| /* |
| * Copyright (c) 2022, Alliance for Open Media. All rights reserved |
| * |
| * This source code is subject to the terms of the BSD 3-Clause Clear License |
| * and the Alliance for Open Media Patent License 1.0. If the BSD 3-Clause Clear |
| * License was not distributed with this source code in the LICENSE file, you |
| * can obtain it at aomedia.org/license/software-license/bsd-3-c-c/. If the |
| * Alliance for Open Media Patent License 1.0 was not distributed with this |
| * source code in the PATENTS file, you can obtain it at |
| * aomedia.org/license/patent-license/. |
| */ |
| |
| #include <memory.h> |
| #include <math.h> |
| #include <time.h> |
| #include <stdio.h> |
| #include <stdlib.h> |
| #include <assert.h> |
| |
| #include "aom_dsp/flow_estimation/ransac.h" |
| #include "aom_dsp/mathutils.h" |
| |
| // TODO(rachelbarker): Remove dependence on code in av1/encoder/ |
| #include "av1/encoder/random.h" |
| |
| #define MAX_MINPTS 4 |
| #define MAX_DEGENERATE_ITER 10 |
| #define MINPTS_MULTIPLIER 5 |
| |
| #define INLIER_THRESHOLD 1.25 |
| #define MIN_TRIALS 20 |
| |
| //////////////////////////////////////////////////////////////////////////////// |
| // ransac |
| typedef int (*IsDegenerateFunc)(double *p); |
| typedef void (*NormalizeFunc)(double *p, int np, double *T); |
| typedef void (*DenormalizeFunc)(double *params, double *T1, double *T2); |
| typedef int (*FindTransformationFunc)(int points, double *points1, |
| double *points2, double *params); |
| typedef void (*ProjectPointsDoubleFunc)(double *mat, double *points, |
| double *proj, int n, int stride_points, |
| int stride_proj); |
| |
| static void project_points_double_translation(double *mat, double *points, |
| double *proj, int n, |
| int stride_points, |
| int stride_proj) { |
| int i; |
| for (i = 0; i < n; ++i) { |
| const double x = *(points++), y = *(points++); |
| *(proj++) = x + mat[0]; |
| *(proj++) = y + mat[1]; |
| points += stride_points - 2; |
| proj += stride_proj - 2; |
| } |
| } |
| |
| static void project_points_double_rotzoom(double *mat, double *points, |
| double *proj, int n, |
| int stride_points, int stride_proj) { |
| int i; |
| for (i = 0; i < n; ++i) { |
| const double x = *(points++), y = *(points++); |
| *(proj++) = mat[2] * x + mat[3] * y + mat[0]; |
| *(proj++) = -mat[3] * x + mat[2] * y + mat[1]; |
| points += stride_points - 2; |
| proj += stride_proj - 2; |
| } |
| } |
| |
| static void project_points_double_affine(double *mat, double *points, |
| double *proj, int n, int stride_points, |
| int stride_proj) { |
| int i; |
| for (i = 0; i < n; ++i) { |
| const double x = *(points++), y = *(points++); |
| *(proj++) = mat[2] * x + mat[3] * y + mat[0]; |
| *(proj++) = mat[4] * x + mat[5] * y + mat[1]; |
| points += stride_points - 2; |
| proj += stride_proj - 2; |
| } |
| } |
| |
| static void normalize_homography(double *pts, int n, double *T) { |
| double *p = pts; |
| double mean[2] = { 0, 0 }; |
| double msqe = 0; |
| double scale; |
| int i; |
| |
| assert(n > 0); |
| for (i = 0; i < n; ++i, p += 2) { |
| mean[0] += p[0]; |
| mean[1] += p[1]; |
| } |
| mean[0] /= n; |
| mean[1] /= n; |
| for (p = pts, i = 0; i < n; ++i, p += 2) { |
| p[0] -= mean[0]; |
