X-Git-Url: https://vcs.maemo.org/git/?a=blobdiff_plain;f=cvaux%2Fsrc%2Fvs%2Fblobtrackpostprockalman.cpp;fp=cvaux%2Fsrc%2Fvs%2Fblobtrackpostprockalman.cpp;h=0000000000000000000000000000000000000000;hb=e4c14cdbdf2fe805e79cd96ded236f57e7b89060;hp=05e22ff2d2d0782046ccb45ff0f23ef1ace1b341;hpb=454138ff8a20f6edb9b65a910101403d8b520643;p=opencv diff --git a/cvaux/src/vs/blobtrackpostprockalman.cpp b/cvaux/src/vs/blobtrackpostprockalman.cpp deleted file mode 100644 index 05e22ff..0000000 --- a/cvaux/src/vs/blobtrackpostprockalman.cpp +++ /dev/null @@ -1,323 +0,0 @@ -/*M/////////////////////////////////////////////////////////////////////////////////////// -// -// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. -// -// By downloading, copying, installing or using the software you agree to this license. -// If you do not agree to this license, do not download, install, -// copy or use the software. -// -// -// Intel License Agreement -// -// Copyright (C) 2000, Intel Corporation, all rights reserved. -// Third party copyrights are property of their respective owners. -// -// Redistribution and use in source and binary forms, with or without modification, -// are permitted provided that the following conditions are met: -// -// * Redistribution's of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// -// * Redistribution's in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// -// * The name of Intel Corporation may not be used to endorse or promote products -// derived from this software without specific prior written permission. -// -// This software is provided by the copyright holders and contributors "as is" and -// any express or implied warranties, including, but not limited to, the implied -// warranties of merchantability and fitness for a particular purpose are disclaimed. -// In no event shall the Intel Corporation or contributors be liable for any direct, -// indirect, incidental, special, exemplary, or consequential damages -// (including, but not limited to, procurement of substitute goods or services; -// loss of use, data, or profits; or business interruption) however caused -// and on any theory of liability, whether in contract, strict liability, -// or tort (including negligence or otherwise) arising in any way out of -// the use of this software, even if advised of the possibility of such damage. -// -//M*/ - -#include "_cvaux.h" - -/*======================= KALMAN FILTER =========================*/ -/* State vector is (x,y,w,h,dx,dy,dw,dh). */ -/* Measurement is (x,y,w,h). */ - -/* Dynamic matrix A: */ -const float A8[] = { 1, 0, 0, 0, 1, 0, 0, 0, - 0, 1, 0, 0, 0, 1, 0, 0, - 0, 0, 1, 0, 0, 0, 1, 0, - 0, 0, 0, 1, 0, 0, 0, 1, - 0, 0, 0, 0, 1, 0, 0, 0, - 0, 0, 0, 0, 0, 1, 0, 0, - 0, 0, 0, 0, 0, 0, 1, 0, - 0, 0, 0, 0, 0, 0, 0, 1}; - -/* Measurement matrix H: */ -const float H8[] = { 1, 0, 0, 0, 0, 0, 0, 0, - 0, 1, 0, 0, 0, 0, 0, 0, - 0, 0, 1, 0, 0, 0, 0, 0, - 0, 0, 0, 1, 0, 0, 0, 0}; - -/* Matrices for zero size velocity: */ -/* Dinamic matrix A: */ -const float A6[] = { 1, 0, 0, 0, 1, 0, - 0, 1, 0, 0, 0, 1, - 0, 0, 1, 0, 0, 0, - 0, 0, 0, 1, 0, 0, - 0, 0, 0, 0, 1, 0, - 0, 0, 0, 0, 0, 1}; - -/* Measurement matrix H: */ -const float H6[] = { 1, 0, 0, 0, 0, 0, - 0, 1, 0, 0, 0, 0, - 0, 0, 1, 0, 0, 0, - 0, 0, 0, 1, 0, 0}; - -#define STATE_NUM 6 -#define A A6 -#define H H6 - -class CvBlobTrackPostProcKalman:public CvBlobTrackPostProcOne -{ - -private: - CvBlob m_Blob; - CvKalman* m_pKalman; - int m_Frame; - float m_ModelNoise; - float m_DataNoisePos; - float