1 /*M///////////////////////////////////////////////////////////////////////////////////////
2 //
3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4 //
5 // By downloading, copying, installing or using the software you agree to this license.
6 // If you do not agree to this license, do not download, install,
7 // copy or use the software.
8 //
9 //
10 // Intel License Agreement
11 // For Open Source Computer Vision Library
12 //
13 // Copyright (C) 2002, Intel Corporation, all rights reserved.
14 // Third party copyrights are property of their respective owners.
15 //
16 // Redistribution and use in source and binary forms, with or without modification,
17 // are permitted provided that the following conditions are met:
18 //
19 // * Redistributions of source code must retain the above copyright notice,
20 // this list of conditions and the following disclaimer.
21 //
22 // * Redistributions in binary form must reproduce the above copyright notice,
23 // this list of conditions and the following disclaimer in the documentation
24 // and/or other materials provided with the distribution.
25 //
26 // * The name of Intel Corporation may not be used to endorse or promote products
27 // derived from this software without specific prior written permission.
28 //
29 // This software is provided by the copyright holders and contributors "as is" and
30 // any express or implied warranties, including, but not limited to, the implied
31 // warranties of merchantability and fitness for a particular purpose are disclaimed.
32 // In no event shall the Intel Corporation or contributors be liable for any direct,
33 // indirect, incidental, special, exemplary, or consequential damages
34 // (including, but not limited to, procurement of substitute goods or services;
35 // loss of use, data, or profits; or business interruption) however caused
36 // and on any theory of liability, whether in contract, strict liability,
37 // or tort (including negligence or otherwise) arising in any way out of
38 // the use of this software, even if advised of the possibility of such damage.
39 //
40 //M*/
41
42 #include "_cvaux.h"
43
44 #if _MSC_VER >= 1200
45 #pragma warning(disable:4786) // Disable MSVC warnings in the standard library.
46 #pragma warning(disable:4100)
47 #pragma warning(disable:4512)
48 #endif
49 #include <stdio.h>
50 #include <map>
51 #include <algorithm>
52 #if _MSC_VER >= 1200
53 #pragma warning(default:4100)
54 #pragma warning(default:4512)
55 #endif
56
57 #define ARRAY_SIZEOF(a) (sizeof(a)/sizeof((a)[0]))
58
59 static void FillObjectPoints(CvPoint3D32f *obj_points, CvSize etalon_size, float square_size);
60 static void DrawEtalon(IplImage *img, CvPoint2D32f *corners,
61 int corner_count, CvSize etalon_size, int draw_ordered);
62 static void MultMatrix(float rm[4][4], const float m1[4][4], const float m2[4][4]);
63 static void MultVectorMatrix(float rv[4], const float v[4], const float m[4][4]);
64 static CvPoint3D32f ImageCStoWorldCS(const Cv3dTrackerCameraInfo &camera_info, CvPoint2D32f p);
65 static bool intersection(CvPoint3D32f o1, CvPoint3D32f p1,
66 CvPoint3D32f o2, CvPoint3D32f p2,
67 CvPoint3D32f &r1, CvPoint3D32f &r2);
68
69 /////////////////////////////////
70 // cv3dTrackerCalibrateCameras //
71 /////////////////////////////////
cv3dTrackerCalibrateCameras(int num_cameras,const Cv3dTrackerCameraIntrinsics camera_intrinsics[],CvSize etalon_size,float square_size,IplImage * samples[],Cv3dTrackerCameraInfo camera_info[])72 CV_IMPL CvBool cv3dTrackerCalibrateCameras(int num_cameras,
73 const Cv3dTrackerCameraIntrinsics camera_intrinsics[], // size is num_cameras
74 CvSize etalon_size,
75 float square_size,
76 IplImage *samples[], // size is num_cameras
77 Cv3dTrackerCameraInfo camera_info[]) // size is num_cameras
78 {
79 CV_FUNCNAME("cv3dTrackerCalibrateCameras");
80 const int num_points = etalon_size.width * etalon_size.height;
81 int cameras_done = 0; // the number of cameras whose positions have been determined
82 CvPoint3D32f *object_points = NULL; // real-world coordinates of checkerboard points
83 CvPoint2D32f *points = NULL; // 2d coordinates of checkerboard points as seen by a camera
84 IplImage *gray_img = NULL; // temporary image for color conversion
85 IplImage *tmp_img = NULL; // temporary image used by FindChessboardCornerGuesses
86 int c, i, j;
87
88 if (etalon_size.width < 3 || etalon_size.height < 3)
89 CV_ERROR(CV_StsBadArg, "Chess board size is invalid");
90
91 for (c = 0; c < num_cameras; c++)
92 {
93 // CV_CHECK_IMAGE is not available in the cvaux library
94 // so perform the checks inline.