| p[1] -= mean[1]; |
| msqe += sqrt(p[0] * p[0] + p[1] * p[1]); |
| } |
| msqe /= n; |
| scale = (msqe == 0 ? 1.0 : sqrt(2) / msqe); |
| T[0] = scale; |
| T[1] = 0; |
| T[2] = -scale * mean[0]; |
| T[3] = 0; |
| T[4] = scale; |
| T[5] = -scale * mean[1]; |
| T[6] = 0; |
| T[7] = 0; |
| T[8] = 1; |
| for (p = pts, i = 0; i < n; ++i, p += 2) { |
| p[0] *= scale; |
| p[1] *= scale; |
| } |
| } |
| |
| static void invnormalize_mat(double *T, double *iT) { |
| double is = 1.0 / T[0]; |
| double m0 = -T[2] * is; |
| double m1 = -T[5] * is; |
| iT[0] = is; |
| iT[1] = 0; |
| iT[2] = m0; |
| iT[3] = 0; |
| iT[4] = is; |
| iT[5] = m1; |
| iT[6] = 0; |
| iT[7] = 0; |
| iT[8] = 1; |
| } |
| |
| static void denormalize_homography(double *params, double *T1, double *T2) { |
| double iT2[9]; |
| double params2[9]; |
| invnormalize_mat(T2, iT2); |
| multiply_mat(params, T1, params2, 3, 3, 3); |
| multiply_mat(iT2, params2, params, 3, 3, 3); |
| } |
| |
| static void denormalize_affine_reorder(double *params, double *T1, double *T2) { |
| double params_denorm[MAX_PARAMDIM]; |
| params_denorm[0] = params[0]; |
| params_denorm[1] = params[1]; |
| params_denorm[2] = params[4]; |
| params_denorm[3] = params[2]; |
| params_denorm[4] = params[3]; |
| params_denorm[5] = params[5]; |
| params_denorm[6] = params_denorm[7] = 0; |
| params_denorm[8] = 1; |
| denormalize_homography(params_denorm, T1, T2); |
| params[0] = params_denorm[2]; |
| params[1] = params_denorm[5]; |
| params[2] = params_denorm[0]; |
| params[3] = params_denorm[1]; |
| params[4] = params_denorm[3]; |
| params[5] = params_denorm[4]; |
| params[6] = params[7] = 0; |
| } |
| |
| static void denormalize_rotzoom_reorder(double *params, double *T1, |
| double *T2) { |
| double params_denorm[MAX_PARAMDIM]; |
| params_denorm[0] = params[0]; |
| params_denorm[1] = params[1]; |
| params_denorm[2] = params[2]; |
| params_denorm[3] = -params[1]; |
| params_denorm[4] = params[0]; |
| params_denorm[5] = params[3]; |
| params_denorm[6] = params_denorm[7] = 0; |
| params_denorm[8] = 1; |
| denormalize_homography(params_denorm, T1, T2); |
| params[0] = params_denorm[2]; |
| params[1] = params_denorm[5]; |
| params[2] = params_denorm[0]; |
| params[3] = params_denorm[1]; |
| params[4] = -params[3]; |
| params[5] = params[2]; |
| params[6] = params[7] = 0; |
| } |
| |
| static void denormalize_translation_reorder(double *params, double *T1, |
| double *T2) { |
| double params_denorm[MAX_PARAMDIM]; |
| params_denorm[0] = 1; |
| params_denorm[1] = 0; |
| params_denorm[2] = params[0]; |
| params_denorm[3] = 0; |
| params_denorm[4] = 1; |
| params_denorm[5] = params[1]; |
| params_denorm[6] = params_denorm[7] = 0; |
| params_denorm[8] = 1; |
| denormalize_homography(params_denorm, T1, T2); |
| params[0] = params_denorm[2]; |
| params[1] = params_denorm[5]; |
| params[2] = params[5] = 1; |
| params[3] = params[4] = 0; |
| params[6] = params[7] = 0; |
| } |
| |
| static int find_translation(int np, double *pts1, double *pts2, double *mat) { |
| int i; |
| double sx, sy, dx, dy; |
| double sumx, sumy; |
| |
| double T1[9], T2[9]; |
| normalize_homography(pts1, np, T1); |
| normalize_homography(pts2, np, T2); |
| |
| sumx = 0; |
