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one_way_descriptor.cpp

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/*
*  one_way_descriptor.cpp
*
*
*  Created by Victor  Eruhimov on 4/19/09.
*  Copyright 2009 Argus Corp. All rights reserved.
*
*/


static const float pi = 3.1415926;

#include <stdio.h>

#include <outlet_pose_estimation/detail/one_way_descriptor.h>

#include <highgui.h>

static inline CvPoint rect_center(CvRect rect)
{
        return cvPoint(rect.x + rect.width/2, rect.y + rect.height/2);
}

void homography_transform(IplImage* frontal, IplImage* result, CvMat* homography)
{
        cvWarpPerspective(frontal, result, homography);
}

CvAffinePose perturbate_pose(CvAffinePose pose, float noise)
{
        // perturbate the matrix
        float noise_mult_factor = 1 + (0.5f - float(rand())/RAND_MAX)*noise;
        float noise_add_factor = noise_mult_factor - 1;

        CvAffinePose pose_pert = pose;
        pose_pert.phi += noise_add_factor;
        pose_pert.theta += noise_mult_factor;
        pose_pert.lambda1 *= noise_mult_factor;
        pose_pert.lambda2 *= noise_mult_factor;

        return pose_pert;
}

void generate_mean_patch(IplImage* frontal, IplImage* result, CvAffinePose pose, int pose_count, float noise)
{
        IplImage* sum = cvCreateImage(cvSize(result->width, result->height), IPL_DEPTH_32F, 1);
        IplImage* workspace = cvCloneImage(result);
        IplImage* workspace_float = cvCloneImage(sum);

        cvSetZero(sum);
        for(int i = 0; i < pose_count; i++)
        {
                CvAffinePose pose_pert = perturbate_pose(pose, noise);

                AffineTransformPatch(frontal, workspace, pose_pert);
                cvConvertScale(workspace, workspace_float);
                cvAdd(sum, workspace_float, sum);
        }

        cvConvertScale(sum, result, 1.0f/pose_count);

        cvReleaseImage(&workspace);
        cvReleaseImage(&sum);
        cvReleaseImage(&workspace_float);
}

void generate_mean_patch_fast(IplImage* frontal, IplImage* result, CvAffinePose pose,
                                                          CvMat* pca_hr_avg, CvMat* pca_hr_eigenvectors, const CvOneWayDescriptor* pca_descriptors)
{
        for(int i = 0; i < pca_hr_eigenvectors->cols; i++)
        {

        }
}


CvOneWayDescriptor::CvOneWayDescriptor()
{
        m_pose_count = 0;
        m_samples = 0;
        m_input_patch = 0;
        m_train_patch = 0;
        m_pca_coeffs = 0;
        m_affine_poses = 0;
        m_transforms = 0;
        m_pca_dim_low = 100;
        m_pca_dim_high = 100;
}

CvOneWayDescriptor::~CvOneWayDescriptor()
{
        if(m_pose_count)
        {
                for(int i = 0; i < m_pose_count; i++)
                {
                        cvReleaseImage(&m_samples[i]);
                        cvReleaseMat(&m_pca_coeffs[i]);
                }
                cvReleaseImage(&m_input_patch);
                cvReleaseImage(&m_train_patch);
                delete []m_samples;
                delete []m_pca_coeffs;

                if(!m_transforms)
                {
                        delete []m_affine_poses;
                }
        }
}

void CvOneWayDescriptor::Allocate(int pose_count, CvSize size, int nChannels)
{
        m_pose_count = pose_count;
        m_samples = new IplImage* [m_pose_count];
        m_pca_coeffs = new CvMat* [m_pose_count];
        m_patch_size = cvSize(size.width/2, size.height/2);

        if(!m_transforms)
        {
                m_affine_poses = new CvAffinePose[m_pose_count];
        }

        int length = m_pca_dim_low;//roi.width*roi.height;
        for(int i = 0; i < m_pose_count; i++)
        {
                m_samples[i] = cvCreateImage(cvSize(size.width/2, size.height/2), IPL_DEPTH_32F, nChannels);
                m_pca_coeffs[i] = cvCreateMat(1, length, CV_32FC1);
        }

        m_input_patch = cvCreateImage(GetPatchSize(), IPL_DEPTH_8U, 1);
        m_train_patch = cvCreateImage(GetInputPatchSize(), IPL_DEPTH_8U, 1);
}

void cvmSet2DPoint(CvMat* matrix, int row, int col, CvPoint2D32f point)
{
        cvmSet(matrix, row, col, point.x);
        cvmSet(matrix, row, col + 1, point.y);
}

void cvmSet3DPoint(CvMat* matrix, int row, int col, CvPoint3D32f point)
{
        cvmSet(matrix, row, col, point.x);
        cvmSet(matrix, row, col + 1, point.y);
        cvmSet(matrix, row, col + 2, point.z);
}

