CV_8U);
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_orientation.create(mhi.size(), CV_32F);
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CvMat c_mhi = mhi, c_mask = _mask.getMat(), c_orientation = _orientation.getMat();
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cvCalcMotionGradient(&c_mhi, &c_mask, &c_orientation, delta1, delta2, aperture_size);
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}
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double cv::calcGlobalOrientation( InputArray _orientation, InputArray _mask,
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InputArray _mhi, double timestamp,
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double duration )
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{
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Mat orientation = _orientation.getMat(), mask = _mask.getMat(), mhi = _mhi.getMat();
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CvMat c_orientation = orientation, c_mask = mask, c_mhi = mhi;
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return cvCalcGlobalOrientation(&c_orientation, &c_mask, &c_mhi, timestamp, duration);
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}
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void cv::segmentMotion(InputArray _mhi, OutputArray _segmask,
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vector<Rect>& boundingRects,
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double timestamp, double segThresh)
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{
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Mat mhi = _mhi.getMat();
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_segmask.create(mhi.size(), CV_32F);
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CvMat c_mhi = mhi, c_segmask = _segmask.getMat();
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Ptr<CvMemStorage> storage = cvCreateMemStorage();
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Seq<CvConnectedComp> comps = cvSegmentMotion(&c_mhi, &c_segmask, storage, timestamp, segThresh);
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Seq<CvConnectedComp>::const_iterator it(comps);
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size_t i, ncomps = comps.size();
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boundingRects.resize(ncomps);
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for( i = 0; i < ncomps; i++, ++it)
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boundingRects[i] = (*it).rect;
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}
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/* End of file. */
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