| sumy = 0; |
| for (i = 0; i < np; ++i) { |
| dx = *(pts2++); |
| dy = *(pts2++); |
| sx = *(pts1++); |
| sy = *(pts1++); |
| |
| sumx += dx - sx; |
| sumy += dy - sy; |
| } |
| mat[0] = sumx / np; |
| mat[1] = sumy / np; |
| denormalize_translation_reorder(mat, T1, T2); |
| return 0; |
| } |
| |
| static int find_rotzoom(int np, double *pts1, double *pts2, double *mat) { |
| const int np2 = np * 2; |
| double *a = (double *)aom_malloc(sizeof(*a) * (np2 * 5 + 20)); |
| if (a == NULL) return 1; |
| double *b = a + np2 * 4; |
| double *temp = b + np2; |
| int i; |
| double sx, sy, dx, dy; |
| |
| double T1[9], T2[9]; |
| normalize_homography(pts1, np, T1); |
| normalize_homography(pts2, np, T2); |
| |
| for (i = 0; i < np; ++i) { |
| dx = *(pts2++); |
| dy = *(pts2++); |
| sx = *(pts1++); |
| sy = *(pts1++); |
| |
| a[i * 2 * 4 + 0] = sx; |
| a[i * 2 * 4 + 1] = sy; |
| a[i * 2 * 4 + 2] = 1; |
| a[i * 2 * 4 + 3] = 0; |
| a[(i * 2 + 1) * 4 + 0] = sy; |
| a[(i * 2 + 1) * 4 + 1] = -sx; |
| a[(i * 2 + 1) * 4 + 2] = 0; |
| a[(i * 2 + 1) * 4 + 3] = 1; |
| |
| b[2 * i] = dx; |
| b[2 * i + 1] = dy; |
| } |
| if (!least_squares(4, a, np2, 4, b, temp, mat)) { |
| aom_free(a); |
| return 1; |
| } |
| denormalize_rotzoom_reorder(mat, T1, T2); |
| aom_free(a); |
| return 0; |
| } |
| |
| static int find_affine(int np, double *pts1, double *pts2, double *mat) { |
| assert(np > 0); |
| const int np2 = np * 2; |
| double *a = (double *)aom_malloc(sizeof(*a) * (np2 * 7 + 42)); |
| if (a == NULL) return 1; |
| double *b = a + np2 * 6; |
| double *temp = b + np2; |
| int i; |
| double sx, sy, dx, dy; |
| |
| double T1[9], T2[9]; |
| normalize_homography(pts1, np, T1); |
| normalize_homography(pts2, np, T2); |
| |
| for (i = 0; i < np; ++i) { |
| dx = *(pts2++); |
| dy = *(pts2++); |
| sx = *(pts1++); |
| sy = *(pts1++); |
| |
| a[i * 2 * 6 + 0] = sx; |
| a[i * 2 * 6 + 1] = sy; |
| a[i * 2 * 6 + 2] = 0; |
| a[i * 2 * 6 + 3] = 0; |
| a[i * 2 * 6 + 4] = 1; |
| a[i * 2 * 6 + 5] = 0; |
| a[(i * 2 + 1) * 6 + 0] = 0; |
| a[(i * 2 + 1) * 6 + 1] = 0; |
| a[(i * 2 + 1) * 6 + 2] = sx; |
| a[(i * 2 + 1) * 6 + 3] = sy; |
| a[(i * 2 + 1) * 6 + 4] = 0; |
| a[(i * 2 + 1) * 6 + 5] = 1; |
| |
| b[2 * i] = dx; |
| b[2 * i + 1] = dy; |
| } |
| if (!least_squares(6, a, np2, 6, b, temp, mat)) { |
| aom_free(a); |
| return 1; |
| } |
| denormalize_affine_reorder(mat, T1, T2); |
| aom_free(a); |
| return 0; |
| } |
| |
| static int get_rand_indices(int npoints, int minpts, int *indices, |
| unsigned int *seed) { |
| int i, j; |
| int ptr = lcg_rand16(seed) % npoints; |
| if (minpts > npoints) return 0; |
| indices[0] = ptr; |
| ptr = (ptr == npoints - 1 ? 0 : ptr + 1); |
| i = 1; |
| while (i < minpts) { |
| int index = lcg_rand16(seed) % npoints; |
| while (index) { |
| ptr = (ptr == npoints - 1 ? 0 : ptr + 1); |
| for (j = 0; j < i; ++j) { |
| if (indices[j] == ptr) break; |
| } |
| if (j == i) index--; |
| } |
| indices[i++] = ptr; |
| } |
| return 1; |
| } |
| |
| typedef struct { |
| int num_inliers; |
| double variance; |
| int *inlier_indices; |
| } RANSAC_MOTION; |
| |
| // Return -1 if 'a' is a better motion, 1 if 'b' is better, 0 otherwise. |
| static int compare_motions(const void *arg_a, const void *arg_b) { |
