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5 * Stefan Leutenegger, Simon Lynen and Margarita Chli.
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38 BRISK - Binary Robust Invariant Scalable Keypoints
39 Reference implementation of
40 [1] Stefan Leutenegger,Margarita Chli and Roland Siegwart, BRISK:
41 Binary Robust Invariant Scalable Keypoints, in Proceedings of
42 the IEEE International Conference on Computer Vision (ICCV2011).
45 #include <opencv2/features2d.hpp>
46 #include <opencv2/core.hpp>
47 #include <opencv2/imgproc.hpp>
51 #include "fast_score.hpp"
56 // a layer in the Brisk detector pyramid
57 class CV_EXPORTS BriskLayer
60 // constructor arguments
61 struct CV_EXPORTS CommonParams
63 static const int HALFSAMPLE = 0;
64 static const int TWOTHIRDSAMPLE = 1;
66 // construct a base layer
67 BriskLayer(const cv::Mat& img, float scale = 1.0f, float offset = 0.0f);
69 BriskLayer(const BriskLayer& layer, int mode);
71 // Fast/Agast without non-max suppression
73 getAgastPoints(int threshold, std::vector<cv::KeyPoint>& keypoints);
75 // get scores - attention, this is in layer coordinates, not scale=1 coordinates!
77 getAgastScore(int x, int y, int threshold) const;
79 getAgastScore_5_8(int x, int y, int threshold) const;
81 getAgastScore(float xf, float yf, int threshold, float scale = 1.0f) const;
107 halfsample(const cv::Mat& srcimg, cv::Mat& dstimg);
108 // two third sampling
110 twothirdsample(const cv::Mat& srcimg, cv::Mat& dstimg);
113 // access gray values (smoothed/interpolated)
115 value(const cv::Mat& mat, float xf, float yf, float scale) const;
119 cv::Mat_<uchar> scores_;
120 // coordinate transformation
124 cv::Ptr<cv::FastFeatureDetector> fast_9_16_;
129 class CV_EXPORTS BriskScaleSpace
132 // construct telling the octaves number:
133 BriskScaleSpace(int _octaves = 3);
136 // construct the image pyramids
138 constructPyramid(const cv::Mat& image);
142 getKeypoints(const int _threshold, std::vector<cv::KeyPoint>& keypoints);
145 // nonmax suppression:
147 isMax2D(const int layer, const int x_layer, const int y_layer);
148 // 1D (scale axis) refinement:
150 refine1D(const float s_05, const float s0, const float s05, float& max) const; // around octave
152 refine1D_1(const float s_05, const float s0, const float s05, float& max) const; // around intra
154 refine1D_2(const float s_05, const float s0, const float s05, float& max) const; // around octave 0 only
155 // 2D maximum refinement:
157 subpixel2D(const int s_0_0, const int s_0_1, const int s_0_2, const int s_1_0, const int s_1_1, const int s_1_2,
158 const int s_2_0, const int s_2_1, const int s_2_2, float& delta_x, float& delta_y) const;
159 // 3D maximum refinement centered around (x_layer,y_layer)
161 refine3D(const int layer, const int x_layer, const int y_layer, float& x, float& y, float& scale, bool& ismax) const;
163 // interpolated score access with recalculation when needed:
165 getScoreAbove(const int layer, const int x_layer, const int y_layer) const;
167 getScoreBelow(const int layer, const int x_layer, const int y_layer) const;
169 // return the maximum of score patches above or below
171 getScoreMaxAbove(const int layer, const int x_layer, const int y_layer, const int threshold, bool& ismax,
172 float& dx, float& dy) const;
174 getScoreMaxBelow(const int layer, const int x_layer, const int y_layer, const int threshold, bool& ismax,
175 float& dx, float& dy) const;
177 // the image pyramids:
179 std::vector<BriskLayer> pyramid_;
181 // some constant parameters:
182 static const float safetyFactor_;
183 static const float basicSize_;
186 const float BRISK::basicSize_ = 12.0f;
187 const unsigned int BRISK::scales_ = 64;
188 const float BRISK::scalerange_ = 30.f; // 40->4 Octaves - else, this needs to be adjusted...
189 const unsigned int BRISK::n_rot_ = 1024; // discretization of the rotation look-up
191 const float BriskScaleSpace::safetyFactor_ = 1.0f;
192 const float BriskScaleSpace::basicSize_ = 12.0f;
195 BRISK::BRISK(int thresh, int octaves_in, float patternScale)
198 octaves = octaves_in;
200 std::vector<float> rList;
201 std::vector<int> nList;
203 // this is the standard pattern found to be suitable also
206 const double f = 0.85 * patternScale;
208 rList[0] = (float)(f * 0.);
209 rList[1] = (float)(f * 2.9);
210 rList[2] = (float)(f * 4.9);
211 rList[3] = (float)(f * 7.4);
212 rList[4] = (float)(f * 10.8);
220 generateKernel(rList, nList, (float)(5.85 * patternScale), (float)(8.2 * patternScale));
223 BRISK::BRISK(std::vector<float> &radiusList, std::vector<int> &numberList, float dMax, float dMin,
224 std::vector<int> indexChange)
226 generateKernel(radiusList, numberList, dMax, dMin, indexChange);
230 BRISK::generateKernel(std::vector<float> &radiusList, std::vector<int> &numberList, float dMax,
231 float dMin, std::vector<int> indexChange)
237 // get the total number of points
238 const int rings = (int)radiusList.size();
239 CV_Assert(radiusList.size() != 0 && radiusList.size() == numberList.size());
240 points_ = 0; // remember the total number of points
241 for (int ring = 0; ring < rings; ring++)
243 points_ += numberList[ring];
245 // set up the patterns
246 patternPoints_ = new BriskPatternPoint[points_ * scales_ * n_rot_];
247 BriskPatternPoint* patternIterator = patternPoints_;
249 // define the scale discretization:
250 static const float lb_scale = (float)(std::log(scalerange_) / std::log(2.0));
251 static const float lb_scale_step = lb_scale / (scales_);
253 scaleList_ = new float[scales_];
254 sizeList_ = new unsigned int[scales_];
256 const float sigma_scale = 1.3f;
258 for (unsigned int scale = 0; scale < scales_; ++scale)
260 scaleList_[scale] = (float)std::pow((double) 2.0, (double) (scale * lb_scale_step));
261 sizeList_[scale] = 0;
263 // generate the pattern points look-up
265 for (size_t rot = 0; rot < n_rot_; ++rot)
267 theta = double(rot) * 2 * CV_PI / double(n_rot_); // this is the rotation of the feature
268 for (int ring = 0; ring < rings; ++ring)
270 for (int num = 0; num < numberList[ring]; ++num)
272 // the actual coordinates on the circle
273 alpha = (double(num)) * 2 * CV_PI / double(numberList[ring]);
274 patternIterator->x = (float)(scaleList_[scale] * radiusList[ring] * cos(alpha + theta)); // feature rotation plus angle of the point
275 patternIterator->y = (float)(scaleList_[scale] * radiusList[ring] * sin(alpha + theta));
276 // and the gaussian kernel sigma
279 patternIterator->sigma = sigma_scale * scaleList_[scale] * 0.5f;
283 patternIterator->sigma = (float)(sigma_scale * scaleList_[scale] * (double(radiusList[ring]))
284 * sin(CV_PI / numberList[ring]));
286 // adapt the sizeList if necessary
287 const unsigned int size = cvCeil(((scaleList_[scale] * radiusList[ring]) + patternIterator->sigma)) + 1;