m_DataNoiseSize; - -public: - CvBlobTrackPostProcKalman(); - ~CvBlobTrackPostProcKalman(); - CvBlob* Process(CvBlob* pBlob); - void Release(); - virtual void ParamUpdate(); -}; /* class CvBlobTrackPostProcKalman */ - - -CvBlobTrackPostProcKalman::CvBlobTrackPostProcKalman() -{ - m_ModelNoise = 1e-6f; - m_DataNoisePos = 1e-6f; - m_DataNoiseSize = 1e-1f; - - #if STATE_NUM>6 - m_DataNoiseSize *= (float)pow(20.,2.); - #else - m_DataNoiseSize /= (float)pow(20.,2.); - #endif - - AddParam("ModelNoise",&m_ModelNoise); - AddParam("DataNoisePos",&m_DataNoisePos); - AddParam("DataNoiseSize",&m_DataNoiseSize); - - m_Frame = 0; - m_pKalman = cvCreateKalman(STATE_NUM,4); - memcpy( m_pKalman->transition_matrix->data.fl, A, sizeof(A)); - memcpy( m_pKalman->measurement_matrix->data.fl, H, sizeof(H)); - - cvSetIdentity( m_pKalman->process_noise_cov, cvRealScalar(m_ModelNoise) ); - cvSetIdentity( m_pKalman->measurement_noise_cov, cvRealScalar(m_DataNoisePos) ); - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 2,2) = m_DataNoiseSize; - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 3,3) = m_DataNoiseSize; - cvSetIdentity( m_pKalman->error_cov_post, cvRealScalar(1)); - cvZero(m_pKalman->state_post); - cvZero(m_pKalman->state_pre); -} - -CvBlobTrackPostProcKalman::~CvBlobTrackPostProcKalman() -{ - cvReleaseKalman(&m_pKalman); -} - -void CvBlobTrackPostProcKalman::ParamUpdate() -{ - cvSetIdentity( m_pKalman->process_noise_cov, cvRealScalar(m_ModelNoise) ); - cvSetIdentity( m_pKalman->measurement_noise_cov, cvRealScalar(m_DataNoisePos) ); - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 2,2) = m_DataNoiseSize; - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 3,3) = m_DataNoiseSize; -} - -CvBlob* CvBlobTrackPostProcKalman::Process(CvBlob* pBlob) -{ - CvBlob* pBlobRes = &m_Blob; - float Z[4]; - CvMat Zmat = cvMat(4,1,CV_32F,Z); - m_Blob = pBlob[0]; - - if(m_Frame < 2) - { /* First call: */ - m_pKalman->state_post->data.fl[0+4] = CV_BLOB_X(pBlob)-m_pKalman->state_post->data.fl[0]; - m_pKalman->state_post->data.fl[1+4] = CV_BLOB_Y(pBlob)-m_pKalman->state_post->data.fl[1]; - if(m_pKalman->DP>6) - { - m_pKalman->state_post->data.fl[2+4] = CV_BLOB_WX(pBlob)-m_pKalman->state_post->data.fl[2]; - m_pKalman->state_post->data.fl[3+4] = CV_BLOB_WY(pBlob)-m_pKalman->state_post->data.fl[3]; - } - m_pKalman->state_post->data.fl[0] = CV_BLOB_X(pBlob); - m_pKalman->state_post->data.fl[1] = CV_BLOB_Y(pBlob); - m_pKalman->state_post->data.fl[2] = CV_BLOB_WX(pBlob); - m_pKalman->state_post->data.fl[3] = CV_BLOB_WY(pBlob); - } - else - { /* Nonfirst call: */ - cvKalmanPredict(m_pKalman,0); - Z[0] = CV_BLOB_X(pBlob); - Z[1] = CV_BLOB_Y(pBlob); - Z[2] = CV_BLOB_WX(pBlob); - Z[3] = CV_BLOB_WY(pBlob); - cvKalmanCorrect(m_pKalman,&Zmat); - cvMatMulAdd(m_pKalman->measurement_matrix, m_pKalman->state_post, NULL, &Zmat); - CV_BLOB_X(pBlobRes) = Z[0]; - CV_BLOB_Y(pBlobRes) = Z[1]; -// CV_BLOB_WX(pBlobRes) = Z[2]; -// CV_BLOB_WY(pBlobRes) = Z[3]; - } - m_Frame++; - return pBlobRes; -} - -void CvBlobTrackPostProcKalman::Release() -{ - delete this; -} - -CvBlobTrackPostProcOne* cvCreateModuleBlobTrackPostProcKalmanOne() -{ - return (CvBlobTrackPostProcOne*) new CvBlobTrackPostProcKalman; -} - -CvBlobTrackPostProc* cvCreateModuleBlobTrackPostProcKalman() -{ - return cvCreateBlobTrackPostProcList(cvCreateModuleBlobTrackPostProcKalmanOne); -} -/*======================= KALMAN FILTER =========================*/ - - - -/*======================= KALMAN PREDICTOR =========================*/ -class