95
96 //CV_CALL(CV_CHECK_IMAGE(samples[c]));
97
98 if( samples[c] == NULL )
99 CV_ERROR( CV_HeaderIsNull, "Null image" );
100
101 if( samples[c]->dataOrder != IPL_DATA_ORDER_PIXEL && samples[c]->nChannels > 1 )
102 CV_ERROR( CV_BadOrder, "Unsupported image format" );
103
104 if( samples[c]->maskROI != 0 || samples[c]->tileInfo != 0 )
105 CV_ERROR( CV_StsBadArg, "Unsupported image format" );
106
107 if( samples[c]->imageData == 0 )
108 CV_ERROR( CV_BadDataPtr, "Null image data" );
109
110 if( samples[c]->roi &&
111 ((samples[c]->roi->xOffset | samples[c]->roi->yOffset
112 | samples[c]->roi->width | samples[c]->roi->height) < 0 ||
113 samples[c]->roi->xOffset + samples[c]->roi->width > samples[c]->width ||
114 samples[c]->roi->yOffset + samples[c]->roi->height > samples[c]->height ||
115 (unsigned) (samples[c]->roi->coi) > (unsigned) (samples[c]->nChannels)))
116 CV_ERROR( CV_BadROISize, "Invalid ROI" );
117
118 // End of CV_CHECK_IMAGE inline expansion
119
120 if (samples[c]->depth != IPL_DEPTH_8U)
121 CV_ERROR(CV_BadDepth, "Channel depth of source image must be 8");
122
123 if (samples[c]->nChannels != 3 && samples[c]->nChannels != 1)
124 CV_ERROR(CV_BadNumChannels, "Source image must have 1 or 3 channels");
125 }
126
127 CV_CALL(object_points = (CvPoint3D32f *)cvAlloc(num_points * sizeof(CvPoint3D32f)));
128 CV_CALL(points = (CvPoint2D32f *)cvAlloc(num_points * sizeof(CvPoint2D32f)));
129
130 // fill in the real-world coordinates of the checkerboard points
131 FillObjectPoints(object_points, etalon_size, square_size);
132
133 for (c = 0; c < num_cameras; c++)
134 {
135 CvSize image_size = cvSize(samples[c]->width, samples[c]->height);
136 IplImage *img;
137
138 // The input samples are not required to all have the same size or color
139 // format. If they have different sizes, the temporary images are
140 // reallocated as necessary.
141 if (samples[c]->nChannels == 3)
142 {
143 // convert to gray
144 if (gray_img == NULL || gray_img->width != samples[c]->width ||
145 gray_img->height != samples[c]->height )
146 {
147 if (gray_img != NULL)
148 cvReleaseImage(&gray_img);
149 CV_CALL(gray_img = cvCreateImage(image_size, IPL_DEPTH_8U, 1));
150 }
151
152 CV_CALL(cvCvtColor(samples[c], gray_img, CV_BGR2GRAY));
153
154 img = gray_img;
155 }
156 else
157 {
158 // no color conversion required
159 img = samples[c];
160 }
161
162 if (tmp_img == NULL || tmp_img->width != samples[c]->width ||
163 tmp_img->height != samples[c]->height )
164 {
165 if (tmp_img != NULL)
166 cvReleaseImage(&tmp_img);
167 CV_CALL(tmp_img = cvCreateImage(image_size, IPL_DEPTH_8U, 1));
168 }
169
170 int count = num_points;
171 bool found = cvFindChessBoardCornerGuesses(img, tmp_img, 0,
172 etalon_size, points, &count) != 0;
173 if (count == 0)
174 continue;
175
176 // If found is true, it means all the points were found (count = num_points).
177 // If found is false but count is non-zero, it means that not all points were found.
178
179 cvFindCornerSubPix(img, points, count, cvSize(5,5), cvSize(-1,-1),
180 cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10, 0.01f));
181
182 // If the image origin is BL (bottom-left), fix the y coordinates
183 // so they are relative to the true top of the image.