288 if (sizeList_[scale] < size)
290 sizeList_[scale] = size;
293 // increment the iterator
300 // now also generate pairings
301 shortPairs_ = new BriskShortPair[points_ * (points_ - 1) / 2];
302 longPairs_ = new BriskLongPair[points_ * (points_ - 1) / 2];
306 // fill indexChange with 0..n if empty
307 unsigned int indSize = (unsigned int)indexChange.size();
310 indexChange.resize(points_ * (points_ - 1) / 2);
311 indSize = (unsigned int)indexChange.size();
313 for (unsigned int i = 0; i < indSize; i++)
316 const float dMin_sq = dMin_ * dMin_;
317 const float dMax_sq = dMax_ * dMax_;
318 for (unsigned int i = 1; i < points_; i++)
320 for (unsigned int j = 0; j < i; j++)
321 { //(find all the pairs)
322 // point pair distance:
323 const float dx = patternPoints_[j].x - patternPoints_[i].x;
324 const float dy = patternPoints_[j].y - patternPoints_[i].y;
325 const float norm_sq = (dx * dx + dy * dy);
326 if (norm_sq > dMin_sq)
328 // save to long pairs
329 BriskLongPair& longPair = longPairs_[noLongPairs_];
330 longPair.weighted_dx = int((dx / (norm_sq)) * 2048.0 + 0.5);
331 longPair.weighted_dy = int((dy / (norm_sq)) * 2048.0 + 0.5);
336 else if (norm_sq < dMax_sq)
338 // save to short pairs
339 CV_Assert(noShortPairs_ < indSize);
340 // make sure the user passes something sensible
341 BriskShortPair& shortPair = shortPairs_[indexChange[noShortPairs_]];
350 strings_ = (int) ceil((float(noShortPairs_)) / 128.0) * 4 * 4;
353 // simple alternative:
355 BRISK::smoothedIntensity(const cv::Mat& image, const cv::Mat& integral, const float key_x,
356 const float key_y, const unsigned int scale, const unsigned int rot,
357 const unsigned int point) const
360 // get the float position
361 const BriskPatternPoint& briskPoint = patternPoints_[scale * n_rot_ * points_ + rot * points_ + point];
362 const float xf = briskPoint.x + key_x;
363 const float yf = briskPoint.y + key_y;
364 const int x = int(xf);
365 const int y = int(yf);
366 const int& imagecols = image.cols;
369 const float sigma_half = briskPoint.sigma;
370 const float area = 4.0f * sigma_half * sigma_half;
374 if (sigma_half < 0.5)
376 //interpolation multipliers:
377 const int r_x = (int)((xf - x) * 1024);
378 const int r_y = (int)((yf - y) * 1024);
379 const int r_x_1 = (1024 - r_x);
380 const int r_y_1 = (1024 - r_y);
381 const uchar* ptr = &image.at<uchar>(y, x);
382 size_t step = image.step;
384 ret_val = r_x_1 * r_y_1 * ptr[0] + r_x * r_y_1 * ptr[1] +
385 r_x * r_y * ptr[step] + r_x_1 * r_y * ptr[step+1];
386 return (ret_val + 512) / 1024;
389 // this is the standard case (simple, not speed optimized yet):
392 const int scaling = (int)(4194304.0 / area);
393 const int scaling2 = int(float(scaling) * area / 1024.0);
395 // the integral image is larger:
396 const int integralcols = imagecols + 1;
399 const float x_1 = xf - sigma_half;
400 const float x1 = xf + sigma_half;
401 const float y_1 = yf - sigma_half;
402 const float y1 = yf + sigma_half;
404 const int x_left = int(x_1 + 0.5);
405 const int y_top = int(y_1 + 0.5);
406 const int x_right = int(x1 + 0.5);
407 const int y_bottom = int(y1 + 0.5);
409 // overlap area - multiplication factors:
410 const float r_x_1 = float(x_left) - x_1 + 0.5f;
411 const float r_y_1 = float(y_top) - y_1 + 0.5f;
412 const float r_x1 = x1 - float(x_right) + 0.5f;
413 const float r_y1 = y1 - float(y_bottom) + 0.5f;
414 const int dx = x_right - x_left - 1;
415 const int dy = y_bottom - y_top - 1;
416 const int A = (int)((r_x_1 * r_y_1) * scaling);
417 const int B = (int)((r_x1 * r_y_1) * scaling);
418 const int C = (int)((r_x1 * r_y1) * scaling);
419 const int D = (int)((r_x_1 * r_y1) * scaling);
420 const int r_x_1_i = (int)(r_x_1 * scaling);
421 const int r_y_1_i = (int)(r_y_1 * scaling);
422 const int r_x1_i = (int)(r_x1 * scaling);
423 const int r_y1_i = (int)(r_y1 * scaling);
427 // now the calculation:
428 uchar* ptr = image.data + x_left + imagecols * y_top;
429 // first the corners:
430 ret_val = A * int(*ptr);
432 ret_val += B * int(*ptr);
433 ptr += dy * imagecols + 1;
434 ret_val += C * int(*ptr);
436 ret_val += D * int(*ptr);
439 int* ptr_integral = (int*) integral.data + x_left + integralcols * y_top + 1;
440 // find a simple path through the different surface corners
441 const int tmp1 = (*ptr_integral);
443 const int tmp2 = (*ptr_integral);
444 ptr_integral += integralcols;
445 const int tmp3 = (*ptr_integral);
447 const int tmp4 = (*ptr_integral);
448 ptr_integral += dy * integralcols;
449 const int tmp5 = (*ptr_integral);
451 const int tmp6 = (*ptr_integral);
452 ptr_integral += integralcols;
453 const int tmp7 = (*ptr_integral);
455 const int tmp8 = (*ptr_integral);
456 ptr_integral -= integralcols;
457 const int tmp9 = (*ptr_integral);
459 const int tmp10 = (*ptr_integral);
460 ptr_integral -= dy * integralcols;
461 const int tmp11 = (*ptr_integral);
463 const int tmp12 = (*ptr_integral);
465 // assign the weighted surface integrals:
466 const int upper = (tmp3 - tmp2 + tmp1 - tmp12) * r_y_1_i;
467 const int middle = (tmp6 - tmp3 + tmp12 - tmp9) * scaling;
468 const int left = (tmp9 - tmp12 + tmp11 - tmp10) * r_x_1_i;
469 const int right = (tmp5 - tmp4 + tmp3 - tmp6) * r_x1_i;
470 const int bottom = (tmp7 - tmp6 + tmp9 - tmp8) * r_y1_i;
472 return (ret_val + upper + middle + left + right + bottom + scaling2 / 2) / scaling2;
475 // now the calculation:
476 uchar* ptr = image.data + x_left + imagecols * y_top;
478 ret_val = A * int(*ptr);
480 const uchar* end1 = ptr + dx;
481 for (; ptr < end1; ptr++)
483 ret_val += r_y_1_i * int(*ptr);
485 ret_val += B * int(*ptr);
487 ptr += imagecols - dx - 1;
488 uchar* end_j = ptr + dy * imagecols;
489 for (; ptr < end_j; ptr += imagecols - dx - 1)
491 ret_val += r_x_1_i * int(*ptr);
493 const uchar* end2 = ptr + dx;
494 for (; ptr < end2; ptr++)
496 ret_val += int(*ptr) * scaling;
498 ret_val += r_x1_i * int(*ptr);
501 ret_val += D * int(*ptr);
503 const uchar* end3 = ptr + dx;
504 for (; ptr < end3; ptr++)
506 ret_val += r_y1_i * int(*ptr);
508 ret_val += C * int(*ptr);
510 return (ret_val + scaling2 / 2) / scaling2;
514 RoiPredicate(const float minX, const float minY, const float maxX, const float maxY, const KeyPoint& keyPt)
516 const Point2f& pt = keyPt.pt;
517 return (pt.x < minX) || (pt.x >= maxX) || (pt.y < minY) || (pt.y >= maxY);
520 // computes the descriptor
522 BRISK::operator()( InputArray _image, InputArray _mask, std::vector<KeyPoint>& keypoints,
523 OutputArray _descriptors, bool useProvidedKeypoints) const
525 bool doOrientation=true;
526 if (useProvidedKeypoints)
527 doOrientation = false;
529 // If the user specified cv::noArray(), this will yield false. Otherwise it will return true.
