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CPointCloud.cpp
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#include "CPointCloud.h"
CPointCloud::CPointCloud()
{
pointsPtr = NULL;
colorsPtr = NULL;
rotatePointsPtr = NULL;
libSvm.libsvmreadmodel();
}
CPointCloud::~CPointCloud()
{
}
void CPointCloud::getVoxelGrid(Mat matDepth, Mat matImage)
{
delete pointsPtr;
delete colorsPtr;
pointsPtr = NULL;
colorsPtr = NULL;
rows = matDepth.rows;
cols = matDepth.cols;
numPoints = rows*cols;
uint16_t *depth = (uint16_t*) matDepth.data; // depth image ptr
uint8_t *rgb = (uint8_t *) matImage.data;
double *points = new double[3*numPoints];
memset(points, 0, sizeof(double)*3*numPoints);
uint8_t* colors = new uint8_t[3*numPoints];
memset(colors, 0, sizeof(uint8_t)*3*numPoints);
uint8_t*counts = new uint8_t[numPoints];
memset(counts, 0, sizeof(uint8_t)*numPoints);
uint16_t maxDepth = 3500; // mm
double voxelDim = 20; // mm
double sideLengthX = 6000/voxelDim; //in voxel
double sideLengthY = 6000/voxelDim; //in voxel
register double fx, fy, cx, cy;
if(rows == 240 ||cols == 320)
{ //low resolution
fx = 1/(525.0/2);
fy = 1/(525.0/2);
cx = 159.75;
cy = 119.75;
}
else
{
fx = 1/525.0;
fy = 1/525.0;
cx = 319.5;
cy = 239.5;
}
//---------------------
uint32_t offsets[MAX_THREAD];
uint8_t numberOfThreads = 1;
register double invVoxelDim = 1/voxelDim;
#pragma omp parallel shared(numberOfThreads, depth, rgb, points,offsets, voxelDim, sideLengthX, sideLengthY)//,
{
int threadID = omp_get_thread_num();
int numThreads = omp_get_num_threads();
numberOfThreads = numThreads;
int pointsPerThread = numPoints/numThreads;
uint32_t freeOffset = threadID*pointsPerThread;
std::unordered_map<uint32_t, uint32_t> voxel;
int start = threadID * pointsPerThread;
int finish = start + pointsPerThread - 1;
double x, y, z;
uint32_t offset, count;
double invCount;
for (int i=start; i<=finish; i++)
{
if (depth[i] <= 0 || depth[i] > maxDepth)
{
continue;
}//if
z = depth[i];
x= -((i%cols) - cx)*z*fx;
y = -((i/cols) - cy)*z*fy; // assuming depth not mirrored
uint32_t voxelID = (uint32_t)(x*invVoxelDim+sideLengthX/2) + (uint32_t)(y*invVoxelDim+sideLengthY/2)*sideLengthX + (uint32_t)(z*invVoxelDim)*sideLengthX*sideLengthY;
if (voxel.count(voxelID) == 0)
{
voxel[voxelID] = freeOffset;
colors[3*freeOffset] = rgb[3*i];//rgb[i];
colors[3*freeOffset+1] = rgb[3*i+1];//rgb[i+numPoints];
colors[3*freeOffset+2] = rgb[3*i+2];//rgb[i+2*numPoints];
freeOffset++;
}// if voxel
offset = voxel[voxelID];
count = (uint32_t)counts[offset];
invCount = 1/(count+1.0);
// average among the points falling in the same voxel
points[3*offset] = (points[3*offset]*count + x) * invCount;
points[3*offset+1] = (points[3*offset+1]*count + y) * invCount;
points[3*offset+2] = (points[3*offset+2]*count + z) * invCount;
counts[offset]++;
}// for
offsets[threadID] = freeOffset - threadID*pointsPerThread;
}
int start = 0;
for (int i=1; i<numberOfThreads; i++)
{
start += offsets[i-1];
memcpy(&colors[3*start + 1], &colors[3*i*numPoints/numberOfThreads + 1], sizeof(uint8_t)*offsets[i]*3);
memcpy(&points[3*start + 1], &points[3*i*numPoints/numberOfThreads + 1], sizeof(double)*offsets[i]*3);
}
num_after_voxel = start + offsets[numberOfThreads-1];
pointsPtr = new double [3*num_after_voxel];
colorsPtr = new uint8_t[3*num_after_voxel];
#pragma omp parallel for