CvAffinePose GenRandomAffinePose()
{
        const float scale_min = 0.8f;
        const float scale_max = 1.2f;
        CvAffinePose pose;
        pose.theta = float(rand())/RAND_MAX*120 - 60;
        pose.phi = float(rand())/RAND_MAX*360;
        pose.lambda1 = scale_min + float(rand())/RAND_MAX*(scale_max - scale_min);
        pose.lambda2 = scale_min + float(rand())/RAND_MAX*(scale_max - scale_min);

        return pose;
}

void GenerateAffineTransformFromPose(CvSize size, CvAffinePose pose, CvMat* transform)
{
        CvMat* temp = cvCreateMat(3, 3, CV_32FC1);
        CvMat* final = cvCreateMat(3, 3, CV_32FC1);
        cvmSet(temp, 2, 0, 0.0f);
        cvmSet(temp, 2, 1, 0.0f);
        cvmSet(temp, 2, 2, 1.0f);

        CvMat rotation;
        cvGetSubRect(temp, &rotation, cvRect(0, 0, 3, 2));

        cv2DRotationMatrix(cvPoint2D32f(size.width/2, size.height/2), pose.phi, 1.0, &rotation);
        cvCopy(temp, final);

        cvmSet(temp, 0, 0, pose.lambda1);
        cvmSet(temp, 0, 1, 0.0f);
        cvmSet(temp, 1, 0, 0.0f);
        cvmSet(temp, 1, 1, pose.lambda2);
        cvmSet(temp, 0, 2, size.width/2*(1 - pose.lambda1));
        cvmSet(temp, 1, 2, size.height/2*(1 - pose.lambda2));
        cvMatMul(temp, final, final);

        cv2DRotationMatrix(cvPoint2D32f(size.width/2, size.height/2), pose.theta - pose.phi, 1.0, &rotation);
        cvMatMul(temp, final, final);

        cvGetSubRect(final, &rotation, cvRect(0, 0, 3, 2));
        cvCopy(&rotation, transform);

        cvReleaseMat(&temp);
        cvReleaseMat(&final);
}

void AffineTransformPatch(IplImage* src, IplImage* dst, CvAffinePose pose)
{
        CvRect src_large_roi = cvGetImageROI(src);

        IplImage* temp = cvCreateImage(cvSize(src_large_roi.width, src_large_roi.height), IPL_DEPTH_32F, src->nChannels);
        cvSetZero(temp);
        IplImage* temp2 = cvCloneImage(temp);
        CvMat* rotation_phi = cvCreateMat(2, 3, CV_32FC1);

        CvSize new_size = cvSize(temp->width*pose.lambda1, temp->height*pose.lambda2);
        IplImage* temp3 = cvCreateImage(new_size, IPL_DEPTH_32F, src->nChannels);

        cvConvertScale(src, temp);
        cvResetImageROI(temp);


        cv2DRotationMatrix(cvPoint2D32f(temp->width/2, temp->height/2), pose.phi, 1.0, rotation_phi);
        cvWarpAffine(temp, temp2, rotation_phi);

        cvSetZero(temp);

        cvResize(temp2, temp3);

        cv2DRotationMatrix(cvPoint2D32f(temp3->width/2, temp3->height/2), pose.theta - pose.phi, 1.0, rotation_phi);
        cvWarpAffine(temp3, temp, rotation_phi);

        cvSetImageROI(temp, cvRect(temp->width/2 - src_large_roi.width/4, temp->height/2 - src_large_roi.height/4,
                src_large_roi.width/2, src_large_roi.height/2));
        cvConvertScale(temp, dst);
        cvReleaseMat(&rotation_phi);

        cvReleaseImage(&temp3);
        cvReleaseImage(&temp2);
        cvReleaseImage(&temp);
}

void CvOneWayDescriptor::GenerateSamples(int pose_count, IplImage* frontal, int norm)
{
        /*    if(m_transforms)
        {
        GenerateSamplesWithTransforms(pose_count, frontal);
        return;
        }
        */
        CvRect roi = cvGetImageROI(frontal);
        IplImage* patch_8u = cvCreateImage(cvSize(roi.width/2, roi.height/2), frontal->depth, frontal->nChannels);
        for(int i = 0; i < pose_count; i++)
        {
                if(!m_transforms)
                {
                        m_affine_poses[i] = GenRandomAffinePose();
                }
                //AffineTransformPatch(frontal, patch_8u, m_affine_poses[i]);
                generate_mean_patch(frontal, patch_8u, m_affine_poses[i], num_mean_components, noise_intensity);

                float scale = 1.0f;
                if(norm)
                {
                        float sum = cvSum(patch_8u).val[0];
                        scale = 1/sum;
                }
                cvConvertScale(patch_8u, m_samples[i], scale);