530 bool doDescriptors = _descriptors.needed();
532 computeDescriptorsAndOrOrientation(_image, _mask, keypoints, _descriptors, doDescriptors, doOrientation,
533 useProvidedKeypoints);
537 BRISK::computeDescriptorsAndOrOrientation(InputArray _image, InputArray _mask, std::vector<KeyPoint>& keypoints,
538 OutputArray _descriptors, bool doDescriptors, bool doOrientation,
539 bool useProvidedKeypoints) const
541 Mat image = _image.getMat(), mask = _mask.getMat();
542 if( image.type() != CV_8UC1 )
543 cvtColor(image, image, COLOR_BGR2GRAY);
545 if (!useProvidedKeypoints)
547 doOrientation = true;
548 computeKeypointsNoOrientation(_image, _mask, keypoints);
551 //Remove keypoints very close to the border
552 size_t ksize = keypoints.size();
553 std::vector<int> kscales; // remember the scale per keypoint
554 kscales.resize(ksize);
555 static const float log2 = 0.693147180559945f;
556 static const float lb_scalerange = (float)(std::log(scalerange_) / (log2));
557 std::vector<cv::KeyPoint>::iterator beginning = keypoints.begin();
558 std::vector<int>::iterator beginningkscales = kscales.begin();
559 static const float basicSize06 = basicSize_ * 0.6f;
560 for (size_t k = 0; k < ksize; k++)
563 scale = std::max((int) (scales_ / lb_scalerange * (std::log(keypoints[k].size / (basicSize06)) / log2) + 0.5), 0);
565 if (scale >= scales_)
568 const int border = sizeList_[scale];
569 const int border_x = image.cols - border;
570 const int border_y = image.rows - border;
571 if (RoiPredicate((float)border, (float)border, (float)border_x, (float)border_y, keypoints[k]))
573 keypoints.erase(beginning + k);
574 kscales.erase(beginningkscales + k);
577 beginning = keypoints.begin();
578 beginningkscales = kscales.begin();
585 // first, calculate the integral image over the whole image:
586 // current integral image
587 cv::Mat _integral; // the integral image
588 cv::integral(image, _integral);
590 int* _values = new int[points_]; // for temporary use
592 // resize the descriptors:
596 _descriptors.create((int)ksize, strings_, CV_8U);
597 descriptors = _descriptors.getMat();
598 descriptors.setTo(0);
601 // now do the extraction for all keypoints:
603 // temporary variables containing gray values at sample points:
607 // the feature orientation
608 uchar* ptr = descriptors.data;
609 for (size_t k = 0; k < ksize; k++)
611 cv::KeyPoint& kp = keypoints[k];
612 const int& scale = kscales[k];
613 int* pvalues = _values;
614 const float& x = kp.pt.x;
615 const float& y = kp.pt.y;
619 // get the gray values in the unrotated pattern
620 for (unsigned int i = 0; i < points_; i++)
622 *(pvalues++) = smoothedIntensity(image, _integral, x, y, scale, 0, i);
627 // now iterate through the long pairings
628 const BriskLongPair* max = longPairs_ + noLongPairs_;
629 for (BriskLongPair* iter = longPairs_; iter < max; ++iter)
631 t1 = *(_values + iter->i);
632 t2 = *(_values + iter->j);
633 const int delta_t = (t1 - t2);
634 // update the direction:
635 const int tmp0 = delta_t * (iter->weighted_dx) / 1024;
636 const int tmp1 = delta_t * (iter->weighted_dy) / 1024;
640 kp.angle = (float)(atan2((float) direction1, (float) direction0) / CV_PI * 180.0);
651 // don't compute the gradient direction, just assign a rotation of 0°
656 theta = (int) (n_rot_ * (kp.angle / (360.0)) + 0.5);
659 if (theta >= int(n_rot_))
663 // now also extract the stuff for the actual direction:
664 // let us compute the smoothed values
667 //unsigned int mean=0;
669 // get the gray values in the rotated pattern
670 for (unsigned int i = 0; i < points_; i++)
672 *(pvalues++) = smoothedIntensity(image, _integral, x, y, scale, theta, i);
675 // now iterate through all the pairings
676 unsigned int* ptr2 = (unsigned int*) ptr;
677 const BriskShortPair* max = shortPairs_ + noShortPairs_;
678 for (BriskShortPair* iter = shortPairs_; iter < max; ++iter)
680 t1 = *(_values + iter->i);
681 t2 = *(_values + iter->j);
684 *ptr2 |= ((1) << shifter);
686 } // else already initialized with zero
687 // take care of the iterators:
704 BRISK::descriptorSize() const
710 BRISK::descriptorType() const
716 BRISK::defaultNorm() const
723 delete[] patternPoints_;
724 delete[] shortPairs_;
731 BRISK::operator()(InputArray image, InputArray mask, std::vector<KeyPoint>& keypoints) const
733 computeKeypointsNoOrientation(image, mask, keypoints);
734 computeDescriptorsAndOrOrientation(image, mask, keypoints, cv::noArray(), false, true, true);
738 BRISK::computeKeypointsNoOrientation(InputArray _image, InputArray _mask, std::vector<KeyPoint>& keypoints) const
740 Mat image = _image.getMat(), mask = _mask.getMat();
741 if( image.type() != CV_8UC1 )
742 cvtColor(_image, image, COLOR_BGR2GRAY);
744 BriskScaleSpace briskScaleSpace(octaves);
745 briskScaleSpace.constructPyramid(image);
746 briskScaleSpace.getKeypoints(threshold, keypoints);
748 // remove invalid points
749 removeInvalidPoints(mask, keypoints);
754 BRISK::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask) const
756 (*this)(image, mask, keypoints);
760 BRISK::computeImpl( const Mat& image, std::vector<KeyPoint>& keypoints, Mat& descriptors) const
762 (*this)(image, Mat(), keypoints, descriptors, true);
765 // construct telling the octaves number:
766 BriskScaleSpace::BriskScaleSpace(int _octaves)
771 layers_ = 2 * _octaves;
773 BriskScaleSpace::~BriskScaleSpace()
777 // construct the image pyramids
779 BriskScaleSpace::constructPyramid(const cv::Mat& image)
786 pyramid_.push_back(BriskLayer(image.clone()));
789 pyramid_.push_back(BriskLayer(pyramid_.back(), BriskLayer::CommonParams::TWOTHIRDSAMPLE));
791 const int octaves2 = layers_;
793 for (uchar i = 2; i < octaves2; i += 2)
795 pyramid_.push_back(BriskLayer(pyramid_[i - 2], BriskLayer::CommonParams::HALFSAMPLE));
796 pyramid_.push_back(BriskLayer(pyramid_[i - 1], BriskLayer::CommonParams::HALFSAMPLE));
801 BriskScaleSpace::getKeypoints(const int threshold_, std::vector<cv::KeyPoint>& keypoints)
803 // make sure keypoints is empty
805 keypoints.reserve(2000);
808 int safeThreshold_ = (int)(threshold_ * safetyFactor_);
809 std::vector<std::vector<cv::KeyPoint> > agastPoints;
810 agastPoints.resize(layers_);
812 // go through the octaves and intra layers and calculate fast corner scores:
813 for (int i = 0; i < layers_; i++)
815 // call OAST16_9 without nms
816 BriskLayer& l = pyramid_[i];
817 l.getAgastPoints(safeThreshold_, agastPoints[i]);
822 // just do a simple 2d subpixel refinement...
823 const size_t num = agastPoints[0].size();
824 for (size_t n = 0; n < num; n++)
826 const cv::Point2f& point = agastPoints.at(0)[n].pt;
827 // first check if it is a maximum:
828 if (!isMax2D(0, (int)point.x, (int)point.y))
831 // let's do the subpixel and float scale refinement:
832 BriskLayer& l = pyramid_[0];
833 int s_0_0 = l.getAgastScore(point.x - 1, point.y - 1, 1);
834 int s_1_0 = l.getAgastScore(point.x, point.y - 1, 1);
835 int s_2_0 = l.getAgastScore(point.x + 1, point.y - 1, 1);
836 int s_2_1 = l.getAgastScore(point.x + 1, point.y, 1);
837 int s_1_1 = l.getAgastScore(point.x, point.y, 1);
838 int s_0_1 = l.getAgastScore(point.x - 1, point.y, 1);
839 int s_0_2 = l.getAgastScore(point.x - 1, point.y + 1, 1);
840 int s_1_2 = l.getAgastScore(point.x, point.y + 1, 1);
841 int s_2_2 = l.getAgastScore(point.x + 1, point.y + 1, 1);
842 float delta_x, delta_y;
843 float max = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, delta_x, delta_y);
846 keypoints.push_back(cv::KeyPoint(float(point.x) + delta_x, float(point.y) + delta_y, basicSize_, -1, max, 0));
853 float x, y, scale, score;
854 for (int i = 0; i < layers_; i++)
856 BriskLayer& l = pyramid_[i];
857 const size_t num = agastPoints[i].size();
858 if (i == layers_ - 1)
860 for (size_t n = 0; n < num; n++)
862 const cv::Point2f& point = agastPoints.at(i)[n].pt;
863 // consider only 2D maxima...