for(int i=0; i<num_after_voxel; i++)
{
pointsPtr[3*i] = points[3*i];
pointsPtr[3*i+1] = points[3*i +1];
pointsPtr[3*i+2] = points[3*i+2];
colorsPtr[3*i] = colors[3*i];
colorsPtr[3* i+1] = colors[3*i+1];
colorsPtr[3* i+2] = colors[3*i +2];
}
delete points;
delete colors;
delete counts;
}
bool CPointCloud::getGroundPlane(PlaneParmeters& best_plane, float maxInclinationAngle , float tol )
{
float collinearityThreshold = sin(0.1*CV_PI/180);
if(maxInclinationAngle >90)
{
maxInclinationAngle = 90;
}
if(maxInclinationAngle <10)
{
maxInclinationAngle = 10;
}
tol = 2; //default 1e-6
float minTolWall = deg2rad(maxInclinationAngle);
float maxTolWall = deg2rad(180 - maxInclinationAngle);
int tentative_num = 30;
vector<Point3d>ptsCut;
//cut points;
for(int i=0; i<num_after_voxel; i++)
{
if(pointsPtr[3*i+1]<0)
{
ptsCut.push_back(Point3d(pointsPtr[3*i], pointsPtr[3*i+1], pointsPtr[3*i+2]));
}
}
int cutSize = ptsCut.size();
if(cutSize< tentative_num*3)
{
best_plane.a = 0;
best_plane.b = 0;
best_plane.c = 0;
best_plane.d = 0;
cout<< "no enough poitns to estimate ground plane!"<<endl;
return false;
}
int best_count = 0;
srand((int)time(0));
while(tentative_num>0)
{
int id1 = rand()%cutSize;
int id2 = rand()%cutSize;
int id3 = rand()%cutSize;
Point3d P1,P2,P3;
P1 = ptsCut[id1];
P2 = ptsCut[id2];
P3 = ptsCut[id3];
Point3d u, v;
u = P2 - P1;
double normU = sqrt(u.x*u.x + u.y*u.y + u.z*u.z);
u.x = u.x/normU;
u.y = u.y/normU;
u.z = u.z/normU;
v = P3- P1;
double normV = sqrt(v.x*v.x + v.y*v.y + v.z*v.z);
v.x = v.x/normU;
v.y = v.y/normU;
v.z = v.z/normU;
// plane normal
double planeNormalX = u.y*v.z - u.z*v.y;
double planeNormalY = u.z*v.x - u.x*v.z;
double planeNormalZ = u.x*v.y - u.y*v.x;
double planeNorm = sqrt((double)(planeNormalX*planeNormalX +planeNormalY*planeNormalY +planeNormalZ*planeNormalZ));
if(planeNorm < collinearityThreshold)
{
continue;
}
double planeToCheckX = planeNormalX/planeNorm;
double planeToCheckY = planeNormalY/planeNorm;
double planeToCheckZ = planeNormalZ/planeNorm;
double angleWithYaxis = acos(planeToCheckY);
if(angleWithYaxis>minTolWall &&angleWithYaxis <maxTolWall)
{
continue;
}
double d = (-planeToCheckX*P1.x) + (-planeToCheckY*P1.y) + (-planeToCheckZ*P1.z);
PlaneParmeters plane;
plane.a = planeToCheckX/d;
plane.b = planeToCheckY/d;
plane.c = planeToCheckZ/d;
plane.d = d/d;
int count = nnz(pointsPtr, plane, tol);
if(count>best_count)
{
best_count = count;
best_plane = plane;
}
tentative_num = tentative_num - 1;
} //while
if(best_plane.b <0)
{
best_plane =best_plane*(-1);
}
return true;
}
void CPointCloud::rotatePointCloud(PlaneParmeters floorParmeters, Mat& matInv)
{
PlaneParmeters floor;
if(floorParmeters.b <0 )
{
floor = floorParmeters*(-1);
}
else
{
floor = floorParmeters;
}
float normFloor = sqrt(floor.a*floor.a + floor.b*floor.b + floor.c*floor.c);
float floorVersorX = floor.a/normFloor;
float floorVersorY = floor.b/normFloor;
float floorVersonZ = floor.c/normFloor;
float tol = 1e-6;
float sum = floorVersorX*floorVersorX + floorVersorY*floorVersorY + (floorVersonZ-1)*(floorVersonZ-1);
bool isDo = sqrt(sum)<tol;
if(isDo)
{
rotatePointsPtr = pointsPtr;
return;
}
rotatePointsPtr = new double[num_after_voxel*3];
// obtain the axis (see angle next) of rotation of camera zAxis w.r.t. the floorVersor
float axisOfRotationX = floorVersorY;
float axisOfRotationY = -floorVersorX;
