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// For Open Source Computer Vision Library
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#include "_cvaux.h"
#if _MSC_VER >= 1200
#pragma warning(disable:4786) // Disable MSVC warnings in the standard library.
#pragma warning(disable:4100)
#pragma warning(disable:4512)
#endif
#include <stdio.h>
#include <map>
#include <algorithm>
#if _MSC_VER >= 1200
#pragma warning(default:4100)
#pragma warning(default:4512)
#endif
#define ARRAY_SIZEOF(a) (sizeof(a)/sizeof((a)[0]))
static void FillObjectPoints(CvPoint3D32f *obj_points, CvSize etalon_size, float square_size);
static void DrawEtalon(IplImage *img, CvPoint2D32f *corners,
int corner_count, CvSize etalon_size, int draw_ordered);
static void MultMatrix(float rm[4][4], const float m1[4][4], const float m2[4][4]);
static void MultVectorMatrix(float rv[4], const float v[4], const float m[4][4]);
static CvPoint3D32f ImageCStoWorldCS(const Cv3dTrackerCameraInfo &camera_info, CvPoint2D32f p);
static bool intersection(CvPoint3D32f o1, CvPoint3D32f p1,
CvPoint3D32f o2, CvPoint3D32f p2,
CvPoint3D32f &r1, CvPoint3D32f &r2);
/////////////////////////////////
// cv3dTrackerCalibrateCameras //
/////////////////////////////////
CV_IMPL CvBool cv3dTrackerCalibrateCameras(int num_cameras,
const Cv3dTrackerCameraIntrinsics camera_intrinsics[], // size is num_cameras
CvSize etalon_size,
float square_size,
IplImage *samples[], // size is num_cameras
Cv3dTrackerCameraInfo camera_info[]) // size is num_cameras
{
CV_FUNCNAME("cv3dTrackerCalibrateCameras");
const int num_points = etalon_size.width * etalon_size.height;
int cameras_done = 0; // the number of cameras whose positions have been determined
CvPoint3D32f *object_points = NULL; // real-world coordinates of checkerboard points
CvPoint2D32f *points = NULL; // 2d coordinates of checkerboard points as seen by a camera
IplImage *gray_img = NULL; // temporary image for color conversion
IplImage *tmp_img = NULL; // temporary image used by FindChessboardCornerGuesses
int c, i, j;
if (etalon_size.width < 3 || etalon_size.height < 3)
CV_ERROR(CV_StsBadArg, "Chess board size is invalid");
for (c = 0; c < num_cameras; c++)
{
// CV_CHECK_IMAGE is not available in the cvaux library
// so perform the checks inline.
//CV_CALL(CV_CHECK_IMAGE(samples[c]));
if( samples[c] == NULL )
CV_ERROR( CV_HeaderIsNull, "Null image" );
if( samples[c]->dataOrder != IPL_DATA_ORDER_PIXEL && samples[c]->nChannels > 1 )
CV_ERROR( CV_BadOrder, "Unsupported image format" );
if( samples[c]->maskROI != 0 || samples[c]->tileInfo != 0 )
CV_ERROR( CV_StsBadArg, "Unsupported image format" );
if( samples[c]->imageData == 0 )
CV_ERROR( CV_BadDataPtr, "Null image data" );
if( samples[c]->roi &&
((samples[c]->roi->xOffset | samples[c]->roi->yOffset
| samples[c]->roi->width | samples[c]->roi->height) < 0 ||
samples[c]->roi->xOffset + samples[c]->roi->width > samples[c]->width ||
samples[c]->roi->yOffset + samples[c]->roi->height > samples[c]->height ||
(unsigned) (samples[c]->roi->coi) > (unsigned) (samples[c]->nChannels)))
CV_ERROR( CV_BadROISize, "Invalid ROI" );
// End of CV_CHECK_IMAGE inline expansion
if (samples[c]->depth != IPL_DEPTH_8U)
CV_ERROR(CV_BadDepth, "Channel depth of source image must be 8");
if (samples[c]->nChannels != 3 && samples[c]->nChannels != 1)
CV_ERROR(CV_BadNumChannels, "Source image must have 1 or 3 channels");
}
CV_CALL(object_points = (CvPoint3D32f *)cvAlloc(num_points * sizeof(CvPoint3D32f)));
CV_CALL(points = (CvPoint2D32f *)cvAlloc(num_points * sizeof(CvPoint2D32f)));
// fill in the real-world coordinates of the checkerboard points
FillObjectPoints(object_points, etalon_size, square_size);
for (c = 0; c < num_cameras; c++)
{
CvSize image_size = cvSize(samples[c]->width, samples[c]->height);
IplImage *img;
// The input samples are not required to all have the same size or color
// format. If they have different sizes, the temporary images are
// reallocated as necessary.