| const RANSAC_MOTION *motion_a = (RANSAC_MOTION *)arg_a; |
| const RANSAC_MOTION *motion_b = (RANSAC_MOTION *)arg_b; |
| |
| if (motion_a->num_inliers > motion_b->num_inliers) return -1; |
| if (motion_a->num_inliers < motion_b->num_inliers) return 1; |
| if (motion_a->variance < motion_b->variance) return -1; |
| if (motion_a->variance > motion_b->variance) return 1; |
| return 0; |
| } |
| |
| static int is_better_motion(const RANSAC_MOTION *motion_a, |
| const RANSAC_MOTION *motion_b) { |
| return compare_motions(motion_a, motion_b) < 0; |
| } |
| |
| static void copy_points_at_indices(double *dest, const double *src, |
| const int *indices, int num_points) { |
| for (int i = 0; i < num_points; ++i) { |
| const int index = indices[i]; |
| dest[i * 2] = src[index * 2]; |
| dest[i * 2 + 1] = src[index * 2 + 1]; |
| } |
| } |
| |
| static const double kInfiniteVariance = 1e12; |
| |
| static void clear_motion(RANSAC_MOTION *motion, int num_points) { |
| motion->num_inliers = 0; |
| motion->variance = kInfiniteVariance; |
| memset(motion->inlier_indices, 0, |
| sizeof(*motion->inlier_indices) * num_points); |
| } |
| |
| static int ransac(const int *matched_points, int npoints, |
| int *num_inliers_by_motion, MotionModel *params_by_motion, |
| int num_desired_motions, int minpts, |
| IsDegenerateFunc is_degenerate, |
| FindTransformationFunc find_transformation, |
| ProjectPointsDoubleFunc projectpoints) { |
| int trial_count = 0; |
| int i = 0; |
| int ret_val = 0; |
| |
| unsigned int seed = (unsigned int)npoints; |
| |
| int indices[MAX_MINPTS] = { 0 }; |
| |
| double *points1, *points2; |
| double *corners1, *corners2; |
| double *image1_coord; |
| |
| // Store information for the num_desired_motions best transformations found |
| // and the worst motion among them, as well as the motion currently under |
| // consideration. |
| RANSAC_MOTION *motions, *worst_kept_motion = NULL; |
| RANSAC_MOTION current_motion; |
| |
| // Store the parameters and the indices of the inlier points for the motion |
| // currently under consideration. |
| double params_this_motion[MAX_PARAMDIM]; |
| |
| double *cnp1, *cnp2; |
| |
| for (i = 0; i < num_desired_motions; ++i) { |
| num_inliers_by_motion[i] = 0; |
| } |
| if (npoints < minpts * MINPTS_MULTIPLIER || npoints == 0) { |
| return 1; |
| } |
| |
| points1 = (double *)aom_malloc(sizeof(*points1) * npoints * 2); |
| points2 = (double *)aom_malloc(sizeof(*points2) * npoints * 2); |
| corners1 = (double *)aom_malloc(sizeof(*corners1) * npoints * 2); |
| corners2 = (double *)aom_malloc(sizeof(*corners2) * npoints * 2); |
| image1_coord = (double *)aom_malloc(sizeof(*image1_coord) * npoints * 2); |
| motions = |
| (RANSAC_MOTION *)aom_calloc(num_desired_motions, sizeof(RANSAC_MOTION)); |
| current_motion.inlier_indices = |
| (int *)aom_malloc(sizeof(*current_motion.inlier_indices) * npoints); |
| if (!(points1 && points2 && corners1 && corners2 && image1_coord && motions && |
| current_motion.inlier_indices)) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| |
| for (i = 0; i < num_desired_motions; ++i) { |
| motions[i].inlier_indices = |
| (int *)aom_malloc(sizeof(*motions->inlier_indices) * npoints); |