float axisOfRotationZ = 0;
float normAxisOfRotation = sqrt(axisOfRotationX*axisOfRotationX + axisOfRotationY*axisOfRotationY + axisOfRotationZ*axisOfRotationZ);
axisOfRotationX = axisOfRotationX/normAxisOfRotation;
axisOfRotationY = axisOfRotationY/normAxisOfRotation;
axisOfRotationZ = axisOfRotationZ/normAxisOfRotation;
// 1) determine rotation of the x-axis to correct eventual roll of camera
// roll = acos(dot(axisOfRotation, xAxis)/(norm(axisOfRotation)*norm(xAxis)));
float normAxisOfRotation2 = sqrt((float)(axisOfRotationX*axisOfRotationX + axisOfRotationY*axisOfRotationY + axisOfRotationZ*axisOfRotationZ));
float roll = acos(axisOfRotationX/normAxisOfRotation2);
float angleRotX;
if(axisOfRotationY >0)
{
angleRotX = -roll;
}
else
{
angleRotX = +roll;
}
Mat RotOfX, RotOfXY, R, rot;
rotationMatrixFromAxisAndAngle(0, 0, 1, angleRotX, RotOfX);
// 2) rotate camera plane xy of CV_PI
rotationMatrixFromAxisAndAngle(0, 0, 1,-CV_PI, RotOfXY);
// 3) rotate around new x-axis to make zAxis pointing to plane versor direction
float floorVersorNorm = sqrt(floorVersorX*floorVersorX + floorVersorY*floorVersorY+floorVersonZ*floorVersonZ);
// angle between floor Versor and zAxis
float angle = acos(floorVersonZ/floorVersorNorm) ;
rotationMatrixFromAxisAndAngle(1, 0, 0, -angle, R);
rot = R * RotOfXY *RotOfX;
float dist = abs(floor.d)/normFloor;
for(int i=0; i<num_after_voxel; i++)
{
rotatePointsPtr[3*i] = rot.at<double>(0,0)*pointsPtr[3*i] +rot.at<double>(0,1)*pointsPtr[3*i+1] + rot.at<double>(0,2)*pointsPtr[3*i+2] + 0;
rotatePointsPtr[3*i+1] = rot.at<double>(1,0)*pointsPtr[3*i] +rot.at<double>(1,1)*pointsPtr[3*i+1] + rot.at<double>(1,2)*pointsPtr[3*i+2] + 0;
rotatePointsPtr[3*i+2] = rot.at<double>(2,0)*pointsPtr[3*i] +rot.at<double>(2,1)*pointsPtr[3*i+1] + rot.at<double>(2,2)*pointsPtr[3*i+2] + dist;
}
Mat invRotOfX ,invRotOfXY, invR;
rotationMatrixFromAxisAndAngle(0, 0, 1,-angleRotX, invRotOfX);
rotationMatrixFromAxisAndAngle(0, 0, 1, CV_PI, invRotOfXY);
rotationMatrixFromAxisAndAngle(1, 0, 0, angle, invR);
Mat invRot = invRotOfX *invRotOfXY *invR;
double x1 = invRot.at<double>(0,0);
double y1 = invRot.at<double>(0,1);
double z1 = invRot.at<double>(0,2);
double x2 = invRot.at<double>(1,0);
double y2 = invRot.at<double>(1,1);
double z2 = invRot.at<double>(1,2);
double x3 = invRot.at<double>(2,0);
double y3 = invRot.at<double>(2,1);
double z3 = invRot.at<double>(2,2);
matInv = (Mat_<double>(4,4)<<x1, y1, z1, z1*(-dist),
x2, y2, z2, z2*(-dist),
x3, y3, z3, z3*(-dist),
0, 0, 0, 1);
matInv.copyTo(invM);
}
void CPointCloud::getCandidateLegs(vector<Candidate>&cadidates)
{
double footCutHeight = 210; //mm
double personCutHeight = 2000; //mm
double footCutBase = 30;
double legCutBase = 10;
vector<Point3d> voxelGridPoints;
vector<Point3d> footCutPoints;
vector<Point3i> voxelGridColors;
vector<Point3i> footCutColors;
for(int i=0; i<num_after_voxel; i++)
{
double height = rotatePointsPtr[3*i+2];
if(height >legCutBase && height<personCutHeight)
{
if(height>footCutBase && height<footCutHeight) // get footCutPoints
{
footCutPoints.push_back(Point3d(rotatePointsPtr[3*i+0], rotatePointsPtr[3*i+1], rotatePointsPtr[3*i+2]));
footCutColors.push_back(Point3d(colorsPtr[3*i],colorsPtr[3*i+1],colorsPtr[3*i+2]));
}
else
{
voxelGridPoints.push_back(Point3d(rotatePointsPtr[3*i+0], rotatePointsPtr[3*i+1], rotatePointsPtr[3*i+2]));