CvBlobTrackPredictKalman:public CvBlobTrackPredictor -{ - -private: - CvBlob m_BlobPredict; - CvKalman* m_pKalman; - int m_Frame; - float m_ModelNoise; - float m_DataNoisePos; - float m_DataNoiseSize; - -public: - CvBlobTrackPredictKalman(); - ~CvBlobTrackPredictKalman(); - CvBlob* Predict(); - void Update(CvBlob* pBlob); - virtual void ParamUpdate(); - void Release() - { - delete this; - } -}; /* class CvBlobTrackPredictKalman */ - - -void CvBlobTrackPredictKalman::ParamUpdate() -{ - cvSetIdentity( m_pKalman->process_noise_cov, cvRealScalar(m_ModelNoise) ); - cvSetIdentity( m_pKalman->measurement_noise_cov, cvRealScalar(m_DataNoisePos) ); - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 2,2) = m_DataNoiseSize; - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 3,3) = m_DataNoiseSize; -} - -CvBlobTrackPredictKalman::CvBlobTrackPredictKalman() -{ - m_ModelNoise = 1e-6f; - m_DataNoisePos = 1e-6f; - m_DataNoiseSize = 1e-1f; - - #if STATE_NUM>6 - m_DataNoiseSize *= (float)pow(20.,2.); - #else - m_DataNoiseSize /= (float)pow(20.,2.); - #endif - - AddParam("ModelNoise",&m_ModelNoise); - AddParam("DataNoisePos",&m_DataNoisePos); - AddParam("DataNoiseSize",&m_DataNoiseSize); - - m_Frame = 0; - m_pKalman = cvCreateKalman(STATE_NUM,4); - memcpy( m_pKalman->transition_matrix->data.fl, A, sizeof(A)); - memcpy( m_pKalman->measurement_matrix->data.fl, H, sizeof(H)); - - cvSetIdentity( m_pKalman->process_noise_cov, cvRealScalar(m_ModelNoise) ); - cvSetIdentity( m_pKalman->measurement_noise_cov, cvRealScalar(m_DataNoisePos) ); - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 2,2) = m_DataNoiseSize; - CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 3,3) = m_DataNoiseSize; - cvSetIdentity( m_pKalman->error_cov_post, cvRealScalar(1)); - cvZero(m_pKalman->state_post); - cvZero(m_pKalman->state_pre); -} - -CvBlobTrackPredictKalman::~CvBlobTrackPredictKalman() -{ - cvReleaseKalman(&m_pKalman); -} - -CvBlob* CvBlobTrackPredictKalman::Predict() -{ - if(m_Frame >= 2) - { - cvKalmanPredict(m_pKalman,0); - m_BlobPredict.x = m_pKalman->state_pre->data.fl[0]; - m_BlobPredict.y = m_pKalman->state_pre->data.fl[1]; - m_BlobPredict.w = m_pKalman->state_pre->data.fl[2]; - m_BlobPredict.h = m_pKalman->state_pre->data.fl[3]; - } - return &m_BlobPredict; -} - -void CvBlobTrackPredictKalman::Update(CvBlob* pBlob) -{ - float Z[4]; - CvMat Zmat = cvMat(4,1,CV_32F,Z); - m_BlobPredict = pBlob[0]; - - if(m_Frame < 2) - { /* First call: */ - m_pKalman->state_post->data.fl[0+4] = CV_BLOB_X(pBlob)-m_pKalman->state_post->data.fl[0]; - m_pKalman->state_post->data.fl[1+4] = CV_BLOB_Y(pBlob)-m_pKalman->state_post->data.fl[1]; - if(m_pKalman->DP>6) - { - m_pKalman->state_post->data.fl[2+4] = CV_BLOB_WX(pBlob)-m_pKalman->state_post->data.fl[2]; - m_pKalman->state_post->data.fl[3+4] = CV_BLOB_WY(pBlob)-m_pKalman->state_post->data.fl[3]; - } - m_pKalman->state_post->data.fl[0] = CV_BLOB_X(pBlob); - m_pKalman->state_post->data.fl[1] = CV_BLOB_Y(pBlob); - m_pKalman->state_post->data.fl[2] = CV_BLOB_WX(pBlob); - m_pKalman->state_post->data.fl[3] = CV_BLOB_WY(pBlob); - } - else - { /* Nonfirst call: */ - Z[0] = CV_BLOB_X(pBlob); - Z[1] = CV_BLOB_Y(pBlob); - Z[2] = CV_BLOB_WX(pBlob); - Z[3] = CV_BLOB_WY(pBlob); - cvKalmanCorrect(m_pKalman,&Zmat); - } - - cvKalmanPredict(m_pKalman,0); - - m_Frame++; - -} /* Update. */ - -CvBlobTrackPredictor* cvCreateModuleBlobTrackPredictKalman() -{ - return (CvBlobTrackPredictor*) new CvBlobTrackPredictKalman; -} -/*======================= KALMAN PREDICTOR =========================*/ -