184 if (samples[c]->origin == IPL_ORIGIN_BL)
185 {
186 for (i = 0; i < count; i++)
187 points[i].y = samples[c]->height - 1 - points[i].y;
188 }
189
190 if (found)
191 {
192 // Make sure x coordinates are increasing and y coordinates are decreasing.
193 // (The y coordinate of point (0,0) should be the greatest, because the point
194 // on the checkerboard that is the origin is nearest the bottom of the image.)
195 // This is done after adjusting the y coordinates according to the image origin.
196 if (points[0].x > points[1].x)
197 {
198 // reverse points in each row
199 for (j = 0; j < etalon_size.height; j++)
200 {
201 CvPoint2D32f *row = &points[j*etalon_size.width];
202 for (i = 0; i < etalon_size.width/2; i++)
203 std::swap(row[i], row[etalon_size.width-i-1]);
204 }
205 }
206
207 if (points[0].y < points[etalon_size.width].y)
208 {
209 // reverse points in each column
210 for (i = 0; i < etalon_size.width; i++)
211 {
212 for (j = 0; j < etalon_size.height/2; j++)
213 std::swap(points[i+j*etalon_size.width],
214 points[i+(etalon_size.height-j-1)*etalon_size.width]);
215 }
216 }
217 }
218
219 DrawEtalon(samples[c], points, count, etalon_size, found);
220
221 if (!found)
222 continue;
223
224 float rotVect[3];
225 float rotMatr[9];
226 float transVect[3];
227
228 cvFindExtrinsicCameraParams(count,
229 image_size,
230 points,
231 object_points,
232 const_cast<float *>(camera_intrinsics[c].focal_length),
233 camera_intrinsics[c].principal_point,
234 const_cast<float *>(camera_intrinsics[c].distortion),
235 rotVect,
236 transVect);
237
238 // Check result against an arbitrary limit to eliminate impossible values.
239 // (If the chess board were truly that far away, the camera wouldn't be able to
240 // see the squares.)
241 if (transVect[0] > 1000*square_size
242 || transVect[1] > 1000*square_size
243 || transVect[2] > 1000*square_size)
244 {
245 // ignore impossible results
246 continue;
247 }
248
249 CvMat rotMatrDescr = cvMat(3, 3, CV_32FC1, rotMatr);
250 CvMat rotVectDescr = cvMat(3, 1, CV_32FC1, rotVect);
251
252 /* Calc rotation matrix by Rodrigues Transform */
253 cvRodrigues2( &rotVectDescr, &rotMatrDescr );
254
255 //combine the two transformations into one matrix
256 //order is important! rotations are not commutative
257 float tmat[4][4] = { { 1.f, 0.f, 0.f, 0.f },
258 { 0.f, 1.f, 0.f, 0.f },
259 { 0.f, 0.f, 1.f, 0.f },
260 { transVect[0], transVect[1], transVect[2], 1.f } };
261
262 float rmat[4][4] = { { rotMatr[0], rotMatr[1], rotMatr[2], 0.f },
263 { rotMatr[3], rotMatr[4], rotMatr[5], 0.f },
264 { rotMatr[6], rotMatr[7], rotMatr[8], 0.f },
265 { 0.f, 0.f, 0.f, 1.f } };
266
267
268 MultMatrix(camera_info[c].mat, tmat, rmat);
269
270 // change the transformation of the cameras to put them in the world coordinate
271 // system we want to work with.
272
273 // Start with an identity matrix; then fill in the values to accomplish
274 // the desired transformation.
275 float smat[4][4] = { { 1.f, 0.f, 0.f, 0.f },
276 { 0.f, 1.f, 0.f, 0.f },
277 { 0.f, 0.f, 1.f, 0.f },
278 { 0.f, 0.f, 0.f, 1.f } };
279
280 // First, reflect through the origin by inverting all three axes.
281 smat[0][0] = -1.f;
282 smat[1][1] = -1.f;
283 smat[2][2] = -1.f;
284 MultMatrix(tmat, camera_info[c].mat, smat);
285
286 // Scale x and y coordinates by the focal length (allowing for non-square pixels
287 // and/or non-symmetrical lenses).