voxelGridColors.push_back(Point3d(colorsPtr[3*i+0],colorsPtr[3*i+1],colorsPtr[3*i+2]));
}
}
}
if(footCutPoints.size() == 0)
{
return;
}
vector<int>classes(footCutPoints.size());
vector<int>types(footCutPoints.size());
dbscanClustering(Mat(footCutPoints), 5, 40,classes, types);
int nClusters;
vector<int>::iterator biggest = max_element( begin(classes), end(classes));
nClusters = *biggest;
double minTol = 50; // min foot size in mm
double maxTol = 600;// max foot size in mm
double minNumPoints = 20; //minimum number of points to consider a cluster
vector<vector<Point3d>>nFootPoints(nClusters);
vector<vector<Point3d>>nFootColors(nClusters);
vector<int>clusterOK(nClusters);
vector<int>candidateOK(nClusters);
Mat centroidsOnFloorTmp = Mat::zeros(Size(2,nClusters),CV_64FC1);
for(int i=0; i<footCutPoints.size(); i++)
{
int id = classes[i];
if(id<=0) continue;
nFootPoints[id-1].push_back(footCutPoints[i]);
nFootColors[id-1].push_back(footCutColors[i]);
}
for(int i=0; i<nClusters; i++)
{
Candidate cadTmp;
if(nFootPoints[i].size()<minNumPoints)
{
clusterOK[i] = 0;
continue;
}
minBoundingBox(nFootPoints[i],cadTmp.rectangleOnFloor);
double x0 = cadTmp.rectangleOnFloor[0].x;
double y0 = cadTmp.rectangleOnFloor[0].y;
double x1 = cadTmp.rectangleOnFloor[1].x;
double y1 = cadTmp.rectangleOnFloor[1].y;
double x2 = cadTmp.rectangleOnFloor[2].x;
double y2 = cadTmp.rectangleOnFloor[2].y;
double l1 = sqrt((x0-x1)*(x0-x1) + (y0-y1)*(y0-y1));
double l2 = sqrt((x2-x1)*(x2-x1) + (y2-y1)*(y2-y1));
if(l1<minTol && l2<minTol)
{
clusterOK[i] = 0;
continue;
}
clusterOK[i] = 1;
if (l1<maxTol && l2<maxTol && l1>minTol && l2>minTol)
{
candidateOK[i] = 1;
float sumX = 0;
float sumY = 0;
for(int m=0; m<nFootPoints[i].size(); m++)
{
sumX += nFootPoints[i][m].x;
sumY += nFootPoints[i][m].y;
}
centroidsOnFloorTmp.at<double>(i,0) =(double) sumX/nFootPoints[i].size();
centroidsOnFloorTmp.at<double>(i,1) = (double)sumY/nFootPoints[i].size();
cadTmp.footPoints = Mat::zeros(nFootPoints[i].size(),1,CV_64FC3);
cadTmp.footPoints = Mat::zeros(nFootColors[i].size(),1,CV_8UC3);
Mat(nFootColors[i]).copyTo(cadTmp.footColors);
Mat(nFootPoints[i]).copyTo(cadTmp.footPoints);
//cadTmp.footPoints = Mat(nFootPoints[i]);
cadTmp.centroid = Point2d(centroidsOnFloorTmp.at<double>(i,0),centroidsOnFloorTmp.at<double>(i,1));
cadidates.push_back(cadTmp);
}
} //for
Mat centroidsOnFloor = Mat::zeros(Size(2,nClusters),CV_64FC1);
int forward= 0;
int backward = centroidsOnFloorTmp.rows -1;
for(int i=0; i<centroidsOnFloorTmp.rows; i++)
{
if(candidateOK[i] == 0)
{
centroidsOnFloor.at<double>(backward, 0) = centroidsOnFloorTmp.at<double>(i,0);
centroidsOnFloor.at<double>(backward, 1) = centroidsOnFloorTmp.at<double>(i,1);
backward--;
}
else
{
centroidsOnFloor.at<double>(forward, 0) = centroidsOnFloorTmp.at<double>(i,0);
centroidsOnFloor.at<double>(forward, 1) = centroidsOnFloorTmp.at<double>(i,1);
forward++;
}
}
expandCandidates(cadidates, centroidsOnFloor,Mat(voxelGridPoints), Mat(voxelGridColors));
}
void CPointCloud::expandCandidates(vector<Candidate>&candidates, Mat centroidOnFloorM, Mat voxelGridPoints, Mat voxelGridColors)
{
uint8_t *colors = (uint8_t*)voxelGridColors.data;
int srow = SHEIGHT/SSIDE;
int scol = SWIDTH/SSIDE;
//build kd-tree of all point cloud
PointCloud pointCloud;
pointCloud.pts = (double*)voxelGridPoints.data;