#if 0
                double maxval;
                cvMinMaxLoc(m_samples[i], 0, &maxval);
                IplImage* test = cvCreateImage(cvSize(roi.width/2, roi.height/2), IPL_DEPTH_8U, 1);
                cvConvertScale(m_samples[i], test, 255.0/maxval);
                cvNamedWindow("1", 1);
                cvShowImage("1", test);
                cvWaitKey(0);
#endif
        }
        cvReleaseImage(&patch_8u);
}

void CvOneWayDescriptor::GenerateSamplesFast(IplImage* frontal, CvMat* pca_hr_avg,
                                                                                         CvMat* pca_hr_eigenvectors, CvOneWayDescriptor* pca_descriptors)
{
        CvRect roi = cvGetImageROI(frontal);
        if(roi.width != GetInputPatchSize().width || roi.height != GetInputPatchSize().height)
        {
                cvResize(frontal, m_train_patch);
                frontal = m_train_patch;
        }

        CvMat* pca_coeffs = cvCreateMat(1, pca_hr_eigenvectors->cols, CV_32FC1);
        double maxval;
        cvMinMaxLoc(frontal, 0, &maxval);
        CvMat* frontal_data = ConvertImageToMatrix(frontal);

        float sum = cvSum(frontal_data).val[0];
        cvConvertScale(frontal_data, frontal_data, 1.0f/sum);
        cvProjectPCA(frontal_data, pca_hr_avg, pca_hr_eigenvectors, pca_coeffs);
        for(int i = 0; i < m_pose_count; i++)
        {
                cvSetZero(m_samples[i]);
                for(int j = 0; j < m_pca_dim_high; j++)
                {
                        float coeff = cvmGet(pca_coeffs, 0, j);
                        IplImage* patch = pca_descriptors[j + 1].GetPatch(i);
                        cvAddWeighted(m_samples[i], 1.0, patch, coeff, 0, m_samples[i]);

#if 0
                        printf("coeff%d = %f\n", j, coeff);
                        IplImage* test = cvCreateImage(cvSize(12, 12), IPL_DEPTH_8U, 1);
                        double maxval;
                        cvMinMaxLoc(patch, 0, &maxval);
                        cvConvertScale(patch, test, 255.0/maxval);
                        cvNamedWindow("1", 1);
                        cvShowImage("1", test);
                        cvWaitKey(0);
#endif
                }

                cvAdd(pca_descriptors[0].GetPatch(i), m_samples[i], m_samples[i]);
                float sum = cvSum(m_samples[i]).val[0];
                cvConvertScale(m_samples[i], m_samples[i], 1.0/sum);

#if 0
                IplImage* test = cvCreateImage(cvSize(12, 12), IPL_DEPTH_8U, 1);
                /*        IplImage* temp1 = cvCreateImage(cvSize(12, 12), IPL_DEPTH_32F, 1);
                eigenvector2image(pca_hr_avg, temp1);
                IplImage* test = cvCreateImage(cvSize(12, 12), IPL_DEPTH_8U, 1);
                cvAdd(m_samples[i], temp1, temp1);
                cvMinMaxLoc(temp1, 0, &maxval);
                cvConvertScale(temp1, test, 255.0/maxval);*/
                cvMinMaxLoc(m_samples[i], 0, &maxval);
                cvConvertScale(m_samples[i], test, 255.0/maxval);

                cvNamedWindow("1", 1);
                cvShowImage("1", frontal);
                cvNamedWindow("2", 1);
                cvShowImage("2", test);
                cvWaitKey(0);
#endif
        }

        cvReleaseMat(&pca_coeffs);
        cvReleaseMat(&frontal_data);
}

void CvOneWayDescriptor::SetTransforms(CvAffinePose* poses, CvMat** transforms)
{
        if(m_affine_poses)
        {
                delete []m_affine_poses;
        }

        m_affine_poses = poses;
        m_transforms = transforms;
}

void CvOneWayDescriptor::Initialize(int pose_count, IplImage* frontal, const char* feature_name, int norm)
{
        m_feature_name = std::string(feature_name);
        CvRect roi = cvGetImageROI(frontal);
        m_center = rect_center(roi);

        Allocate(pose_count, cvSize(roi.width, roi.height), frontal->nChannels);

        GenerateSamples(pose_count, frontal, norm);
}

void CvOneWayDescriptor::InitializeFast(int pose_count, IplImage* frontal, const char* feature_name,
                                                                                CvMat* pca_hr_avg, CvMat* pca_hr_eigenvectors, CvOneWayDescriptor* pca_descriptors)
{
        if(pca_hr_avg == 0)
        {
                Initialize(pose_count, frontal, feature_name, 1);
                return;
        }
        m_feature_name = std::string(feature_name);
        CvRect roi = cvGetImageROI(frontal);
        m_center = rect_center(roi);

        Allocate(pose_count, cvSize(roi.width, roi.height), frontal->nChannels);