if (samples[c]->nChannels == 3)
{
// convert to gray
if (gray_img == NULL || gray_img->width != samples[c]->width ||
gray_img->height != samples[c]->height )
{
if (gray_img != NULL)
cvReleaseImage(&gray_img);
CV_CALL(gray_img = cvCreateImage(image_size, IPL_DEPTH_8U, 1));
}
CV_CALL(cvCvtColor(samples[c], gray_img, CV_BGR2GRAY));
img = gray_img;
}
else
{
// no color conversion required
img = samples[c];
}
if (tmp_img == NULL || tmp_img->width != samples[c]->width ||
tmp_img->height != samples[c]->height )
{
if (tmp_img != NULL)
cvReleaseImage(&tmp_img);
CV_CALL(tmp_img = cvCreateImage(image_size, IPL_DEPTH_8U, 1));
}
int count = num_points;
bool found = cvFindChessBoardCornerGuesses(img, tmp_img, 0,
etalon_size, points, &count) != 0;
if (count == 0)
continue;
// If found is true, it means all the points were found (count = num_points).
// If found is false but count is non-zero, it means that not all points were found.
cvFindCornerSubPix(img, points, count, cvSize(5,5), cvSize(-1,-1),
cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10, 0.01f));
// If the image origin is BL (bottom-left), fix the y coordinates
// so they are relative to the true top of the image.
if (samples[c]->origin == IPL_ORIGIN_BL)
{
for (i = 0; i < count; i++)
points[i].y = samples[c]->height - 1 - points[i].y;
}
if (found)
{
// Make sure x coordinates are increasing and y coordinates are decreasing.
// (The y coordinate of point (0,0) should be the greatest, because the point
// on the checkerboard that is the origin is nearest the bottom of the image.)
// This is done after adjusting the y coordinates according to the image origin.
if (points[0].x > points[1].x)
{
// reverse points in each row
for (j = 0; j < etalon_size.height; j++)
{
CvPoint2D32f *row = &points[j*etalon_size.width];
for (i = 0; i < etalon_size.width/2; i++)
std::swap(row[i], row[etalon_size.width-i-1]);
}
}
if (points[0].y < points[etalon_size.width].y)
{
// reverse points in each column
for (i = 0; i < etalon_size.width; i++)
{
for (j = 0; j < etalon_size.height/2; j++)
std::swap(points[i+j*etalon_size.width],
points[i+(etalon_size.height-j-1)*etalon_size.width]);
}
}
}
DrawEtalon(samples[c], points, count, etalon_size, found);
if (!found)
continue;
float rotVect[3];
float rotMatr[9];
float transVect[3];
cvFindExtrinsicCameraParams(count,
image_size,
points,
object_points,
const_cast<float *>(camera_intrinsics[c].focal_length),
camera_intrinsics[c].principal_point,
const_cast<float *>(camera_intrinsics[c].distortion),
rotVect,
transVect);
// Check result against an arbitrary limit to eliminate impossible values.