pointCloud.numPoints = voxelGridPoints.rows;
KDTreeSingleIndexAdaptor<L2_Simple_Adaptor<double, PointCloud>, PointCloud, 3 /* dim */> tree(3 /*dim*/, pointCloud, KDTreeSingleIndexAdaptorParams(20 /* max leaf */) );
tree.buildIndex();
size_t numCandidates = candidates.size();
size_t numPoints = voxelGridPoints.rows;
double* centroidsOnFloor = (double*)centroidOnFloorM.data;
size_t numCentroidsOnFloor = centroidOnFloorM.rows;
//allocations for filling candidates structs
double **footPointsPtrs = (double **)malloc(numCandidates*sizeof(double *));
double **legPointsPtrs = (double **)malloc(numCandidates*sizeof(double *));
double **legPointsNormalizedPtrs = (double **)malloc(numCandidates*sizeof(double *));
double **silhouettePtrs = (double **)malloc(numCandidates*sizeof(double *));
double **personPointsPtrs = (double **)malloc(numCandidates*sizeof(double *));
size_t *numFootPointsPtrs = (size_t *)malloc(numCandidates*sizeof(size_t));
size_t *actualNumLegPointsPtrs = (size_t *)malloc(numCandidates*sizeof(size_t));
size_t *actualNumPersonPointsPtrs = (size_t *)malloc(numCandidates*sizeof(size_t));
uint8_t **legColorsPtrs = (uint8_t **)malloc(numCandidates*sizeof(uint8_t *));
uint8_t **footColorsPtrs = (uint8_t **)malloc(numCandidates*sizeof(uint8_t *));
for (int i=0; i < numCandidates; i++)
{
footPointsPtrs[i] = (double*)candidates[i].footPoints.data;
numFootPointsPtrs[i] = candidates[i].footPoints.rows;
// legPoints
candidates[i].legPoints = Mat::zeros(Size(1,numPoints+numFootPointsPtrs[i]),CV_64FC3);
legPointsPtrs[i] = (double*)candidates[i].legPoints.data;
//legPointsNormalized
candidates[i].legPointsNormalized = Mat::zeros(Size(1, numPoints+numFootPointsPtrs[i]), CV_64FC3);
legPointsNormalizedPtrs[i] = (double*)candidates[i].legPointsNormalized.data;
//silhouette
candidates[i].silhouette = Mat::zeros(srow, scol, CV_64FC1);
silhouettePtrs[i] = (double*)candidates[i].silhouette.data;
// allPoints
candidates[i].allPoints = Mat::zeros(Size(1, numPoints+numFootPointsPtrs[i]), CV_64FC3);
personPointsPtrs[i] = (double*)candidates[i].allPoints.data;
//footColors
footColorsPtrs[i] = (uint8_t*)candidates[i].footColors.data;
// legColors
candidates[i].legColors = Mat::zeros(Size(1,numPoints+numFootPointsPtrs[i]),CV_8UC3);
legColorsPtrs[i] = (uint8_t*)candidates[i].legColors.data;
}// for
// array for points already considered for explansion
uint8_t *visited = (uint8_t*)calloc(numPoints, sizeof(uint8_t));
//expand candidates in parallel
int freeCandidate = 0;
#pragma omp parallel
{
int id;
while(true)
{
#pragma omp critical
{
id = freeCandidate;
freeCandidate++;
}
if(id >= numCandidates)
break;
expandCandidate(footPointsPtrs[id],
legPointsPtrs[id],
personPointsPtrs[id],
centroidsOnFloor,
&tree,
numFootPointsPtrs[id],
&actualNumLegPointsPtrs[id],
&actualNumPersonPointsPtrs[id],
numCentroidsOnFloor,
visited,
pointCloud.pts,
id,
colors,
legColorsPtrs[id],
footColorsPtrs[id],
legPointsNormalizedPtrs[id],
silhouettePtrs[id], numPoints);
}
}
//
for(int i=0; i<candidates.size(); i++)
{
// set legPoints actual num legs
candidates[i].legPoints = candidates[i].legPoints.rowRange(0, actualNumLegPointsPtrs[i]);
candidates[i].legColors = candidates[i].legColors.rowRange(0, actualNumLegPointsPtrs[i]);
candidates[i].legPointsNormalized = candidates[i].legPointsNormalized.rowRange(0, actualNumLegPointsPtrs[i]);