        GenerateSamplesFast(frontal, pca_hr_avg, pca_hr_eigenvectors, pca_descriptors);
}

void CvOneWayDescriptor::InitializePCACoeffs(CvMat* avg, CvMat* eigenvectors)
{
        for(int i = 0; i < m_pose_count; i++)
        {
                ProjectPCASample(m_samples[i], avg, eigenvectors, m_pca_coeffs[i]);
        }
}

void CvOneWayDescriptor::ProjectPCASample(IplImage* patch, CvMat* avg, CvMat* eigenvectors, CvMat* pca_coeffs) const
{
        CvMat* patch_mat = ConvertImageToMatrix(patch);
        //    CvMat eigenvectorsr;
        //    cvGetSubRect(eigenvectors, &eigenvectorsr, cvRect(0, 0, eigenvectors->cols, pca_coeffs->cols));
        CvMat* temp = cvCreateMat(1, eigenvectors->cols, CV_32FC1);
        cvProjectPCA(patch_mat, avg, eigenvectors, temp);
        CvMat temp1;
        cvGetSubRect(temp, &temp1, cvRect(0, 0, pca_coeffs->cols, 1));
        cvCopy(&temp1, pca_coeffs);

        cvReleaseMat(&temp);
        cvReleaseMat(&patch_mat);
}

void CvOneWayDescriptor::EstimatePosePCA(CvArr* patch, int& pose_idx, float& distance, CvMat* avg, CvMat* eigenvectors) const
{
        if(avg == 0)
        {
                // do not use pca
                if (!CV_IS_MAT(patch))
                {
                        EstimatePose((IplImage*)patch, pose_idx, distance);
                }
                else
                {

                }
                return;
        }
        CvRect roi;
        if (!CV_IS_MAT(patch))
        {
                roi = cvGetImageROI((IplImage*)patch);
                if(roi.width != GetPatchSize().width || roi.height != GetPatchSize().height)
                {
                        cvResize(patch, m_input_patch);
                        patch = m_input_patch;
                        roi = cvGetImageROI((IplImage*)patch);
                }
        }

        CvMat* pca_coeffs = cvCreateMat(1, m_pca_dim_low, CV_32FC1);

        if (CV_IS_MAT(patch))
        {
                cvCopy((CvMat*)patch, pca_coeffs);
        }
        else
        {
                IplImage* patch_32f = cvCreateImage(cvSize(roi.width, roi.height), IPL_DEPTH_32F, 1);
                float sum = cvSum(patch).val[0];
                cvConvertScale(patch, patch_32f, 1.0f/sum);
                ProjectPCASample(patch_32f, avg, eigenvectors, pca_coeffs);
                cvReleaseImage(&patch_32f);
        }


        distance = 1e10;
        pose_idx = -1;

        for(int i = 0; i < m_pose_count; i++)
        {
                float dist = cvNorm(m_pca_coeffs[i], pca_coeffs);
                //              float dist = 0;
                //              float data1, data2;
                //              //CvMat* pose_pca_coeffs = m_pca_coeffs[i];
                //              for (int x=0; x < pca_coeffs->width; x++)
                //                      for (int y =0 ; y < pca_coeffs->height; y++)
                //                      {
                //                              data1 = ((float*)(pca_coeffs->data.ptr + pca_coeffs->step*x))[y];
                //                              data2 = ((float*)(m_pca_coeffs[i]->data.ptr + m_pca_coeffs[i]->step*x))[y];
                //                              dist+=(data1-data2)*(data1-data2);
                //                      }
                //              for (int j = 0; j < m_pca_dim_low; j++)
                //              {
                //                      dist += (pose_pca_coeffs->data.fl[j]- pca_coeffs->data.fl[j])*(pose_pca_coeffs->data.fl[j]- pca_coeffs->data.fl[j]);
                //              }
                //#else
                //              for (int j = 0; j <= m_pca_dim_low - 4; j += 4)
                //              {
                //                      dist += (pose_pca_coeffs->data.fl[j]- pca_coeffs->data.fl[j])*
                //                              (pose_pca_coeffs->data.fl[j]- pca_coeffs->data.fl[j]);
                //                      dist += (pose_pca_coeffs->data.fl[j+1]- pca_coeffs->data.fl[j+1])*
                //                              (pose_pca_coeffs->data.fl[j+1]- pca_coeffs->data.fl[j+1]);
                //                      dist += (pose_pca_coeffs->data.fl[j+2]- pca_coeffs->data.fl[j+2])*
                //                              (pose_pca_coeffs->data.fl[j+2]- pca_coeffs->data.fl[j+2]);
                //                      dist += (pose_pca_coeffs->data.fl[j+3]- pca_coeffs->data.fl[j+3])*
                //                              (pose_pca_coeffs->data.fl[j+3]- pca_coeffs->data.fl[j+3]);
                //              }
                //#endif
                if(dist < distance)
                {
                        distance = dist;
                        pose_idx = i;
                }
        }

        cvReleaseMat(&pca_coeffs);
}

void CvOneWayDescriptor::EstimatePose(IplImage* patch, int& pose_idx, float& distance) const
{
        distance = 1e10;
        pose_idx = -1;

        CvRect roi = cvGetImageROI(patch);
        IplImage* patch_32f = cvCreateImage(cvSize(roi.width, roi.height), IPL_DEPTH_32F, patch->nChannels);
        float sum = cvSum(patch).val[0];
        cvConvertScale(patch, patch_32f, 1/sum);

        for(int i = 0; i < m_pose_count; i++)
        {
                if(m_samples[i]->width != patch_32f->width || m_samples[i]->height != patch_32f->height)
                {
                        continue;
                }
                float dist = cvNorm(m_samples[i], patch_32f);
                //float dist = 0.0f;
                //float i1,i2;