// (If the chess board were truly that far away, the camera wouldn't be able to
// see the squares.)
if (transVect[0] > 1000*square_size
|| transVect[1] > 1000*square_size
|| transVect[2] > 1000*square_size)
{
// ignore impossible results
continue;
}
CvMat rotMatrDescr = cvMat(3, 3, CV_32FC1, rotMatr);
CvMat rotVectDescr = cvMat(3, 1, CV_32FC1, rotVect);
/* Calc rotation matrix by Rodrigues Transform */
cvRodrigues2( &rotVectDescr, &rotMatrDescr );
//combine the two transformations into one matrix
//order is important! rotations are not commutative
float tmat[4][4] = { { 1.f, 0.f, 0.f, 0.f },
{ 0.f, 1.f, 0.f, 0.f },
{ 0.f, 0.f, 1.f, 0.f },
{ transVect[0], transVect[1], transVect[2], 1.f } };
float rmat[4][4] = { { rotMatr[0], rotMatr[1], rotMatr[2], 0.f },
{ rotMatr[3], rotMatr[4], rotMatr[5], 0.f },
{ rotMatr[6], rotMatr[7], rotMatr[8], 0.f },
{ 0.f, 0.f, 0.f, 1.f } };
MultMatrix(camera_info[c].mat, tmat, rmat);
// change the transformation of the cameras to put them in the world coordinate
// system we want to work with.
// Start with an identity matrix; then fill in the values to accomplish
// the desired transformation.
float smat[4][4] = { { 1.f, 0.f, 0.f, 0.f },
{ 0.f, 1.f, 0.f, 0.f },
{ 0.f, 0.f, 1.f, 0.f },
{ 0.f, 0.f, 0.f, 1.f } };
// First, reflect through the origin by inverting all three axes.
smat[0][0] = -1.f;
smat[1][1] = -1.f;
smat[2][2] = -1.f;
MultMatrix(tmat, camera_info[c].mat, smat);
// Scale x and y coordinates by the focal length (allowing for non-square pixels
// and/or non-symmetrical lenses).
smat[0][0] = 1.0f / camera_intrinsics[c].focal_length[0];
smat[1][1] = 1.0f / camera_intrinsics[c].focal_length[1];
smat[2][2] = 1.0f;
MultMatrix(camera_info[c].mat, smat, tmat);
camera_info[c].principal_point = camera_intrinsics[c].principal_point;
camera_info[c].valid = true;
cameras_done++;
}
exit:
cvReleaseImage(&gray_img);
cvReleaseImage(&tmp_img);
cvFree(&object_points);
cvFree(&points);
return cameras_done == num_cameras;
}
// fill in the real-world coordinates of the checkerboard points
static void FillObjectPoints(CvPoint3D32f *obj_points, CvSize etalon_size, float square_size)
{
int x, y, i;
for (y = 0, i = 0; y < etalon_size.height; y++)
{
for (x = 0; x < etalon_size.width; x++, i++)
{
obj_points[i].x = square_size * x;
obj_points[i].y = square_size * y;
obj_points[i].z = 0;
}
}
}
// Mark the points found on the input image
// The marks are drawn multi-colored if all the points were found.
static void DrawEtalon(IplImage *img, CvPoint2D32f *corners,
int corner_count, CvSize etalon_size, int draw_ordered)
{
const int r = 4;
int i;
int x, y;
CvPoint prev_pt = { 0, 0 };
static const CvScalar rgb_colors[] = {
{{0,0,255}},
{{0,128,255}},
{{0,200,200}},
{{0,255,0}},
{{200,200,0}},
{{255,0,0}},
{{255,0,255}} };
static const CvScalar gray_colors[] = {
{{80}}, {{120}}, {{160}}, {{200}}, {{100}}, {{140}}, {{180}}
};
const CvScalar* colors = img->nChannels == 3 ? rgb_colors : gray_colors;
CvScalar color = colors[0];
for (y = 0, i = 0; y < etalon_size.height; y++)
{
if (draw_ordered)
color = colors[y % ARRAY_SIZEOF(rgb_colors)];
for (x = 0; x < etalon_size.width && i < corner_count; x++, i++)
{
CvPoint pt;
pt.x = cvRound(corners[i].x);
pt.y = cvRound(corners[i].y);
if (img->origin == IPL_ORIGIN_BL)
pt.y = img->height - 1 - pt.y;
if (draw_ordered)
{
if (i != 0)
cvLine(img, prev_pt, pt, color, 1, CV_AA);
prev_pt = pt;
}
cvLine( img, cvPoint(pt.x - r, pt.y - r),
cvPoint(pt.x + r, pt.y + r), color, 1, CV_AA );
cvLine( img, cvPoint(pt.x - r, pt.y + r),
cvPoint(pt.x + r, pt.y - r), color, 1, CV_AA );
cvCircle( img, pt, r+1, color, 1, CV_AA );
}
}
}
// Find the midpoint of the line segment between two points.