| if (!motions[i].inlier_indices) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| clear_motion(motions + i, npoints); |
| } |
| clear_motion(¤t_motion, npoints); |
| |
| worst_kept_motion = motions; |
| |
| cnp1 = corners1; |
| cnp2 = corners2; |
| for (i = 0; i < npoints; ++i) { |
| *(cnp1++) = *(matched_points++); |
| *(cnp1++) = *(matched_points++); |
| *(cnp2++) = *(matched_points++); |
| *(cnp2++) = *(matched_points++); |
| } |
| |
| while (MIN_TRIALS > trial_count) { |
| double sum_distance = 0.0; |
| double sum_distance_squared = 0.0; |
| |
| clear_motion(¤t_motion, npoints); |
| |
| int degenerate = 1; |
| int num_degenerate_iter = 0; |
| |
| while (degenerate) { |
| num_degenerate_iter++; |
| if (!get_rand_indices(npoints, minpts, indices, &seed)) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| |
| copy_points_at_indices(points1, corners1, indices, minpts); |
| copy_points_at_indices(points2, corners2, indices, minpts); |
| |
| degenerate = is_degenerate(points1); |
| if (num_degenerate_iter > MAX_DEGENERATE_ITER) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| } |
| |
| if (find_transformation(minpts, points1, points2, params_this_motion)) { |
| trial_count++; |
| continue; |
| } |
| |
| projectpoints(params_this_motion, corners1, image1_coord, npoints, 2, 2); |
| |
| for (i = 0; i < npoints; ++i) { |
| double dx = image1_coord[i * 2] - corners2[i * 2]; |
| double dy = image1_coord[i * 2 + 1] - corners2[i * 2 + 1]; |
| double distance = sqrt(dx * dx + dy * dy); |
| |
| if (distance < INLIER_THRESHOLD) { |
| current_motion.inlier_indices[current_motion.num_inliers++] = i; |
| sum_distance += distance; |
| sum_distance_squared += distance * distance; |
| } |
| } |
| |
| if (current_motion.num_inliers >= worst_kept_motion->num_inliers && |
| current_motion.num_inliers > 1) { |
| double mean_distance; |
| mean_distance = sum_distance / ((double)current_motion.num_inliers); |
| current_motion.variance = |
| sum_distance_squared / ((double)current_motion.num_inliers - 1.0) - |
| mean_distance * mean_distance * ((double)current_motion.num_inliers) / |
| ((double)current_motion.num_inliers - 1.0); |
| if (is_better_motion(¤t_motion, worst_kept_motion)) { |
| // This motion is better than the worst currently kept motion. Remember |
| // the inlier points and variance. The parameters for each kept motion |
| // will be recomputed later using only the inliers. |
| worst_kept_motion->num_inliers = current_motion.num_inliers; |
| worst_kept_motion->variance = current_motion.variance; |
| memcpy(worst_kept_motion->inlier_indices, current_motion.inlier_indices, |
| sizeof(*current_motion.inlier_indices) * npoints); |
| assert(npoints > 0); |
| // Determine the new worst kept motion and its num_inliers and variance. |
| for (i = 0; i < num_desired_motions; ++i) { |
| if (is_better_motion(worst_kept_motion, &motions[i])) { |
| worst_kept_motion = &motions[i]; |
| } |
| } |
| } |
| } |
| trial_count++; |
| } |
| |
| // Sort the motions, best first. |
| qsort(motions, num_desired_motions, sizeof(RANSAC_MOTION), compare_motions); |
| |
| // Recompute the motions using only the inliers. |
| for (i = 0; i < num_desired_motions; ++i) { |