864 if (!isMax2D(i, (int)point.x, (int)point.y))
869 getScoreMaxBelow(i, (int)point.x, (int)point.y, l.getAgastScore(point.x, point.y, safeThreshold_), ismax, dx, dy);
873 // get the patch on this layer:
874 int s_0_0 = l.getAgastScore(point.x - 1, point.y - 1, 1);
875 int s_1_0 = l.getAgastScore(point.x, point.y - 1, 1);
876 int s_2_0 = l.getAgastScore(point.x + 1, point.y - 1, 1);
877 int s_2_1 = l.getAgastScore(point.x + 1, point.y, 1);
878 int s_1_1 = l.getAgastScore(point.x, point.y, 1);
879 int s_0_1 = l.getAgastScore(point.x - 1, point.y, 1);
880 int s_0_2 = l.getAgastScore(point.x - 1, point.y + 1, 1);
881 int s_1_2 = l.getAgastScore(point.x, point.y + 1, 1);
882 int s_2_2 = l.getAgastScore(point.x + 1, point.y + 1, 1);
883 float delta_x, delta_y;
884 float max = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, delta_x, delta_y);
888 cv::KeyPoint((float(point.x) + delta_x) * l.scale() + l.offset(),
889 (float(point.y) + delta_y) * l.scale() + l.offset(), basicSize_ * l.scale(), -1, max, i));
894 // not the last layer:
895 for (size_t n = 0; n < num; n++)
897 const cv::Point2f& point = agastPoints.at(i)[n].pt;
899 // first check if it is a maximum:
900 if (!isMax2D(i, (int)point.x, (int)point.y))
903 // let's do the subpixel and float scale refinement:
905 score = refine3D(i, (int)point.x, (int)point.y, x, y, scale, ismax);
911 // finally store the detected keypoint:
912 if (score > float(threshold_))
914 keypoints.push_back(cv::KeyPoint(x, y, basicSize_ * scale, -1, score, i));
921 // interpolated score access with recalculation when needed:
923 BriskScaleSpace::getScoreAbove(const int layer, const int x_layer, const int y_layer) const
925 CV_Assert(layer < layers_-1);
926 const BriskLayer& l = pyramid_[layer + 1];
929 const int sixths_x = 4 * x_layer - 1;
930 const int x_above = sixths_x / 6;
931 const int sixths_y = 4 * y_layer - 1;
932 const int y_above = sixths_y / 6;
933 const int r_x = (sixths_x % 6);
934 const int r_x_1 = 6 - r_x;
935 const int r_y = (sixths_y % 6);
936 const int r_y_1 = 6 - r_y;
938 & ((r_x_1 * r_y_1 * l.getAgastScore(x_above, y_above, 1) + r_x * r_y_1
939 * l.getAgastScore(x_above + 1, y_above, 1)
940 + r_x_1 * r_y * l.getAgastScore(x_above, y_above + 1, 1)
941 + r_x * r_y * l.getAgastScore(x_above + 1, y_above + 1, 1) + 18)
948 const int eighths_x = 6 * x_layer - 1;
949 const int x_above = eighths_x / 8;
950 const int eighths_y = 6 * y_layer - 1;
951 const int y_above = eighths_y / 8;
952 const int r_x = (eighths_x % 8);
953 const int r_x_1 = 8 - r_x;
954 const int r_y = (eighths_y % 8);
955 const int r_y_1 = 8 - r_y;
957 & ((r_x_1 * r_y_1 * l.getAgastScore(x_above, y_above, 1) + r_x * r_y_1
958 * l.getAgastScore(x_above + 1, y_above, 1)
959 + r_x_1 * r_y * l.getAgastScore(x_above, y_above + 1, 1)
960 + r_x * r_y * l.getAgastScore(x_above + 1, y_above + 1, 1) + 32)
966 BriskScaleSpace::getScoreBelow(const int layer, const int x_layer, const int y_layer) const
969 const BriskLayer& l = pyramid_[layer - 1];
985 sixth_x = 8 * x_layer + 1;
986 xf = float(sixth_x) / 6.0f;
987 sixth_y = 8 * y_layer + 1;
988 yf = float(sixth_y) / 6.0f;
992 area = 4.0f * offs * offs;
993 scaling = (int)(4194304.0 / area);
994 scaling2 = (int)(float(scaling) * area);
998 quarter_x = 6 * x_layer + 1;
999 xf = float(quarter_x) / 4.0f;
1000 quarter_y = 6 * y_layer + 1;
1001 yf = float(quarter_y) / 4.0f;
1005 area = 4.0f * offs * offs;
1006 scaling = (int)(4194304.0 / area);
1007 scaling2 = (int)(float(scaling) * area);
1010 // calculate borders
1011 const float x_1 = xf - offs;
1012 const float x1 = xf + offs;
1013 const float y_1 = yf - offs;
1014 const float y1 = yf + offs;
1016 const int x_left = int(x_1 + 0.5);
1017 const int y_top = int(y_1 + 0.5);
1018 const int x_right = int(x1 + 0.5);
1019 const int y_bottom = int(y1 + 0.5);
1021 // overlap area - multiplication factors:
1022 const float r_x_1 = float(x_left) - x_1 + 0.5f;
1023 const float r_y_1 = float(y_top) - y_1 + 0.5f;
1024 const float r_x1 = x1 - float(x_right) + 0.5f;
1025 const float r_y1 = y1 - float(y_bottom) + 0.5f;
1026 const int dx = x_right - x_left - 1;
1027 const int dy = y_bottom - y_top - 1;
1028 const int A = (int)((r_x_1 * r_y_1) * scaling);
1029 const int B = (int)((r_x1 * r_y_1) * scaling);
1030 const int C = (int)((r_x1 * r_y1) * scaling);
1031 const int D = (int)((r_x_1 * r_y1) * scaling);
1032 const int r_x_1_i = (int)(r_x_1 * scaling);
1033 const int r_y_1_i = (int)(r_y_1 * scaling);
1034 const int r_x1_i = (int)(r_x1 * scaling);
1035 const int r_y1_i = (int)(r_y1 * scaling);
1038 int ret_val = A * int(l.getAgastScore(x_left, y_top, 1));
1039 for (int X = 1; X <= dx; X++)
1041 ret_val += r_y_1_i * int(l.getAgastScore(x_left + X, y_top, 1));
1043 ret_val += B * int(l.getAgastScore(x_left + dx + 1, y_top, 1));
1045 for (int Y = 1; Y <= dy; Y++)
1047 ret_val += r_x_1_i * int(l.getAgastScore(x_left, y_top + Y, 1));
1049 for (int X = 1; X <= dx; X++)
1051 ret_val += int(l.getAgastScore(x_left + X, y_top + Y, 1)) * scaling;
1053 ret_val += r_x1_i * int(l.getAgastScore(x_left + dx + 1, y_top + Y, 1));
1056 ret_val += D * int(l.getAgastScore(x_left, y_top + dy + 1, 1));
1057 for (int X = 1; X <= dx; X++)
1059 ret_val += r_y1_i * int(l.getAgastScore(x_left + X, y_top + dy + 1, 1));
1061 ret_val += C * int(l.getAgastScore(x_left + dx + 1, y_top + dy + 1, 1));
1063 return ((ret_val + scaling2 / 2) / scaling2);
1067 BriskScaleSpace::isMax2D(const int layer, const int x_layer, const int y_layer)
1069 const cv::Mat& scores = pyramid_[layer].scores();
1070 const int scorescols = scores.cols;
1071 uchar* data = scores.data + y_layer * scorescols + x_layer;
1073 const uchar center = (*data);
1075 const uchar s_10 = *data;
1079 const uchar s10 = *data;
1082 data -= (scorescols + 1);
1083 const uchar s0_1 = *data;
1086 data += 2 * scorescols;
1087 const uchar s01 = *data;
1091 const uchar s_11 = *data;
1095 const uchar s11 = *data;
1098 data -= 2 * scorescols;
1099 const uchar s1_1 = *data;
1103 const uchar s_1_1 = *data;
1107 // reject neighbor maxima
1108 std::vector<int> delta;
1109 // put together a list of 2d-offsets to where the maximum is also reached
1110 if (center == s_1_1)
1112 delta.push_back(-1);
1113 delta.push_back(-1);
1118 delta.push_back(-1);
1123 delta.push_back(-1);
1127 delta.push_back(-1);
1137 delta.push_back(-1);
1150 const unsigned int deltasize = (unsigned int)delta.size();
1153 // in this case, we have to analyze the situation more carefully:
1154 // the values are gaussian blurred and then we really decide
1155 data = scores.data + y_layer * scorescols + x_layer;
1156 int smoothedcenter = 4 * center + 2 * (s_10 + s10 + s0_1 + s01) + s_1_1 + s1_1 + s_11 + s11;
1157 for (unsigned int i = 0; i < deltasize; i += 2)
1159 data = scores.data + (y_layer - 1 + delta[i + 1]) * scorescols + x_layer + delta[i] - 1;
1160 int othercenter = *data;
1162 othercenter += 2 * (*data);
1164 othercenter += *data;
1166 othercenter += 2 * (*data);
1168 othercenter += 4 * (*data);
1170 othercenter += 2 * (*data);
1172 othercenter += *data;
1174 othercenter += 2 * (*data);
1176 othercenter += *data;
1177 if (othercenter > smoothedcenter)
1184 // 3D maximum refinement centered around (x_layer,y_layer)
1186 BriskScaleSpace::refine3D(const int layer, const int x_layer, const int y_layer, float& x, float& y, float& scale,
1190 const BriskLayer& thisLayer = pyramid_[layer];
1191 const int center = thisLayer.getAgastScore(x_layer, y_layer, 1);
1193 // check and get above maximum:
1194 float delta_x_above = 0, delta_y_above = 0;
1195 float max_above = getScoreMaxAbove(layer, x_layer, y_layer, center, ismax, delta_x_above, delta_y_above);
1200 float max; // to be returned
1204 // treat the patch below:
1205 float delta_x_below, delta_y_below;
1206 float max_below_float;
1210 // guess the lower intra octave...