static CvPoint3D32f midpoint(const CvPoint3D32f &p1, const CvPoint3D32f &p2)
{
return cvPoint3D32f((p1.x+p2.x)/2, (p1.y+p2.y)/2, (p1.z+p2.z)/2);
}
static void operator +=(CvPoint3D32f &p1, const CvPoint3D32f &p2)
{
p1.x += p2.x;
p1.y += p2.y;
p1.z += p2.z;
}
static CvPoint3D32f operator /(const CvPoint3D32f &p, int d)
{
return cvPoint3D32f(p.x/d, p.y/d, p.z/d);
}
static const Cv3dTracker2dTrackedObject *find(const Cv3dTracker2dTrackedObject v[], int num_objects, int id)
{
for (int i = 0; i < num_objects; i++)
{
if (v[i].id == id)
return &v[i];
}
return NULL;
}
#define CAMERA_POS(c) (cvPoint3D32f((c).mat[3][0], (c).mat[3][1], (c).mat[3][2]))
//////////////////////////////
// cv3dTrackerLocateObjects //
//////////////////////////////
CV_IMPL int cv3dTrackerLocateObjects(int num_cameras, int num_objects,
const Cv3dTrackerCameraInfo camera_info[], // size is num_cameras
const Cv3dTracker2dTrackedObject tracking_info[], // size is num_objects*num_cameras
Cv3dTrackerTrackedObject tracked_objects[]) // size is num_objects
{
/*CV_FUNCNAME("cv3dTrackerLocateObjects");*/
int found_objects = 0;
// count how many cameras could see each object
std::map<int, int> count;
for (int c = 0; c < num_cameras; c++)
{
if (!camera_info[c].valid)
continue;
for (int i = 0; i < num_objects; i++)
{
const Cv3dTracker2dTrackedObject *o = &tracking_info[c*num_objects+i];
if (o->id != -1)
count[o->id]++;
}
}
// process each object that was seen by at least two cameras
for (std::map<int, int>::iterator i = count.begin(); i != count.end(); i++)
{
if (i->second < 2)
continue; // ignore object seen by only one camera
int id = i->first;
// find an approximation of the objects location for each pair of cameras that
// could see this object, and average them
CvPoint3D32f total = cvPoint3D32f(0, 0, 0);
int weight = 0;
for (int c1 = 0; c1 < num_cameras-1; c1++)
{
if (!camera_info[c1].valid)
continue;
const Cv3dTracker2dTrackedObject *o1 = find(&tracking_info[c1*num_objects],
num_objects, id);
if (o1 == NULL)
continue; // this camera didn't see this object
CvPoint3D32f p1a = CAMERA_POS(camera_info[c1]);
CvPoint3D32f p1b = ImageCStoWorldCS(camera_info[c1], o1->p);
for (int c2 = c1 + 1; c2 < num_cameras; c2++)
{
if (!camera_info[c2].valid)
continue;
const Cv3dTracker2dTrackedObject *o2 = find(&tracking_info[c2*num_objects],
num_objects, id);
if (o2 == NULL)
continue; // this camera didn't see this object
CvPoint3D32f p2a = CAMERA_POS(camera_info[c2]);
CvPoint3D32f p2b = ImageCStoWorldCS(camera_info[c2], o2->p);
// these variables are initialized simply to avoid erroneous error messages
// from the compiler
CvPoint3D32f r1 = cvPoint3D32f(0, 0, 0);
CvPoint3D32f r2 = cvPoint3D32f(0, 0, 0);
// find the intersection of the two lines (or the points of closest
// approach, if they don't intersect)
if (!intersection(p1a, p1b, p2a, p2b, r1, r2))
continue;
total += midpoint(r1, r2);
weight++;
}
}
CvPoint3D32f center = total/weight;
tracked_objects[found_objects++] = cv3dTrackerTrackedObject(id, center);
}
return found_objects;
}
#define EPS 1e-9
// Compute the determinant of the 3x3 matrix represented by 3 row vectors.