candidates[i].allPoints = candidates[i].allPoints.rowRange(0, actualNumPersonPointsPtrs[i]);
}
free(footPointsPtrs);
free(legPointsPtrs);
free(legPointsNormalizedPtrs);
free(personPointsPtrs);
free(numFootPointsPtrs);
free(actualNumPersonPointsPtrs);
free(actualNumLegPointsPtrs);
free(silhouettePtrs);
free(visited);
free(footColorsPtrs);
free(legColorsPtrs);
}
void CPointCloud::expandCandidate(double *footPoints, //footPoints of a candidates leg
double *legPoints,
double *personPoints,
double *centroidsOnFloor,
KDTreeSingleIndexAdaptor<L2_Simple_Adaptor<double, PointCloud>, PointCloud, 3> *tree,
size_t numFootPoints,
size_t *actualNumLegPoints,
size_t *actualNumPersonPoints,
size_t numCentroidsOnFloor,
uint8_t *visited,
double *points,
size_t idCandidate,
uint8_t *colors,
uint8_t *legColors,
uint8_t *footColors,
double *legPointsNormalized,
double *silhouette,
int numPoints)
{
int legCutHeight = LEG_CUT_HEIGHT;
double eps = DBSCAN_RADIUS;
int k = DBSCAN_NEIGH;
int reserveSize = 50;
double xMin=4000, yMin=4000, xMax = 0;
// foot centroid
double xCenter = centroidsOnFloor[idCandidate*2];
double yCenter = centroidsOnFloor[idCandidate*2+1];
// foot angle on the scene
double alpha = acos(yCenter/sqrt(xCenter*xCenter + yCenter*yCenter));
if (xCenter<0)
alpha = -alpha;
double cosAlpha = cos(alpha);
double sinAlpha = sin(alpha);
bool enabledColor = true;
if (colors == NULL || legColors == NULL || footColors == NULL)
enabledColor = false;
// copy foot data in leg fields
memcpy(legPoints, footPoints, numFootPoints*sizeof(double)*3);
if (enabledColor)
memcpy(legColors, footColors, numFootPoints*sizeof(uint8_t)*3);
*actualNumLegPoints = numFootPoints;
const double search_radius = static_cast<double>(eps*eps);
nanoflann::SearchParams params;
params.sorted = false;
queue<size_t> neigh;
double queryPoint[3];
std::vector<std::pair<size_t, double> > ret_matches;
// find immediate neighbors of foot points, from which it will start the expansion
for (int i=0; i<numFootPoints; i++) {
queryPoint[0] = footPoints[i*3];
queryPoint[1] = footPoints[i*3+1];
queryPoint[2] = footPoints[i*3+2];
legPointsNormalized[3*i] = cosAlpha*queryPoint[0]-sinAlpha*queryPoint[1];
legPointsNormalized[3*i+1] = sinAlpha*queryPoint[0]+cosAlpha*queryPoint[1];
legPointsNormalized[3*i+2] = queryPoint[2];
// find min and max coordinates for normalize the candidate
if (legPointsNormalized[3*i] < xMin)
xMin = legPointsNormalized[3*i];
if (legPointsNormalized[3*i] > xMax)
xMax = legPointsNormalized[3*i];
if (legPointsNormalized[3*i+1] < yMin)
yMin = legPointsNormalized[3*i+1];
// search neighbors of the current foot point
ret_matches.clear();
ret_matches.reserve(reserveSize);
const size_t nMatches = (*tree).radiusSearch(queryPoint, search_radius, ret_matches, params);
if (nMatches >= k) {
// border connected with outer points
for(int j=0;j<nMatches;j++) {
size_t id = ret_matches[j].first;
if(visited[id] == 0) {
// if not already visited add to expansion queue
neigh.push(id);
visited[id] = 1;
legPoints[(*actualNumLegPoints)*3] = points[3*id];
legPoints[(*actualNumLegPoints)*3+1] = points[3*id+1];
legPoints[(*actualNumLegPoints)*3+2] = points[3*id+2];
legPointsNormalized[(*actualNumLegPoints)*3] = cosAlpha*points[3*id]-sinAlpha*points[3*id+1];
legPointsNormalized[(*actualNumLegPoints)*3+1] = sinAlpha*points[3*id]+cosAlpha*points[3*id+1];