| if (motions[i].num_inliers >= minpts) { |
| copy_points_at_indices(points1, corners1, motions[i].inlier_indices, |
| motions[i].num_inliers); |
| copy_points_at_indices(points2, corners2, motions[i].inlier_indices, |
| motions[i].num_inliers); |
| |
| find_transformation(motions[i].num_inliers, points1, points2, |
| params_by_motion[i].params); |
| |
| params_by_motion[i].num_inliers = motions[i].num_inliers; |
| memcpy(params_by_motion[i].inliers, motions[i].inlier_indices, |
| sizeof(*motions[i].inlier_indices) * npoints); |
| num_inliers_by_motion[i] = motions[i].num_inliers; |
| } |
| } |
| |
| finish_ransac: |
| aom_free(points1); |
| aom_free(points2); |
| aom_free(corners1); |
| aom_free(corners2); |
| aom_free(image1_coord); |
| aom_free(current_motion.inlier_indices); |
| if (motions) { |
| for (i = 0; i < num_desired_motions; ++i) { |
| aom_free(motions[i].inlier_indices); |
| } |
| aom_free(motions); |
| } |
| |
| return ret_val; |
| } |
| |
| static int ransac_double_prec(const double *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions, int minpts, |
| IsDegenerateFunc is_degenerate, |
| FindTransformationFunc find_transformation, |
| ProjectPointsDoubleFunc projectpoints) { |
| int trial_count = 0; |
| int i = 0; |
| int ret_val = 0; |
| |
| unsigned int seed = (unsigned int)npoints; |
| |
| int indices[MAX_MINPTS] = { 0 }; |
| |
| double *points1, *points2; |
| double *corners1, *corners2; |
| double *image1_coord; |
| |
| // Store information for the num_desired_motions best transformations found |
| // and the worst motion among them, as well as the motion currently under |
| // consideration. |
| RANSAC_MOTION *motions, *worst_kept_motion = NULL; |
| RANSAC_MOTION current_motion; |
| |
| // Store the parameters and the indices of the inlier points for the motion |
| // currently under consideration. |
| double params_this_motion[MAX_PARAMDIM]; |
| |
| double *cnp1, *cnp2; |
| |
| for (i = 0; i < num_desired_motions; ++i) { |
| num_inliers_by_motion[i] = 0; |
| } |
| if (npoints < minpts * MINPTS_MULTIPLIER || npoints == 0) { |
| return 1; |
| } |
| |
| points1 = (double *)aom_malloc(sizeof(*points1) * npoints * 2); |
| points2 = (double *)aom_malloc(sizeof(*points2) * npoints * 2); |
| corners1 = (double *)aom_malloc(sizeof(*corners1) * npoints * 2); |
| corners2 = (double *)aom_malloc(sizeof(*corners2) * npoints * 2); |
| image1_coord = (double *)aom_malloc(sizeof(*image1_coord) * npoints * 2); |
| motions = |
| (RANSAC_MOTION *)aom_calloc(num_desired_motions, sizeof(RANSAC_MOTION)); |
| current_motion.inlier_indices = |
| (int *)aom_malloc(sizeof(*current_motion.inlier_indices) * npoints); |
| if (!(points1 && points2 && corners1 && corners2 && image1_coord && motions && |
| current_motion.inlier_indices)) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| |
| for (i = 0; i < num_desired_motions; ++i) { |
| motions[i].inlier_indices = |
| (int *)aom_malloc(sizeof(*motions->inlier_indices) * npoints); |
| if (!motions[i].inlier_indices) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| clear_motion(motions + i, npoints); |
| } |
| clear_motion(¤t_motion, npoints); |
| |
| worst_kept_motion = motions; |
| |
| cnp1 = corners1; |