288 smat[0][0] = 1.0f / camera_intrinsics[c].focal_length[0];
289 smat[1][1] = 1.0f / camera_intrinsics[c].focal_length[1];
290 smat[2][2] = 1.0f;
291 MultMatrix(camera_info[c].mat, smat, tmat);
292
293 camera_info[c].principal_point = camera_intrinsics[c].principal_point;
294 camera_info[c].valid = true;
295
296 cameras_done++;
297 }
298
299 exit:
300 cvReleaseImage(&gray_img);
301 cvReleaseImage(&tmp_img);
302 cvFree(&object_points);
303 cvFree(&points);
304
305 return cameras_done == num_cameras;
306 }
307
308 // fill in the real-world coordinates of the checkerboard points
FillObjectPoints(CvPoint3D32f * obj_points,CvSize etalon_size,float square_size)309 static void FillObjectPoints(CvPoint3D32f *obj_points, CvSize etalon_size, float square_size)
310 {
311 int x, y, i;
312
313 for (y = 0, i = 0; y < etalon_size.height; y++)
314 {
315 for (x = 0; x < etalon_size.width; x++, i++)
316 {
317 obj_points[i].x = square_size * x;
318 obj_points[i].y = square_size * y;
319 obj_points[i].z = 0;
320 }
321 }
322 }
323
324
325 // Mark the points found on the input image
326 // The marks are drawn multi-colored if all the points were found.
DrawEtalon(IplImage * img,CvPoint2D32f * corners,int corner_count,CvSize etalon_size,int draw_ordered)327 static void DrawEtalon(IplImage *img, CvPoint2D32f *corners,
328 int corner_count, CvSize etalon_size, int draw_ordered)
329 {
330 const int r = 4;
331 int i;
332 int x, y;
333 CvPoint prev_pt = { 0, 0 };
334 static const CvScalar rgb_colors[] = {
335 {{0,0,255}},
336 {{0,128,255}},
337 {{0,200,200}},
338 {{0,255,0}},
339 {{200,200,0}},
340 {{255,0,0}},
341 {{255,0,255}} };
342 static const CvScalar gray_colors[] = {
343 {{80}}, {{120}}, {{160}}, {{200}}, {{100}}, {{140}}, {{180}}
344 };
345 const CvScalar* colors = img->nChannels == 3 ? rgb_colors : gray_colors;
346
347 CvScalar color = colors[0];
348 for (y = 0, i = 0; y < etalon_size.height; y++)
349 {
350 if (draw_ordered)
351 color = colors[y % ARRAY_SIZEOF(rgb_colors)];
352
353 for (x = 0; x < etalon_size.width && i < corner_count; x++, i++)
354 {
355 CvPoint pt;
356 pt.x = cvRound(corners[i].x);
357 pt.y = cvRound(corners[i].y);
358 if (img->origin == IPL_ORIGIN_BL)
359 pt.y = img->height - 1 - pt.y;
360
361 if (draw_ordered)
362 {
363 if (i != 0)
364 cvLine(img, prev_pt, pt, color, 1, CV_AA);
365 prev_pt = pt;
366 }
367
368 cvLine( img, cvPoint(pt.x - r, pt.y - r),
369 cvPoint(pt.x + r, pt.y + r), color, 1, CV_AA );
370 cvLine( img, cvPoint(pt.x - r, pt.y + r),
371 cvPoint(pt.x + r, pt.y - r), color, 1, CV_AA );
372 cvCircle( img, pt, r+1, color, 1, CV_AA );
373 }
374 }
375 }
376
377 // Find the midpoint of the line segment between two points.