1211 const BriskLayer& l = pyramid_[0];
1212 int s_0_0 = l.getAgastScore_5_8(x_layer - 1, y_layer - 1, 1);
1214 int s_1_0 = l.getAgastScore_5_8(x_layer, y_layer - 1, 1);
1215 max_below = std::max(s_1_0, max_below);
1216 int s_2_0 = l.getAgastScore_5_8(x_layer + 1, y_layer - 1, 1);
1217 max_below = std::max(s_2_0, max_below);
1218 int s_2_1 = l.getAgastScore_5_8(x_layer + 1, y_layer, 1);
1219 max_below = std::max(s_2_1, max_below);
1220 int s_1_1 = l.getAgastScore_5_8(x_layer, y_layer, 1);
1221 max_below = std::max(s_1_1, max_below);
1222 int s_0_1 = l.getAgastScore_5_8(x_layer - 1, y_layer, 1);
1223 max_below = std::max(s_0_1, max_below);
1224 int s_0_2 = l.getAgastScore_5_8(x_layer - 1, y_layer + 1, 1);
1225 max_below = std::max(s_0_2, max_below);
1226 int s_1_2 = l.getAgastScore_5_8(x_layer, y_layer + 1, 1);
1227 max_below = std::max(s_1_2, max_below);
1228 int s_2_2 = l.getAgastScore_5_8(x_layer + 1, y_layer + 1, 1);
1229 max_below = std::max(s_2_2, max_below);
1231 max_below_float = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, delta_x_below,
1233 max_below_float = (float)max_below;
1237 max_below_float = getScoreMaxBelow(layer, x_layer, y_layer, center, ismax, delta_x_below, delta_y_below);
1242 // get the patch on this layer:
1243 int s_0_0 = thisLayer.getAgastScore(x_layer - 1, y_layer - 1, 1);
1244 int s_1_0 = thisLayer.getAgastScore(x_layer, y_layer - 1, 1);
1245 int s_2_0 = thisLayer.getAgastScore(x_layer + 1, y_layer - 1, 1);
1246 int s_2_1 = thisLayer.getAgastScore(x_layer + 1, y_layer, 1);
1247 int s_1_1 = thisLayer.getAgastScore(x_layer, y_layer, 1);
1248 int s_0_1 = thisLayer.getAgastScore(x_layer - 1, y_layer, 1);
1249 int s_0_2 = thisLayer.getAgastScore(x_layer - 1, y_layer + 1, 1);
1250 int s_1_2 = thisLayer.getAgastScore(x_layer, y_layer + 1, 1);
1251 int s_2_2 = thisLayer.getAgastScore(x_layer + 1, y_layer + 1, 1);
1252 float delta_x_layer, delta_y_layer;
1253 float max_layer = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, delta_x_layer,
1256 // calculate the relative scale (1D maximum):
1259 scale = refine1D_2(max_below_float, std::max(float(center), max_layer), max_above, max);
1262 scale = refine1D(max_below_float, std::max(float(center), max_layer), max_above, max);
1266 // interpolate the position:
1267 const float r0 = (1.5f - scale) / .5f;
1268 const float r1 = 1.0f - r0;
1269 x = (r0 * delta_x_layer + r1 * delta_x_above + float(x_layer)) * thisLayer.scale() + thisLayer.offset();
1270 y = (r0 * delta_y_layer + r1 * delta_y_above + float(y_layer)) * thisLayer.scale() + thisLayer.offset();
1276 // interpolate the position:
1277 const float r0 = (scale - 0.5f) / 0.5f;
1278 const float r_1 = 1.0f - r0;
1279 x = r0 * delta_x_layer + r_1 * delta_x_below + float(x_layer);
1280 y = r0 * delta_y_layer + r_1 * delta_y_below + float(y_layer);
1284 // interpolate the position:
1285 const float r0 = (scale - 0.75f) / 0.25f;
1286 const float r_1 = 1.0f - r0;
1287 x = (r0 * delta_x_layer + r_1 * delta_x_below + float(x_layer)) * thisLayer.scale() + thisLayer.offset();
1288 y = (r0 * delta_y_layer + r_1 * delta_y_below + float(y_layer)) * thisLayer.scale() + thisLayer.offset();
1295 // check the patch below:
1296 float delta_x_below, delta_y_below;
1297 float max_below = getScoreMaxBelow(layer, x_layer, y_layer, center, ismax, delta_x_below, delta_y_below);
1301 // get the patch on this layer:
1302 int s_0_0 = thisLayer.getAgastScore(x_layer - 1, y_layer - 1, 1);
1303 int s_1_0 = thisLayer.getAgastScore(x_layer, y_layer - 1, 1);
1304 int s_2_0 = thisLayer.getAgastScore(x_layer + 1, y_layer - 1, 1);
1305 int s_2_1 = thisLayer.getAgastScore(x_layer + 1, y_layer, 1);
1306 int s_1_1 = thisLayer.getAgastScore(x_layer, y_layer, 1);
1307 int s_0_1 = thisLayer.getAgastScore(x_layer - 1, y_layer, 1);
1308 int s_0_2 = thisLayer.getAgastScore(x_layer - 1, y_layer + 1, 1);
1309 int s_1_2 = thisLayer.getAgastScore(x_layer, y_layer + 1, 1);
1310 int s_2_2 = thisLayer.getAgastScore(x_layer + 1, y_layer + 1, 1);
1311 float delta_x_layer, delta_y_layer;
1312 float max_layer = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, delta_x_layer,
1315 // calculate the relative scale (1D maximum):
1316 scale = refine1D_1(max_below, std::max(float(center), max_layer), max_above, max);
1319 // interpolate the position:
1320 const float r0 = 4.0f - scale * 3.0f;
1321 const float r1 = 1.0f - r0;
1322 x = (r0 * delta_x_layer + r1 * delta_x_above + float(x_layer)) * thisLayer.scale() + thisLayer.offset();
1323 y = (r0 * delta_y_layer + r1 * delta_y_above + float(y_layer)) * thisLayer.scale() + thisLayer.offset();
1327 // interpolate the position:
1328 const float r0 = scale * 3.0f - 2.0f;
1329 const float r_1 = 1.0f - r0;
1330 x = (r0 * delta_x_layer + r_1 * delta_x_below + float(x_layer)) * thisLayer.scale() + thisLayer.offset();
1331 y = (r0 * delta_y_layer + r_1 * delta_y_below + float(y_layer)) * thisLayer.scale() + thisLayer.offset();
1335 // calculate the absolute scale:
1336 scale *= thisLayer.scale();
1338 // that's it, return the refined maximum:
1342 // return the maximum of score patches above or below
1344 BriskScaleSpace::getScoreMaxAbove(const int layer, const int x_layer, const int y_layer, const int threshold,
1345 bool& ismax, float& dx, float& dy) const
1349 // relevant floating point coordinates
1356 CV_Assert(layer + 1 < layers_);
1357 const BriskLayer& layerAbove = pyramid_[layer + 1];
1362 x_1 = float(4 * (x_layer) - 1 - 2) / 6.0f;
1363 x1 = float(4 * (x_layer) - 1 + 2) / 6.0f;
1364 y_1 = float(4 * (y_layer) - 1 - 2) / 6.0f;
1365 y1 = float(4 * (y_layer) - 1 + 2) / 6.0f;
1370 x_1 = float(6 * (x_layer) - 1 - 3) / 8.0f;
1371 x1 = float(6 * (x_layer) - 1 + 3) / 8.0f;
1372 y_1 = float(6 * (y_layer) - 1 - 3) / 8.0f;
1373 y1 = float(6 * (y_layer) - 1 + 3) / 8.0f;
1376 // check the first row
1377 int max_x = (int)x_1 + 1;
1378 int max_y = (int)y_1 + 1;
1380 float maxval = (float)layerAbove.getAgastScore(x_1, y_1, 1);
1381 if (maxval > threshold)
1383 for (int x = (int)x_1 + 1; x <= int(x1); x++)
1385 tmp_max = (float)layerAbove.getAgastScore(float(x), y_1, 1);
1386 if (tmp_max > threshold)
1388 if (tmp_max > maxval)
1394 tmp_max = (float)layerAbove.getAgastScore(x1, y_1, 1);
1395 if (tmp_max > threshold)
1397 if (tmp_max > maxval)
1404 for (int y = (int)y_1 + 1; y <= int(y1); y++)
1406 tmp_max = (float)layerAbove.getAgastScore(x_1, float(y), 1);
1407 if (tmp_max > threshold)
1409 if (tmp_max > maxval)