legPointsNormalized[(*actualNumLegPoints)*3+2] = points[3*id+2];
if (legPointsNormalized[(*actualNumLegPoints)*3] < xMin)
{
xMin = legPointsNormalized[(*actualNumLegPoints)*3];
}
if (legPointsNormalized[(*actualNumLegPoints)*3] > xMax)
{
xMax = legPointsNormalized[(*actualNumLegPoints)*3];
}
if (legPointsNormalized[(*actualNumLegPoints)*3+1] < yMin)
{
yMin = legPointsNormalized[(*actualNumLegPoints)*3+1];
}
if (enabledColor)
{
legColors[(*actualNumLegPoints)*3] = colors[3*id];
legColors[(*actualNumLegPoints)*3+1] = colors[3*id+1];
legColors[(*actualNumLegPoints)*3+2] = colors[3*id+2];
}
*actualNumLegPoints += 1;
}
}
}
}
// copy leg points into person points
memcpy(personPoints, legPoints, (*actualNumLegPoints)*sizeof(double)*3);
*actualNumPersonPoints = *actualNumLegPoints;
double x,y,z;
// expand the leg and the person starting from the just found border points
while(!neigh.empty()) {
size_t id = neigh.front();
neigh.pop();
queryPoint[0] = points[id*3];
queryPoint[1] = points[id*3+1];
queryPoint[2] = points[id*3+2];
// neighbors search
ret_matches.clear();
ret_matches.reserve(reserveSize);
const size_t nMatches = (*tree).radiusSearch(queryPoint, search_radius, ret_matches, params);
if (nMatches >= k+1) {
// core point
for(int j=0;j<nMatches;j++)
{
size_t idx = ret_matches[j].first;
if(visited[idx] == 0)
{
// check if belong to the current voronoi region
double minDist = 4000*4000;
int label = -1;
x = points[idx*3];
y = points[idx*3+1];
z = points[idx*3+2];
for (int t=0; t<numCentroidsOnFloor; t++)
{
// Voronoi
double dist = (x-centroidsOnFloor[t*2])*(x-centroidsOnFloor[t*2]) + (y-centroidsOnFloor[t*2+1])*(y-centroidsOnFloor[t*2+1]);
if (dist<minDist) {
minDist = dist;
label = t;
}
}
if (label == idCandidate)
{
// add to current expansion
neigh.push(idx);
visited[idx] = 1;
if (*actualNumPersonPoints >= numPoints+numFootPoints) {
//mexPrintf("numFootPoints: %d numPoints: %d actualPerson: %d actualLeg: %d\n", numFootPoints, numPoints, *actualNumPersonPoints, *actualNumLegPoints);
continue;
}
// add to person points
personPoints[(*actualNumPersonPoints)*3] = x;
personPoints[(*actualNumPersonPoints)*3+1] = y;
personPoints[(*actualNumPersonPoints)*3+2] = z;
*actualNumPersonPoints += 1;
if (z < legCutHeight)
{
// add to leg points
legPoints[(*actualNumLegPoints)*3] = x;
legPoints[(*actualNumLegPoints)*3+1] = y;
legPoints[(*actualNumLegPoints)*3+2] = z;
legPointsNormalized[(*actualNumLegPoints)*3] = cosAlpha*x-sinAlpha*y;
legPointsNormalized[(*actualNumLegPoints)*3+1] = sinAlpha*x+cosAlpha*y;
legPointsNormalized[(*actualNumLegPoints)*3+2] = z;
if (legPointsNormalized[(*actualNumLegPoints)*3] < xMin)
xMin = legPointsNormalized[(*actualNumLegPoints)*3];
if (legPointsNormalized[(*actualNumLegPoints)*3] > xMax)
xMax = legPointsNormalized[(*actualNumLegPoints)*3];
if (legPointsNormalized[(*actualNumLegPoints)*3+1] < yMin)
yMin = legPointsNormalized[(*actualNumLegPoints)*3+1];
if (enabledColor)
{
legColors[(*actualNumLegPoints)*3] = colors[idx*3];
legColors[(*actualNumLegPoints)*3+1] = colors[idx*3+1];
legColors[(*actualNumLegPoints)*3+2] = colors[idx*3+2];
}
*actualNumLegPoints += 1;
}
}
}
}
}
}
// normalize legPoints and create silhouette
int srow = SHEIGHT/SSIDE;
int scol = SWIDTH/SSIDE;
int sdepth = SDEPTH/SSIDE;
double xoff = (SWIDTH-(xMax-xMin))/2;