midpoint(const CvPoint3D32f & p1,const CvPoint3D32f & p2)378 static CvPoint3D32f midpoint(const CvPoint3D32f &p1, const CvPoint3D32f &p2)
379 {
380 return cvPoint3D32f((p1.x+p2.x)/2, (p1.y+p2.y)/2, (p1.z+p2.z)/2);
381 }
382
operator +=(CvPoint3D32f & p1,const CvPoint3D32f & p2)383 static void operator +=(CvPoint3D32f &p1, const CvPoint3D32f &p2)
384 {
385 p1.x += p2.x;
386 p1.y += p2.y;
387 p1.z += p2.z;
388 }
389
operator /(const CvPoint3D32f & p,int d)390 static CvPoint3D32f operator /(const CvPoint3D32f &p, int d)
391 {
392 return cvPoint3D32f(p.x/d, p.y/d, p.z/d);
393 }
394
find(const Cv3dTracker2dTrackedObject v[],int num_objects,int id)395 static const Cv3dTracker2dTrackedObject *find(const Cv3dTracker2dTrackedObject v[], int num_objects, int id)
396 {
397 for (int i = 0; i < num_objects; i++)
398 {
399 if (v[i].id == id)
400 return &v[i];
401 }
402 return NULL;
403 }
404
405 #define CAMERA_POS(c) (cvPoint3D32f((c).mat[3][0], (c).mat[3][1], (c).mat[3][2]))
406
407 //////////////////////////////
408 // cv3dTrackerLocateObjects //
409 //////////////////////////////
cv3dTrackerLocateObjects(int num_cameras,int num_objects,const Cv3dTrackerCameraInfo camera_info[],const Cv3dTracker2dTrackedObject tracking_info[],Cv3dTrackerTrackedObject tracked_objects[])410 CV_IMPL int cv3dTrackerLocateObjects(int num_cameras, int num_objects,
411 const Cv3dTrackerCameraInfo camera_info[], // size is num_cameras
412 const Cv3dTracker2dTrackedObject tracking_info[], // size is num_objects*num_cameras
413 Cv3dTrackerTrackedObject tracked_objects[]) // size is num_objects
414 {
415 /*CV_FUNCNAME("cv3dTrackerLocateObjects");*/
416 int found_objects = 0;
417
418 // count how many cameras could see each object
419 std::map<int, int> count;
420 for (int c = 0; c < num_cameras; c++)
421 {
422 if (!camera_info[c].valid)
423 continue;
424
425 for (int i = 0; i < num_objects; i++)
426 {
427 const Cv3dTracker2dTrackedObject *o = &tracking_info[c*num_objects+i];
428 if (o->id != -1)
429 count[o->id]++;
430 }
431 }
432
433 // process each object that was seen by at least two cameras
434 for (std::map<int, int>::iterator i = count.begin(); i != count.end(); i++)
435 {
436 if (i->second < 2)
437 continue; // ignore object seen by only one camera
438 int id = i->first;
439
440 // find an approximation of the objects location for each pair of cameras that
441 // could see this object, and average them
442 CvPoint3D32f total = cvPoint3D32f(0, 0, 0);
443 int weight = 0;
444
445 for (int c1 = 0; c1 < num_cameras-1; c1++)
446 {
447 if (!camera_info[c1].valid)
448 continue;
449
450 const Cv3dTracker2dTrackedObject *o1 = find(&tracking_info[c1*num_objects],
451 num_objects, id);
452 if (o1 == NULL)
453 continue; // this camera didn't see this object
454
455 CvPoint3D32f p1a = CAMERA_POS(camera_info[c1]);
456 CvPoint3D32f p1b = ImageCStoWorldCS(camera_info[c1], o1->p);
457
458 for (int c2 = c1 + 1; c2 < num_cameras; c2++)
459 {
460 if (!camera_info[c2].valid)
461 continue;
462
463 const Cv3dTracker2dTrackedObject *o2 = find(&tracking_info[c2*num_objects],
464 num_objects, id);
465 if (o2 == NULL)
466 continue; // this camera didn't see this object
467
468 CvPoint3D32f p2a = CAMERA_POS(camera_info[c2]);
469 CvPoint3D32f p2b = ImageCStoWorldCS(camera_info[c2], o2->p);
470
471 // these variables are initialized simply to avoid erroneous error messages
472 // from the compiler
473 CvPoint3D32f r1 = cvPoint3D32f(0, 0, 0);
474 CvPoint3D32f r2 = cvPoint3D32f(0, 0, 0);
475
476 // find the intersection of the two lines (or the points of closest
477 // approach, if they don't intersect)
478 if (!intersection(p1a, p1b, p2a, p2b, r1, r2))
479 continue;
480
481 total += midpoint(r1, r2);
482 weight++;
483 }
484 }
485
486 CvPoint3D32f center = total/weight;
487 tracked_objects[found_objects++] = cv3dTrackerTrackedObject(id, center);
488 }
489
490 return found_objects;
491 }
492
493 #define EPS 1e-9
494
495 // Compute the determinant of the 3x3 matrix represented by 3 row vectors.