1412 max_x = int(x_1 + 1);
1415 for (int x = (int)x_1 + 1; x <= int(x1); x++)
1417 tmp_max = (float)layerAbove.getAgastScore(x, y, 1);
1418 if (tmp_max > threshold)
1420 if (tmp_max > maxval)
1427 tmp_max = (float)layerAbove.getAgastScore(x1, float(y), 1);
1428 if (tmp_max > threshold)
1430 if (tmp_max > maxval)
1439 tmp_max = (float)layerAbove.getAgastScore(x_1, y1, 1);
1440 if (tmp_max > maxval)
1443 max_x = int(x_1 + 1);
1446 for (int x = (int)x_1 + 1; x <= int(x1); x++)
1448 tmp_max = (float)layerAbove.getAgastScore(float(x), y1, 1);
1449 if (tmp_max > maxval)
1456 tmp_max = (float)layerAbove.getAgastScore(x1, y1, 1);
1457 if (tmp_max > maxval)
1465 int s_0_0 = layerAbove.getAgastScore(max_x - 1, max_y - 1, 1);
1466 int s_1_0 = layerAbove.getAgastScore(max_x, max_y - 1, 1);
1467 int s_2_0 = layerAbove.getAgastScore(max_x + 1, max_y - 1, 1);
1468 int s_2_1 = layerAbove.getAgastScore(max_x + 1, max_y, 1);
1469 int s_1_1 = layerAbove.getAgastScore(max_x, max_y, 1);
1470 int s_0_1 = layerAbove.getAgastScore(max_x - 1, max_y, 1);
1471 int s_0_2 = layerAbove.getAgastScore(max_x - 1, max_y + 1, 1);
1472 int s_1_2 = layerAbove.getAgastScore(max_x, max_y + 1, 1);
1473 int s_2_2 = layerAbove.getAgastScore(max_x + 1, max_y + 1, 1);
1475 float refined_max = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, dx_1, dy_1);
1477 // calculate dx/dy in above coordinates
1478 float real_x = float(max_x) + dx_1;
1479 float real_y = float(max_y) + dy_1;
1480 bool returnrefined = true;
1483 dx = (real_x * 6.0f + 1.0f) / 4.0f - float(x_layer);
1484 dy = (real_y * 6.0f + 1.0f) / 4.0f - float(y_layer);
1488 dx = (real_x * 8.0f + 1.0f) / 6.0f - float(x_layer);
1489 dy = (real_y * 8.0f + 1.0f) / 6.0f - float(y_layer);
1496 returnrefined = false;
1501 returnrefined = false;
1506 returnrefined = false;
1511 returnrefined = false;
1518 return std::max(refined_max, maxval);
1524 BriskScaleSpace::getScoreMaxBelow(const int layer, const int x_layer, const int y_layer, const int threshold,
1525 bool& ismax, float& dx, float& dy) const
1529 // relevant floating point coordinates
1538 x_1 = float(8 * (x_layer) + 1 - 4) / 6.0f;
1539 x1 = float(8 * (x_layer) + 1 + 4) / 6.0f;
1540 y_1 = float(8 * (y_layer) + 1 - 4) / 6.0f;
1541 y1 = float(8 * (y_layer) + 1 + 4) / 6.0f;
1545 x_1 = float(6 * (x_layer) + 1 - 3) / 4.0f;
1546 x1 = float(6 * (x_layer) + 1 + 3) / 4.0f;
1547 y_1 = float(6 * (y_layer) + 1 - 3) / 4.0f;
1548 y1 = float(6 * (y_layer) + 1 + 3) / 4.0f;
1552 CV_Assert(layer > 0);
1553 const BriskLayer& layerBelow = pyramid_[layer - 1];
1555 // check the first row
1556 int max_x = (int)x_1 + 1;
1557 int max_y = (int)y_1 + 1;
1559 float max = (float)layerBelow.getAgastScore(x_1, y_1, 1);
1560 if (max > threshold)
1562 for (int x = (int)x_1 + 1; x <= int(x1); x++)
1564 tmp_max = (float)layerBelow.getAgastScore(float(x), y_1, 1);
1565 if (tmp_max > threshold)
1573 tmp_max = (float)layerBelow.getAgastScore(x1, y_1, 1);
1574 if (tmp_max > threshold)
1583 for (int y = (int)y_1 + 1; y <= int(y1); y++)
1585 tmp_max = (float)layerBelow.getAgastScore(x_1, float(y), 1);
1586 if (tmp_max > threshold)
1591 max_x = int(x_1 + 1);
1594 for (int x = (int)x_1 + 1; x <= int(x1); x++)
1596 tmp_max = (float)layerBelow.getAgastScore(x, y, 1);
1597 if (tmp_max > threshold)
1602 * (layerBelow.getAgastScore(x - 1, y, 1) + layerBelow.getAgastScore(x + 1, y, 1)
1603 + layerBelow.getAgastScore(x, y + 1, 1) + layerBelow.getAgastScore(x, y - 1, 1))
1604 + (layerBelow.getAgastScore(x + 1, y + 1, 1) + layerBelow.getAgastScore(x - 1, y + 1, 1)
1605 + layerBelow.getAgastScore(x + 1, y - 1, 1) + layerBelow.getAgastScore(x - 1, y - 1, 1));
1607 * (layerBelow.getAgastScore(max_x - 1, max_y, 1) + layerBelow.getAgastScore(max_x + 1, max_y, 1)
1608 + layerBelow.getAgastScore(max_x, max_y + 1, 1) + layerBelow.getAgastScore(max_x, max_y - 1, 1))
1609 + (layerBelow.getAgastScore(max_x + 1, max_y + 1, 1) + layerBelow.getAgastScore(max_x - 1,
1611 + layerBelow.getAgastScore(max_x + 1, max_y - 1, 1)
1612 + layerBelow.getAgastScore(max_x - 1, max_y - 1, 1));
1626 tmp_max = (float)layerBelow.getAgastScore(x1, float(y), 1);
1627 if (tmp_max > threshold)
1638 tmp_max = (float)layerBelow.getAgastScore(x_1, y1, 1);
1642 max_x = int(x_1 + 1);
1645 for (int x = (int)x_1 + 1; x <= int(x1); x++)
1647 tmp_max = (float)layerBelow.getAgastScore(float(x), y1, 1);
1655 tmp_max = (float)layerBelow.getAgastScore(x1, y1, 1);
1664 int s_0_0 = layerBelow.getAgastScore(max_x - 1, max_y - 1, 1);
1665 int s_1_0 = layerBelow.getAgastScore(max_x, max_y - 1, 1);
1666 int s_2_0 = layerBelow.getAgastScore(max_x + 1, max_y - 1, 1);
1667 int s_2_1 = layerBelow.getAgastScore(max_x + 1, max_y, 1);
1668 int s_1_1 = layerBelow.getAgastScore(max_x, max_y, 1);
1669 int s_0_1 = layerBelow.getAgastScore(max_x - 1, max_y, 1);
1670 int s_0_2 = layerBelow.getAgastScore(max_x - 1, max_y + 1, 1);
1671 int s_1_2 = layerBelow.getAgastScore(max_x, max_y + 1, 1);
1672 int s_2_2 = layerBelow.getAgastScore(max_x + 1, max_y + 1, 1);
1674 float refined_max = subpixel2D(s_0_0, s_0_1, s_0_2, s_1_0, s_1_1, s_1_2, s_2_0, s_2_1, s_2_2, dx_1, dy_1);
1676 // calculate dx/dy in above coordinates
1677 float real_x = float(max_x) + dx_1;
1678 float real_y = float(max_y) + dy_1;
1679 bool returnrefined = true;
1682 dx = (float)((real_x * 6.0 + 1.0) / 8.0) - float(x_layer);
1683 dy = (float)((real_y * 6.0 + 1.0) / 8.0) - float(y_layer);
1687 dx = (float)((real_x * 4.0 - 1.0) / 6.0) - float(x_layer);
1688 dy = (float)((real_y * 4.0 - 1.0) / 6.0) - float(y_layer);
1695 returnrefined = false;
1700 returnrefined = false;
1705 returnrefined = false;
1710 returnrefined = false;
1717 return std::max(refined_max, max);
1723 BriskScaleSpace::refine1D(const float s_05, const float s0, const float s05, float& max) const
1725 int i_05 = int(1024.0 * s_05 + 0.5);
1726 int i0 = int(1024.0 * s0 + 0.5);
1727 int i05 = int(1024.0 * s05 + 0.5);
1729 // 16.0000 -24.0000 8.0000
1730 // -40.0000 54.0000 -14.0000
1731 // 24.0000 -27.0000 6.0000
1733 int three_a = 16 * i_05 - 24 * i0 + 8 * i05;
1734 // second derivative must be negative:
1737 if (s0 >= s_05 && s0 >= s05)
1742 if (s_05 >= s0 && s_05 >= s05)
1747 if (s05 >= s0 && s05 >= s_05)
1754 int three_b = -40 * i_05 + 54 * i0 - 14 * i05;
1755 // calculate max location:
1756 float ret_val = -float(three_b) / float(2 * three_a);
1757 // saturate and return
1760 else if (ret_val > 1.5)
1761 ret_val = 1.5; // allow to be slightly off bounds ...?