                //for (int y = 0; y<patch_32f->height; y++)
                //      for (int x = 0; x< patch_32f->width; x++)
                //      {
                //              i1 = ((float*)(m_samples[i]->imageData + m_samples[i]->widthStep*y))[x];
                //              i2 = ((float*)(patch_32f->imageData + patch_32f->widthStep*y))[x];
                //              dist+= (i1-i2)*(i1-i2);
                //      }

                if(dist < distance)
                {
                        distance = dist;
                        pose_idx = i;
                }

#if 0
                IplImage* img1 = cvCreateImage(cvSize(roi.width, roi.height), IPL_DEPTH_8U, 1);
                IplImage* img2 = cvCreateImage(cvSize(roi.width, roi.height), IPL_DEPTH_8U, 1);
                double maxval;
                cvMinMaxLoc(m_samples[i], 0, &maxval);
                cvConvertScale(m_samples[i], img1, 255.0/maxval);
                cvMinMaxLoc(patch_32f, 0, &maxval);
                cvConvertScale(patch_32f, img2, 255.0/maxval);

                cvNamedWindow("1", 1);
                cvShowImage("1", img1);
                cvNamedWindow("2", 1);
                cvShowImage("2", img2);
                printf("Distance = %f\n", dist);
                cvWaitKey(0);
#endif
        }

        cvReleaseImage(&patch_32f);
}

void CvOneWayDescriptor::Save(const char* path)
{
        for(int i = 0; i < m_pose_count; i++)
        {
                char buf[1024];
                sprintf(buf, "%s/patch_%04d.jpg", path, i);
                IplImage* patch = cvCreateImage(cvSize(m_samples[i]->width, m_samples[i]->height), IPL_DEPTH_8U, m_samples[i]->nChannels);

                double maxval;
                cvMinMaxLoc(m_samples[i], 0, &maxval);
                cvConvertScale(m_samples[i], patch, 255/maxval);

                cvSaveImage(buf, patch);

                cvReleaseImage(&patch);
        }
}

void CvOneWayDescriptor::Write(CvFileStorage* fs, const char* name)
{
        CvMat* mat = cvCreateMat(m_pose_count, m_samples[0]->width*m_samples[0]->height, CV_32FC1);

        // prepare data to write as a single matrix
        for(int i = 0; i < m_pose_count; i++)
        {
                for(int y = 0; y < m_samples[i]->height; y++)
                {
                        for(int x = 0; x < m_samples[i]->width; x++)
                        {
                                float val = *((float*)(m_samples[i]->imageData + m_samples[i]->widthStep*y) + x);
                                cvmSet(mat, i, y*m_samples[i]->width + x, val);
                        }
                }
        }

        cvWrite(fs, name, mat);

        cvReleaseMat(&mat);
}

int CvOneWayDescriptor::ReadByName(CvFileStorage* fs, CvFileNode* parent, const char* name)
{
        CvMat* mat = (CvMat*)cvReadByName(fs, parent, name);
        if(!mat)
        {
                return 0;
        }


        for(int i = 0; i < m_pose_count; i++)
        {
                for(int y = 0; y < m_samples[i]->height; y++)
                {
                        for(int x = 0; x < m_samples[i]->width; x++)
                        {
                                float val = cvmGet(mat, i, y*m_samples[i]->width + x);
                                *((float*)(m_samples[i]->imageData + y*m_samples[i]->widthStep) + x) = val;
                        }
                }
        }

        cvReleaseMat(&mat);
        return 1;
}

IplImage* CvOneWayDescriptor::GetPatch(int index)
{
        return m_samples[index];
}

CvAffinePose CvOneWayDescriptor::GetPose(int index) const
{
        return m_affine_poses[index];
}

void FindOneWayDescriptor(int desc_count, const CvOneWayDescriptor* descriptors, IplImage* patch, int& desc_idx, int& pose_idx, float& distance,
    CvMat* avg, CvMat* eigenvectors)
{
    desc_idx = -1;
    pose_idx = -1;
    distance = 1e10;
//--------
        //PCA_coeffs precalculating
        int m_pca_dim_low = descriptors[0].GetPCADimLow();
        CvMat* pca_coeffs = cvCreateMat(1, m_pca_dim_low, CV_32FC1);
        int patch_width = descriptors[0].GetPatchSize().width;
        int patch_height = descriptors[0].GetPatchSize().height;
        if (avg)
        {
                CvRect _roi = cvGetImageROI((IplImage*)patch);
                IplImage* test_img = cvCreateImage(cvSize(patch_width,patch_height), IPL_DEPTH_8U, 1);
                if(_roi.width != patch_width|| _roi.height != patch_height)
                {

                        cvResize(patch, test_img);
                        _roi = cvGetImageROI(test_img);
                }
                else
                {
                        cvCopy(patch,test_img);
                }
                IplImage* patch_32f = cvCreateImage(cvSize(_roi.width, _roi.height), IPL_DEPTH_32F, 1);
                float sum = cvSum(test_img).val[0];
                cvConvertScale(test_img, patch_32f, 1.0f/sum);