uint8_t *depthIndex = (uint8_t *)malloc(srow*scol*sizeof(uint8_t));
uint8_t *count = (uint8_t *)calloc(srow*scol,sizeof(uint8_t));
int currentRow, currentCol, currentDepth, linearIdx;
// compute linear idx where each leg points belong
for (int i=0; i<*actualNumLegPoints; i++)
{
legPointsNormalized[3*i] -= xMin;
legPointsNormalized[3*i+1] -= yMin;
currentRow = srow-1 - (int)(legPointsNormalized[3*i+2]/SSIDE);
currentCol = (int)((legPointsNormalized[3*i]+xoff)/SSIDE);
currentDepth = (int)(legPointsNormalized[3*i+1]/SSIDE)+1;
if (currentRow<0 || currentCol<0 || currentDepth<0 || currentRow>srow-1 || currentCol>scol-1 || currentDepth>sdepth-1) continue;
linearIdx = currentCol*srow + currentRow;
if (count[linearIdx] == 0 || currentDepth < depthIndex[linearIdx])
{
count[linearIdx] = 1;
silhouette[linearIdx] = legPointsNormalized[3*i+1];
depthIndex[linearIdx] = currentDepth;
}
else if (currentDepth == depthIndex[linearIdx])
{
silhouette[linearIdx] = (silhouette[linearIdx]*count[linearIdx] + legPointsNormalized[3*i+1])/(count[linearIdx] + 1);
count[linearIdx]++;
}
}
// fill silhouette holes
uint8_t *binary = depthIndex;
memset(binary, 0, srow*scol*sizeof(uint8_t));
for (int i=0; i<srow*scol; i++)
{
if (count[i] == 0)
{
silhouette[i] = SDEPTH;
} else
{
binary[i] = 2;
}
}
// dilate
for (int i=1; i<scol-1; i++)
{
for (int j=1; j<srow-1; j++)
{
if (binary[i*srow+j] == 2)
{
if (binary[(i-1)*srow+j] == 0) binary[(i-1)*srow+j] = 3;
if (binary[(i-1)*srow+j-1] == 0) binary[(i-1)*srow+j-1] = 3;
if (binary[(i)*srow+j-1] == 0) binary[(i)*srow+j-1] = 3;
if (binary[(i+1)*srow+j-1] == 0) binary[(i+1)*srow+j-1] = 3;
if (binary[(i+1)*srow+j] == 0) binary[(i+1)*srow+j] = 3;
if (binary[(i+1)*srow+j+1] == 0) binary[(i+1)*srow+j+1] = 3;
if (binary[(i)*srow+j+1] == 0) binary[(i)*srow+j+1] = 3;
if (binary[(i-1)*srow+j+1] == 0) binary[(i-1)*srow+j+1] = 3;
}
}
}
// erode
for (int i=1; i<scol-1; i++)
{
for (int j=1; j<srow-1; j++)
{
if (binary[i*srow+j] >= 2)
{
if (binary[(i-1)*srow+j] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i)*srow+j-1] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i+1)*srow+j-1] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i+1)*srow+j] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i+1)*srow+j+1] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i)*srow+j+1] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i-1)*srow+j+1] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
if (binary[(i-1)*srow+j-1] == 0)
{
binary[(i)*srow+j] = 1;
continue;
}
}
}
}
// fill hole in correspondence of 3 in binary image with average of non zero neighbors
double *silhouetteCopy = (double *)malloc(srow*scol*sizeof(double));
silhouetteCopy = (double *)memcpy(silhouetteCopy, silhouette, srow*scol*sizeof(double));
int numNeigh;
double mean;
for (int i=1; i<scol-1; i++) {
for (int j=1; j<srow-1; j++) {
if (binary[i*srow+j] == 3) {
mean = 0;
numNeigh = 0;
if (binary[(i-1)*srow+j] == 2) {
mean += silhouetteCopy[(i-1)*srow+j];
numNeigh++;
}
if (binary[(i)*srow+j-1] == 2) {
mean += silhouetteCopy[(i)*srow+j-1];
numNeigh++;
}
if (binary[(i+1)*srow+j-1] == 2) {
mean += silhouetteCopy[(i+1)*srow+j-1];
numNeigh++;
}
if (binary[(i+1)*srow+j] == 2) {
mean += silhouetteCopy[(i+1)*srow+j];
numNeigh++;
}
if (binary[(i+1)*srow+j+1] == 2) {
mean += silhouetteCopy[(i+1)*srow+j+1];
numNeigh++;
}