1762 int three_c = +24 * i_05 - 27 * i0 + 6 * i05;
1763 max = float(three_c) + float(three_a) * ret_val * ret_val + float(three_b) * ret_val;
1769 BriskScaleSpace::refine1D_1(const float s_05, const float s0, const float s05, float& max) const
1771 int i_05 = int(1024.0 * s_05 + 0.5);
1772 int i0 = int(1024.0 * s0 + 0.5);
1773 int i05 = int(1024.0 * s05 + 0.5);
1775 // 4.5000 -9.0000 4.5000
1776 //-10.5000 18.0000 -7.5000
1777 // 6.0000 -8.0000 3.0000
1779 int two_a = 9 * i_05 - 18 * i0 + 9 * i05;
1780 // second derivative must be negative:
1783 if (s0 >= s_05 && s0 >= s05)
1788 if (s_05 >= s0 && s_05 >= s05)
1791 return 0.6666666666666666666666666667f;
1793 if (s05 >= s0 && s05 >= s_05)
1796 return 1.3333333333333333333333333333f;
1800 int two_b = -21 * i_05 + 36 * i0 - 15 * i05;
1801 // calculate max location:
1802 float ret_val = -float(two_b) / float(2 * two_a);
1803 // saturate and return
1804 if (ret_val < 0.6666666666666666666666666667f)
1805 ret_val = 0.666666666666666666666666667f;
1806 else if (ret_val > 1.33333333333333333333333333f)
1807 ret_val = 1.333333333333333333333333333f;
1808 int two_c = +12 * i_05 - 16 * i0 + 6 * i05;
1809 max = float(two_c) + float(two_a) * ret_val * ret_val + float(two_b) * ret_val;
1815 BriskScaleSpace::refine1D_2(const float s_05, const float s0, const float s05, float& max) const
1817 int i_05 = int(1024.0 * s_05 + 0.5);
1818 int i0 = int(1024.0 * s0 + 0.5);
1819 int i05 = int(1024.0 * s05 + 0.5);
1821 // 18.0000 -30.0000 12.0000
1822 // -45.0000 65.0000 -20.0000
1823 // 27.0000 -30.0000 8.0000
1825 int a = 2 * i_05 - 4 * i0 + 2 * i05;
1826 // second derivative must be negative:
1829 if (s0 >= s_05 && s0 >= s05)
1834 if (s_05 >= s0 && s_05 >= s05)
1839 if (s05 >= s0 && s05 >= s_05)
1846 int b = -5 * i_05 + 8 * i0 - 3 * i05;
1847 // calculate max location:
1848 float ret_val = -float(b) / float(2 * a);
1849 // saturate and return
1852 else if (ret_val > 1.5f)
1853 ret_val = 1.5f; // allow to be slightly off bounds ...?
1854 int c = +3 * i_05 - 3 * i0 + 1 * i05;
1855 max = float(c) + float(a) * ret_val * ret_val + float(b) * ret_val;
1861 BriskScaleSpace::subpixel2D(const int s_0_0, const int s_0_1, const int s_0_2, const int s_1_0, const int s_1_1,
1862 const int s_1_2, const int s_2_0, const int s_2_1, const int s_2_2, float& delta_x,
1863 float& delta_y) const
1866 // the coefficients of the 2d quadratic function least-squares fit:
1867 int tmp1 = s_0_0 + s_0_2 - 2 * s_1_1 + s_2_0 + s_2_2;
1868 int coeff1 = 3 * (tmp1 + s_0_1 - ((s_1_0 + s_1_2) << 1) + s_2_1);
1869 int coeff2 = 3 * (tmp1 - ((s_0_1 + s_2_1) << 1) + s_1_0 + s_1_2);
1870 int tmp2 = s_0_2 - s_2_0;
1871 int tmp3 = (s_0_0 + tmp2 - s_2_2);
1872 int tmp4 = tmp3 - 2 * tmp2;
1873 int coeff3 = -3 * (tmp3 + s_0_1 - s_2_1);
1874 int coeff4 = -3 * (tmp4 + s_1_0 - s_1_2);
1875 int coeff5 = (s_0_0 - s_0_2 - s_2_0 + s_2_2) << 2;
1876 int coeff6 = -(s_0_0 + s_0_2 - ((s_1_0 + s_0_1 + s_1_2 + s_2_1) << 1) - 5 * s_1_1 + s_2_0 + s_2_2) << 1;
1878 // 2nd derivative test:
1879 int H_det = 4 * coeff1 * coeff2 - coeff5 * coeff5;
1885 return float(coeff6) / 18.0f;
1888 if (!(H_det > 0 && coeff1 < 0))
1890 // The maximum must be at the one of the 4 patch corners.
1891 int tmp_max = coeff3 + coeff4 + coeff5;
1895 int tmp = -coeff3 + coeff4 - coeff5;
1902 tmp = coeff3 - coeff4 - coeff5;
1909 tmp = -coeff3 - coeff4 + coeff5;
1916 return float(tmp_max + coeff1 + coeff2 + coeff6) / 18.0f;
1919 // this is hopefully the normal outcome of the Hessian test
1920 delta_x = float(2 * coeff2 * coeff3 - coeff4 * coeff5) / float(-H_det);
1921 delta_y = float(2 * coeff1 * coeff4 - coeff3 * coeff5) / float(-H_det);
1922 // TODO: this is not correct, but easy, so perform a real boundary maximum search:
1929 else if (delta_x < -1.0)
1936 if (tx || tx_ || ty || ty_)
1938 // get two candidates:
1939 float delta_x1 = 0.0f, delta_x2 = 0.0f, delta_y1 = 0.0f, delta_y2 = 0.0f;
1943 delta_y1 = -float(coeff4 + coeff5) / float(2 * coeff2);
1944 if (delta_y1 > 1.0f)
1946 else if (delta_y1 < -1.0f)
1952 delta_y1 = -float(coeff4 - coeff5) / float(2 * coeff2);
1953 if (delta_y1 > 1.0f)
1955 else if (delta_y1 < -1.0)
1961 delta_x2 = -float(coeff3 + coeff5) / float(2 * coeff1);
1962 if (delta_x2 > 1.0f)
1964 else if (delta_x2 < -1.0f)
1970 delta_x2 = -float(coeff3 - coeff5) / float(2 * coeff1);
1971 if (delta_x2 > 1.0f)
1973 else if (delta_x2 < -1.0f)
1976 // insert both options for evaluation which to pick
1977 float max1 = (coeff1 * delta_x1 * delta_x1 + coeff2 * delta_y1 * delta_y1 + coeff3 * delta_x1 + coeff4 * delta_y1
1978 + coeff5 * delta_x1 * delta_y1 + coeff6)
1980 float max2 = (coeff1 * delta_x2 * delta_x2 + coeff2 * delta_y2 * delta_y2 + coeff3 * delta_x2 + coeff4 * delta_y2
1981 + coeff5 * delta_x2 * delta_y2 + coeff6)
1997 // this is the case of the maximum inside the boundaries:
1998 return (coeff1 * delta_x * delta_x + coeff2 * delta_y * delta_y + coeff3 * delta_x + coeff4 * delta_y
1999 + coeff5 * delta_x * delta_y + coeff6)
2003 // construct a layer
2004 BriskLayer::BriskLayer(const cv::Mat& img_in, float scale_in, float offset_in)
2007 scores_ = cv::Mat_<uchar>::zeros(img_in.rows, img_in.cols);
2008 // attention: this means that the passed image reference must point to persistent memory
2010 offset_ = offset_in;
2011 // create an agast detector
2012 fast_9_16_ = makePtr<FastFeatureDetector>(1, true, FastFeatureDetector::TYPE_9_16);
2013 makeOffsets(pixel_5_8_, (int)img_.step, 8);
2014 makeOffsets(pixel_9_16_, (int)img_.step, 16);
2017 BriskLayer::BriskLayer(const BriskLayer& layer, int mode)
2019 if (mode == CommonParams::HALFSAMPLE)
2021 img_.create(layer.img().rows / 2, layer.img().cols / 2, CV_8U);
2022 halfsample(layer.img(), img_);
2023 scale_ = layer.scale() * 2;
2024 offset_ = 0.5f * scale_ - 0.5f;
2028 img_.create(2 * (layer.img().rows / 3), 2 * (layer.img().cols / 3), CV_8U);
2029 twothirdsample(layer.img(), img_);