                //ProjectPCASample(patch_32f, avg, eigenvectors, pca_coeffs);
                //Projecting PCA
                CvMat* patch_mat = ConvertImageToMatrix(patch_32f);
                CvMat* temp = cvCreateMat(1, eigenvectors->cols, CV_32FC1);
                cvProjectPCA(patch_mat, avg, eigenvectors, temp);
                CvMat temp1;
                cvGetSubRect(temp, &temp1, cvRect(0, 0, pca_coeffs->cols, 1));
                cvCopy(&temp1, pca_coeffs);
                cvReleaseMat(&temp);
                cvReleaseMat(&patch_mat);
                //End of projecting

                cvReleaseImage(&patch_32f);
                cvReleaseImage(&test_img);
        }

//--------



    for(int i = 0; i < desc_count; i++)
    {
        int _pose_idx = -1;
        float _distance = 0;

#if 0
        descriptors[i].EstimatePose(patch, _pose_idx, _distance);
#else
                if (!avg)
                {
                        descriptors[i].EstimatePosePCA(patch, _pose_idx, _distance, avg, eigenvectors);
                }
                else
                {
                        descriptors[i].EstimatePosePCA(pca_coeffs, _pose_idx, _distance, avg, eigenvectors);
                }
#endif

        if(_distance < distance)
        {
            desc_idx = i;
            pose_idx = _pose_idx;
            distance = _distance;
        }
    }
        cvReleaseMat(&pca_coeffs);
}

#if defined(_KDTREE)

void FindOneWayDescriptor(cv::flann::Index* m_pca_descriptors_tree, CvSize patch_size, int m_pca_dim_low, int m_pose_count, IplImage* patch, int& desc_idx, int& pose_idx, float& distance,
    CvMat* avg, CvMat* eigenvectors)
{
    desc_idx = -1;
    pose_idx = -1;
    distance = 1e10;
//--------
        //PCA_coeffs precalculating
        CvMat* pca_coeffs = cvCreateMat(1, m_pca_dim_low, CV_32FC1);
        int patch_width = patch_size.width;
        int patch_height = patch_size.height;
        //if (avg)
        //{
                CvRect _roi = cvGetImageROI((IplImage*)patch);
                IplImage* test_img = cvCreateImage(cvSize(patch_width,patch_height), IPL_DEPTH_8U, 1);
                if(_roi.width != patch_width|| _roi.height != patch_height)
                {

                        cvResize(patch, test_img);
                        _roi = cvGetImageROI(test_img);
                }
                else
                {
                        cvCopy(patch,test_img);
                }
                IplImage* patch_32f = cvCreateImage(cvSize(_roi.width, _roi.height), IPL_DEPTH_32F, 1);
                float sum = cvSum(test_img).val[0];
                cvConvertScale(test_img, patch_32f, 1.0f/sum);

                //ProjectPCASample(patch_32f, avg, eigenvectors, pca_coeffs);
                //Projecting PCA
                CvMat* patch_mat = ConvertImageToMatrix(patch_32f);
                CvMat* temp = cvCreateMat(1, eigenvectors->cols, CV_32FC1);
                cvProjectPCA(patch_mat, avg, eigenvectors, temp);
                CvMat temp1;
                cvGetSubRect(temp, &temp1, cvRect(0, 0, pca_coeffs->cols, 1));
                cvCopy(&temp1, pca_coeffs);
                cvReleaseMat(&temp);
                cvReleaseMat(&patch_mat);
                //End of projecting

                cvReleaseImage(&patch_32f);
                cvReleaseImage(&test_img);
//      }

//--------

                //float* target = new float[m_pca_dim_low];
                //::flann::KNNResultSet res(1,pca_coeffs->data.fl,m_pca_dim_low);
                //::flann::SearchParams params;
                //params.checks = -1;

                //int maxDepth = 1000000;
                //int neighbors_count = 1;
                //int* neighborsIdx = new int[neighbors_count];
                //float* distances = new float[neighbors_count];
                //if (m_pca_descriptors_tree->findNearest(pca_coeffs->data.fl,neighbors_count,maxDepth,neighborsIdx,0,distances) > 0)
                //{
                //      desc_idx = neighborsIdx[0] / m_pose_count;
                //      pose_idx = neighborsIdx[0] % m_pose_count;
                //      distance = distances[0];
                //}
                //delete[] neighborsIdx;
                //delete[] distances;

                cv::Mat m_object(1, m_pca_dim_low, CV_32F);
                cv::Mat m_indices(1, 1, CV_32S);
                cv::Mat m_dists(1, 1, CV_32F);

                float* object_ptr = m_object.ptr<float>(0);
                for (int i=0;i<m_pca_dim_low;i++)
                {
                        object_ptr[i] = pca_coeffs->data.fl[i];
                }

                m_pca_descriptors_tree->knnSearch(m_object, m_indices, m_dists, 1, cv::flann::SearchParams(-1) );

                desc_idx = ((int*)(m_indices.ptr<int>(0)))[0] / m_pose_count;
                pose_idx = ((int*)(m_indices.ptr<int>(0)))[0] % m_pose_count;
                distance = ((float*)(m_dists.ptr<float>(0)))[0];