static inline double det(CvPoint3D32f v1, CvPoint3D32f v2, CvPoint3D32f v3)
{
return v1.x*v2.y*v3.z + v1.z*v2.x*v3.y + v1.y*v2.z*v3.x
- v1.z*v2.y*v3.x - v1.x*v2.z*v3.y - v1.y*v2.x*v3.z;
}
static CvPoint3D32f operator +(CvPoint3D32f a, CvPoint3D32f b)
{
return cvPoint3D32f(a.x + b.x, a.y + b.y, a.z + b.z);
}
static CvPoint3D32f operator -(CvPoint3D32f a, CvPoint3D32f b)
{
return cvPoint3D32f(a.x - b.x, a.y - b.y, a.z - b.z);
}
static CvPoint3D32f operator *(CvPoint3D32f v, double f)
{
return cvPoint3D32f(f*v.x, f*v.y, f*v.z);
}
// Find the intersection of two lines, or if they don't intersect,
// the points of closest approach.
// The lines are defined by (o1,p1) and (o2, p2).
// If they intersect, r1 and r2 will be the same.
// Returns false on error.
static bool intersection(CvPoint3D32f o1, CvPoint3D32f p1,
CvPoint3D32f o2, CvPoint3D32f p2,
CvPoint3D32f &r1, CvPoint3D32f &r2)
{
CvPoint3D32f x = o2 - o1;
CvPoint3D32f d1 = p1 - o1;
CvPoint3D32f d2 = p2 - o2;
CvPoint3D32f cross = cvPoint3D32f(d1.y*d2.z - d1.z*d2.y,
d1.z*d2.x - d1.x*d2.z,
d1.x*d2.y - d1.y*d2.x);
double den = cross.x*cross.x + cross.y*cross.y + cross.z*cross.z;
if (den < EPS)
return false;
double t1 = det(x, d2, cross) / den;
double t2 = det(x, d1, cross) / den;
r1 = o1 + d1 * t1;
r2 = o2 + d2 * t2;
return true;
}
// Convert from image to camera space by transforming point p in
// the image plane by the camera matrix.
static CvPoint3D32f ImageCStoWorldCS(const Cv3dTrackerCameraInfo &camera_info, CvPoint2D32f p)
{
float tp[4];
tp[0] = (float)p.x - camera_info.principal_point.x;
tp[1] = (float)p.y - camera_info.principal_point.y;
tp[2] = 1.f;
tp[3] = 1.f;
float tr[4];
//multiply tp by mat to get tr
MultVectorMatrix(tr, tp, camera_info.mat);
return cvPoint3D32f(tr[0]/tr[3], tr[1]/tr[3], tr[2]/tr[3]);
}
// Multiply affine transformation m1 by the affine transformation m2 and
// return the result in rm.
static void MultMatrix(float rm[4][4], const float m1[4][4], const float m2[4][4])
{
for (int i=0; i<=3; i++)
for (int j=0; j<=3; j++)
{
rm[i][j]= 0.0;
for (int k=0; k <= 3; k++)
rm[i][j] += m1[i][k]*m2[k][j];
}
}
// Multiply the vector v by the affine transformation matrix m and return the
// result in rv.
void MultVectorMatrix(float rv[4], const float v[4], const float m[4][4])
{
for (int i=0; i<=3; i++)
{
rv[i] = 0.f;
for (int j=0;j<=3;j++)
rv[i] += v[j] * m[j][i];
}
}