2030 scale_ = layer.scale() * 1.5f;
2031 offset_ = 0.5f * scale_ - 0.5f;
2033 scores_ = cv::Mat::zeros(img_.rows, img_.cols, CV_8U);
2034 fast_9_16_ = makePtr<FastFeatureDetector>(1, false, FastFeatureDetector::TYPE_9_16);
2035 makeOffsets(pixel_5_8_, (int)img_.step, 8);
2036 makeOffsets(pixel_9_16_, (int)img_.step, 16);
2040 // wraps the agast class
2042 BriskLayer::getAgastPoints(int threshold, std::vector<KeyPoint>& keypoints)
2044 fast_9_16_->set("threshold", threshold);
2045 fast_9_16_->detect(img_, keypoints);
2047 // also write scores
2048 const size_t num = keypoints.size();
2050 for (size_t i = 0; i < num; i++)
2051 scores_((int)keypoints[i].pt.y, (int)keypoints[i].pt.x) = saturate_cast<uchar>(keypoints[i].response);
2055 BriskLayer::getAgastScore(int x, int y, int threshold) const
2059 if (x >= img_.cols - 3 || y >= img_.rows - 3)
2061 uchar& score = (uchar&)scores_(y, x);
2066 score = (uchar)cornerScore<16>(&img_.at<uchar>(y, x), pixel_9_16_, threshold - 1);
2067 if (score < threshold)
2073 BriskLayer::getAgastScore_5_8(int x, int y, int threshold) const
2077 if (x >= img_.cols - 2 || y >= img_.rows - 2)
2079 int score = cornerScore<8>(&img_.at<uchar>(y, x), pixel_5_8_, threshold - 1);
2080 if (score < threshold)
2086 BriskLayer::getAgastScore(float xf, float yf, int threshold_in, float scale_in) const
2088 if (scale_in <= 1.0f)
2090 // just do an interpolation inside the layer
2091 const int x = int(xf);
2092 const float rx1 = xf - float(x);
2093 const float rx = 1.0f - rx1;
2094 const int y = int(yf);
2095 const float ry1 = yf - float(y);
2096 const float ry = 1.0f - ry1;
2098 return (uchar)(rx * ry * getAgastScore(x, y, threshold_in) + rx1 * ry * getAgastScore(x + 1, y, threshold_in)
2099 + rx * ry1 * getAgastScore(x, y + 1, threshold_in) + rx1 * ry1 * getAgastScore(x + 1, y + 1, threshold_in));
2103 // this means we overlap area smoothing
2104 const float halfscale = scale_in / 2.0f;
2105 // get the scores first:
2106 for (int x = int(xf - halfscale); x <= int(xf + halfscale + 1.0f); x++)
2108 for (int y = int(yf - halfscale); y <= int(yf + halfscale + 1.0f); y++)
2110 getAgastScore(x, y, threshold_in);
2113 // get the smoothed value
2114 return value(scores_, xf, yf, scale_in);
2118 // access gray values (smoothed/interpolated)
2120 BriskLayer::value(const cv::Mat& mat, float xf, float yf, float scale_in) const
2122 CV_Assert(!mat.empty());
2124 const int x = cvFloor(xf);
2125 const int y = cvFloor(yf);
2126 const cv::Mat& image = mat;
2127 const int& imagecols = image.cols;
2129 // get the sigma_half:
2130 const float sigma_half = scale_in / 2;
2131 const float area = 4.0f * sigma_half * sigma_half;
2132 // calculate output:
2134 if (sigma_half < 0.5)
2136 //interpolation multipliers:
2137 const int r_x = (int)((xf - x) * 1024);
2138 const int r_y = (int)((yf - y) * 1024);
2139 const int r_x_1 = (1024 - r_x);
2140 const int r_y_1 = (1024 - r_y);
2141 uchar* ptr = image.data + x + y * imagecols;
2142 // just interpolate:
2143 ret_val = (r_x_1 * r_y_1 * int(*ptr));
2145 ret_val += (r_x * r_y_1 * int(*ptr));
2147 ret_val += (r_x * r_y * int(*ptr));
2149 ret_val += (r_x_1 * r_y * int(*ptr));
2150 return 0xFF & ((ret_val + 512) / 1024 / 1024);
2153 // this is the standard case (simple, not speed optimized yet):
2156 const int scaling = (int)(4194304.0f / area);
2157 const int scaling2 = (int)(float(scaling) * area / 1024.0f);
2159 // calculate borders
2160 const float x_1 = xf - sigma_half;
2161 const float x1 = xf + sigma_half;
2162 const float y_1 = yf - sigma_half;
2163 const float y1 = yf + sigma_half;
2165 const int x_left = int(x_1 + 0.5);
2166 const int y_top = int(y_1 + 0.5);
2167 const int x_right = int(x1 + 0.5);
2168 const int y_bottom = int(y1 + 0.5);
2170 // overlap area - multiplication factors:
2171 const float r_x_1 = float(x_left) - x_1 + 0.5f;
2172 const float r_y_1 = float(y_top) - y_1 + 0.5f;
2173 const float r_x1 = x1 - float(x_right) + 0.5f;
2174 const float r_y1 = y1 - float(y_bottom) + 0.5f;
2175 const int dx = x_right - x_left - 1;
2176 const int dy = y_bottom - y_top - 1;
2177 const int A = (int)((r_x_1 * r_y_1) * scaling);
2178 const int B = (int)((r_x1 * r_y_1) * scaling);
2179 const int C = (int)((r_x1 * r_y1) * scaling);
2180 const int D = (int)((r_x_1 * r_y1) * scaling);
2181 const int r_x_1_i = (int)(r_x_1 * scaling);
2182 const int r_y_1_i = (int)(r_y_1 * scaling);
2183 const int r_x1_i = (int)(r_x1 * scaling);
2184 const int r_y1_i = (int)(r_y1 * scaling);
2186 // now the calculation:
2187 uchar* ptr = image.data + x_left + imagecols * y_top;
2189 ret_val = A * int(*ptr);
2191 const uchar* end1 = ptr + dx;
2192 for (; ptr < end1; ptr++)
2194 ret_val += r_y_1_i * int(*ptr);
2196 ret_val += B * int(*ptr);
2198 ptr += imagecols - dx - 1;
2199 uchar* end_j = ptr + dy * imagecols;
2200 for (; ptr < end_j; ptr += imagecols - dx - 1)
2202 ret_val += r_x_1_i * int(*ptr);
2204 const uchar* end2 = ptr + dx;
2205 for (; ptr < end2; ptr++)
2207 ret_val += int(*ptr) * scaling;
2209 ret_val += r_x1_i * int(*ptr);
2212 ret_val += D * int(*ptr);
2214 const uchar* end3 = ptr + dx;
2215 for (; ptr < end3; ptr++)
2217 ret_val += r_y1_i * int(*ptr);
2219 ret_val += C * int(*ptr);
2221 return 0xFF & ((ret_val + scaling2 / 2) / scaling2 / 1024);
2226 BriskLayer::halfsample(const cv::Mat& srcimg, cv::Mat& dstimg)
2228 // make sure the destination image is of the right size:
2229 CV_Assert(srcimg.cols / 2 == dstimg.cols);
2230 CV_Assert(srcimg.rows / 2 == dstimg.rows);
2232 // handle non-SSE case
2233 resize(srcimg, dstimg, dstimg.size(), 0, 0, INTER_AREA);
2237 BriskLayer::twothirdsample(const cv::Mat& srcimg, cv::Mat& dstimg)
2239 // make sure the destination image is of the right size:
2240 CV_Assert((srcimg.cols / 3) * 2 == dstimg.cols);
2241 CV_Assert((srcimg.rows / 3) * 2 == dstimg.rows);
2243 resize(srcimg, dstimg, dstimg.size(), 0, 0, INTER_AREA);