        //      delete[] target;


//    for(int i = 0; i < desc_count; i++)
//    {
//        int _pose_idx = -1;
//        float _distance = 0;
//
//#if 0
//        descriptors[i].EstimatePose(patch, _pose_idx, _distance);
//#else
//              if (!avg)
//              {
//                      descriptors[i].EstimatePosePCA(patch, _pose_idx, _distance, avg, eigenvectors);
//              }
//              else
//              {
//                      descriptors[i].EstimatePosePCA(pca_coeffs, _pose_idx, _distance, avg, eigenvectors);
//              }
//#endif
//
//        if(_distance < distance)
//        {
//            desc_idx = i;
//            pose_idx = _pose_idx;
//            distance = _distance;
//        }
//    }
        cvReleaseMat(&pca_coeffs);
}
#endif
//**
void FindOneWayDescriptor(int desc_count, const CvOneWayDescriptor* descriptors, IplImage* patch, int n,
            std::vector<int>& desc_idxs, std::vector<int>&  pose_idxs, std::vector<float>& distances,
                        CvMat* avg, CvMat* eigenvectors)
{
        for (int i=0;i<n;i++)
        {
                desc_idxs[i] = -1;
                pose_idxs[i] = -1;
                distances[i] = 1e10;
        }
        //--------
        //PCA_coeffs precalculating
        int m_pca_dim_low = descriptors[0].GetPCADimLow();
        CvMat* pca_coeffs = cvCreateMat(1, m_pca_dim_low, CV_32FC1);
        int patch_width = descriptors[0].GetPatchSize().width;
        int patch_height = descriptors[0].GetPatchSize().height;
        if (avg)
        {
                CvRect _roi = cvGetImageROI((IplImage*)patch);
                IplImage* test_img = cvCreateImage(cvSize(patch_width,patch_height), IPL_DEPTH_8U, 1);
                if(_roi.width != patch_width|| _roi.height != patch_height)
                {

                        cvResize(patch, test_img);
                        _roi = cvGetImageROI(test_img);
                }
                else
                {
                        cvCopy(patch,test_img);
                }
                IplImage* patch_32f = cvCreateImage(cvSize(_roi.width, _roi.height), IPL_DEPTH_32F, 1);
                float sum = cvSum(test_img).val[0];
                cvConvertScale(test_img, patch_32f, 1.0f/sum);

                //ProjectPCASample(patch_32f, avg, eigenvectors, pca_coeffs);
                //Projecting PCA
                CvMat* patch_mat = ConvertImageToMatrix(patch_32f);
                CvMat* temp = cvCreateMat(1, eigenvectors->cols, CV_32FC1);
                cvProjectPCA(patch_mat, avg, eigenvectors, temp);
                CvMat temp1;
                cvGetSubRect(temp, &temp1, cvRect(0, 0, pca_coeffs->cols, 1));
                cvCopy(&temp1, pca_coeffs);
                cvReleaseMat(&temp);
                cvReleaseMat(&patch_mat);
                //End of projecting

                cvReleaseImage(&patch_32f);
                cvReleaseImage(&test_img);
        }
        //--------



        for(int i = 0; i < desc_count; i++)
        {
                int _pose_idx = -1;
                float _distance = 0;

#if 0
                descriptors[i].EstimatePose(patch, _pose_idx, _distance);
#else
                if (!avg)
                {
                        descriptors[i].EstimatePosePCA(patch, _pose_idx, _distance, avg, eigenvectors);
                }
                else
                {
                        descriptors[i].EstimatePosePCA(pca_coeffs, _pose_idx, _distance, avg, eigenvectors);
                }
#endif

                for (int j=0;j<n;j++)
                {
                        if(_distance < distances[j])
                        {
                                for (int k=(n-1);k > j;k--)
                                {
                                        desc_idxs[k] = desc_idxs[k-1];
                                        pose_idxs[k] = pose_idxs[k-1];
                                        distances[k] = distances[k-1];
                                }
                                desc_idxs[j] = i;
                                pose_idxs[j] = _pose_idx;
                                distances[j] = _distance;
                                break;
                        }
                }
        }
        cvReleaseMat(&pca_coeffs);
}

void FindOneWayDescriptorEx(int desc_count, const CvOneWayDescriptor* descriptors, IplImage* patch,
                                                        float scale_min, float scale_max, float scale_step,
                                                        int& desc_idx, int& pose_idx, float& distance, float& scale,
                                                        CvMat* avg, CvMat* eigenvectors)
{
        CvSize patch_size = descriptors[0].GetPatchSize();
        IplImage* input_patch;
        CvRect roi;

        input_patch= cvCreateImage(patch_size, IPL_DEPTH_8U, 1);
        roi = cvGetImageROI((IplImage*)patch);

        int _desc_idx, _pose_idx;
        float _distance;
        distance = 1e10;
        for(float cur_scale = scale_min; cur_scale < scale_max; cur_scale *= scale_step)
        {
                //        printf("Scale = %f\n", cur_scale);