det(CvPoint3D32f v1,CvPoint3D32f v2,CvPoint3D32f v3)496 static inline double det(CvPoint3D32f v1, CvPoint3D32f v2, CvPoint3D32f v3)
497 {
498 return v1.x*v2.y*v3.z + v1.z*v2.x*v3.y + v1.y*v2.z*v3.x
499 - v1.z*v2.y*v3.x - v1.x*v2.z*v3.y - v1.y*v2.x*v3.z;
500 }
501
operator +(CvPoint3D32f a,CvPoint3D32f b)502 static CvPoint3D32f operator +(CvPoint3D32f a, CvPoint3D32f b)
503 {
504 return cvPoint3D32f(a.x + b.x, a.y + b.y, a.z + b.z);
505 }
506
operator -(CvPoint3D32f a,CvPoint3D32f b)507 static CvPoint3D32f operator -(CvPoint3D32f a, CvPoint3D32f b)
508 {
509 return cvPoint3D32f(a.x - b.x, a.y - b.y, a.z - b.z);
510 }
511
operator *(CvPoint3D32f v,double f)512 static CvPoint3D32f operator *(CvPoint3D32f v, double f)
513 {
514 return cvPoint3D32f(f*v.x, f*v.y, f*v.z);
515 }
516
517
518 // Find the intersection of two lines, or if they don't intersect,
519 // the points of closest approach.
520 // The lines are defined by (o1,p1) and (o2, p2).
521 // If they intersect, r1 and r2 will be the same.
522 // Returns false on error.
intersection(CvPoint3D32f o1,CvPoint3D32f p1,CvPoint3D32f o2,CvPoint3D32f p2,CvPoint3D32f & r1,CvPoint3D32f & r2)523 static bool intersection(CvPoint3D32f o1, CvPoint3D32f p1,
524 CvPoint3D32f o2, CvPoint3D32f p2,
525 CvPoint3D32f &r1, CvPoint3D32f &r2)
526 {
527 CvPoint3D32f x = o2 - o1;
528 CvPoint3D32f d1 = p1 - o1;
529 CvPoint3D32f d2 = p2 - o2;
530
531 CvPoint3D32f cross = cvPoint3D32f(d1.y*d2.z - d1.z*d2.y,
532 d1.z*d2.x - d1.x*d2.z,
533 d1.x*d2.y - d1.y*d2.x);
534 double den = cross.x*cross.x + cross.y*cross.y + cross.z*cross.z;
535
536 if (den < EPS)
537 return false;
538
539 double t1 = det(x, d2, cross) / den;
540 double t2 = det(x, d1, cross) / den;
541
542 r1 = o1 + d1 * t1;
543 r2 = o2 + d2 * t2;
544
545 return true;
546 }
547
548 // Convert from image to camera space by transforming point p in
549 // the image plane by the camera matrix.
ImageCStoWorldCS(const Cv3dTrackerCameraInfo & camera_info,CvPoint2D32f p)550 static CvPoint3D32f ImageCStoWorldCS(const Cv3dTrackerCameraInfo &camera_info, CvPoint2D32f p)
551 {
552 float tp[4];
553 tp[0] = (float)p.x - camera_info.principal_point.x;
554 tp[1] = (float)p.y - camera_info.principal_point.y;
555 tp[2] = 1.f;
556 tp[3] = 1.f;
557
558 float tr[4];
559 //multiply tp by mat to get tr
560 MultVectorMatrix(tr, tp, camera_info.mat);
561
562 return cvPoint3D32f(tr[0]/tr[3], tr[1]/tr[3], tr[2]/tr[3]);
563 }
564
565 // Multiply affine transformation m1 by the affine transformation m2 and
566 // return the result in rm.
MultMatrix(float rm[4][4],const float m1[4][4],const float m2[4][4])567 static void MultMatrix(float rm[4][4], const float m1[4][4], const float m2[4][4])
568 {
569 for (int i=0; i<=3; i++)
570 for (int j=0; j<=3; j++)
571 {
572 rm[i][j]= 0.0;
573 for (int k=0; k <= 3; k++)
574 rm[i][j] += m1[i][k]*m2[k][j];
575 }
576 }
577
578 // Multiply the vector v by the affine transformation matrix m and return the
579 // result in rv.
MultVectorMatrix(float rv[4],const float v[4],const float m[4][4])580 void MultVectorMatrix(float rv[4], const float v[4], const float m[4][4])
581 {
582 for (int i=0; i<=3; i++)
583 {
584 rv[i] = 0.f;
585 for (int j=0;j<=3;j++)
586 rv[i] += v[j] * m[j][i];
587 }
588 }
589