                CvRect roi_scaled = resize_rect(roi, cur_scale);
                cvSetImageROI(patch, roi_scaled);
                cvResize(patch, input_patch);


#if 0
                if(roi.x > 244 && roi.y < 200)
                {
                        cvNamedWindow("1", 1);
                        cvShowImage("1", input_patch);
                        cvWaitKey(0);
                }
#endif

                FindOneWayDescriptor(desc_count, descriptors, input_patch, _desc_idx, _pose_idx, _distance, avg, eigenvectors);
                if(_distance < distance)
                {
                        distance = _distance;
                        desc_idx = _desc_idx;
                        pose_idx = _pose_idx;
                        scale = cur_scale;
                }
        }


        cvSetImageROI((IplImage*)patch, roi);
        cvReleaseImage(&input_patch);

}

void FindOneWayDescriptorEx(int desc_count, const CvOneWayDescriptor* descriptors, IplImage* patch,
                                                        float scale_min, float scale_max, float scale_step,
                                                        int n, std::vector<int>& desc_idxs, std::vector<int>& pose_idxs,
                                                        std::vector<float>& distances, std::vector<float>& scales,
                                                        CvMat* avg, CvMat* eigenvectors)
{
        CvSize patch_size = descriptors[0].GetPatchSize();
        IplImage* input_patch;
        CvRect roi;

        input_patch= cvCreateImage(patch_size, IPL_DEPTH_8U, 1);
        roi = cvGetImageROI((IplImage*)patch);

        //  float min_distance = 1e10;
        std::vector<int> _desc_idxs;
        _desc_idxs.resize(n);
        std::vector<int> _pose_idxs;
        _pose_idxs.resize(n);
        std::vector<float> _distances;
        _distances.resize(n);


        for (int i=0;i<n;i++)
        {
                distances[i] = 1e10;
        }

        for(float cur_scale = scale_min; cur_scale < scale_max; cur_scale *= scale_step)
        {

                CvRect roi_scaled = resize_rect(roi, cur_scale);
                cvSetImageROI(patch, roi_scaled);
                cvResize(patch, input_patch);



                FindOneWayDescriptor(desc_count, descriptors, input_patch, n,_desc_idxs, _pose_idxs, _distances, avg, eigenvectors);
                for (int i=0;i<n;i++)
                {
                        if(_distances[i] < distances[i])
                        {
                                distances[i] = _distances[i];
                                desc_idxs[i] = _desc_idxs[i];
                                pose_idxs[i] = _pose_idxs[i];
                                scales[i] = cur_scale;
                        }
                }
        }



        cvSetImageROI((IplImage*)patch, roi);
        cvReleaseImage(&input_patch);
}

#if defined(_KDTREE)
void FindOneWayDescriptorEx(cv::flann::Index* m_pca_descriptors_tree, CvSize patch_size, int m_pca_dim_low,
                            int m_pose_count, IplImage* patch,
                                                        float scale_min, float scale_max, float scale_step,
                                                        int& desc_idx, int& pose_idx, float& distance, float& scale,
                                                        CvMat* avg, CvMat* eigenvectors)
{
        IplImage* input_patch;
        CvRect roi;

        input_patch= cvCreateImage(patch_size, IPL_DEPTH_8U, 1);
        roi = cvGetImageROI((IplImage*)patch);

        int _desc_idx, _pose_idx;
        float _distance;
        distance = 1e10;
        for(float cur_scale = scale_min; cur_scale < scale_max; cur_scale *= scale_step)
        {
                //        printf("Scale = %f\n", cur_scale);

                CvRect roi_scaled = resize_rect(roi, cur_scale);
                cvSetImageROI(patch, roi_scaled);
                cvResize(patch, input_patch);

                FindOneWayDescriptor(m_pca_descriptors_tree, patch_size, m_pca_dim_low, m_pose_count, input_patch, _desc_idx, _pose_idx, _distance, avg, eigenvectors);
                if(_distance < distance)
                {
                        distance = _distance;
                        desc_idx = _desc_idx;
                        pose_idx = _pose_idx;
                        scale = cur_scale;
                }
        }


        cvSetImageROI((IplImage*)patch, roi);
        cvReleaseImage(&input_patch);

}
#endif

const char* CvOneWayDescriptor::GetFeatureName() const
{
        return m_feature_name.c_str();
}

CvPoint CvOneWayDescriptor::GetCenter() const
{
        return m_center;
}

int CvOneWayDescriptor::GetPCADimLow() const
{
        return m_pca_dim_low;
}

int CvOneWayDescriptor::GetPCADimHigh() const
{
        return m_pca_dim_high;
}

---

outlet_pose_estimation
Author(s): Patrick Mihelich
autogenerated on Fri Mar 1 17:34:08 2013