| cnp2 = corners2; |
| for (i = 0; i < npoints; ++i) { |
| *(cnp1++) = *(matched_points++); |
| *(cnp1++) = *(matched_points++); |
| *(cnp2++) = *(matched_points++); |
| *(cnp2++) = *(matched_points++); |
| } |
| |
| while (MIN_TRIALS > trial_count) { |
| double sum_distance = 0.0; |
| double sum_distance_squared = 0.0; |
| |
| clear_motion(¤t_motion, npoints); |
| |
| int degenerate = 1; |
| int num_degenerate_iter = 0; |
| |
| while (degenerate) { |
| num_degenerate_iter++; |
| if (!get_rand_indices(npoints, minpts, indices, &seed)) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| |
| copy_points_at_indices(points1, corners1, indices, minpts); |
| copy_points_at_indices(points2, corners2, indices, minpts); |
| |
| degenerate = is_degenerate(points1); |
| if (num_degenerate_iter > MAX_DEGENERATE_ITER) { |
| ret_val = 1; |
| goto finish_ransac; |
| } |
| } |
| |
| if (find_transformation(minpts, points1, points2, params_this_motion)) { |
| trial_count++; |
| continue; |
| } |
| |
| projectpoints(params_this_motion, corners1, image1_coord, npoints, 2, 2); |
| |
| for (i = 0; i < npoints; ++i) { |
| double dx = image1_coord[i * 2] - corners2[i * 2]; |
| double dy = image1_coord[i * 2 + 1] - corners2[i * 2 + 1]; |
| double distance = sqrt(dx * dx + dy * dy); |
| |
| if (distance < INLIER_THRESHOLD) { |
| current_motion.inlier_indices[current_motion.num_inliers++] = i; |
| sum_distance += distance; |
| sum_distance_squared += distance * distance; |
| } |
| } |
| |
| if (current_motion.num_inliers >= worst_kept_motion->num_inliers && |
| current_motion.num_inliers > 1) { |
| double mean_distance; |
| mean_distance = sum_distance / ((double)current_motion.num_inliers); |
| current_motion.variance = |
| sum_distance_squared / ((double)current_motion.num_inliers - 1.0) - |
| mean_distance * mean_distance * ((double)current_motion.num_inliers) / |
| ((double)current_motion.num_inliers - 1.0); |
| if (is_better_motion(¤t_motion, worst_kept_motion)) { |
| // This motion is better than the worst currently kept motion. Remember |
| // the inlier points and variance. The parameters for each kept motion |
| // will be recomputed later using only the inliers. |
| worst_kept_motion->num_inliers = current_motion.num_inliers; |
| worst_kept_motion->variance = current_motion.variance; |
| memcpy(worst_kept_motion->inlier_indices, current_motion.inlier_indices, |
| sizeof(*current_motion.inlier_indices) * npoints); |
| assert(npoints > 0); |
| // Determine the new worst kept motion and its num_inliers and variance. |
| for (i = 0; i < num_desired_motions; ++i) { |
| if (is_better_motion(worst_kept_motion, &motions[i])) { |
| worst_kept_motion = &motions[i]; |
| } |
| } |
| } |
| } |
| trial_count++; |
| } |
| |
| // Sort the motions, best first. |
| qsort(motions, num_desired_motions, sizeof(RANSAC_MOTION), compare_motions); |
| |
| // Recompute the motions using only the inliers. |
| for (i = 0; i < num_desired_motions; ++i) { |
| if (motions[i].num_inliers >= minpts) { |
| copy_points_at_indices(points1, corners1, motions[i].inlier_indices, |
| motions[i].num_inliers); |
| copy_points_at_indices(points2, corners2, motions[i].inlier_indices, |
| motions[i].num_inliers); |
| |
| find_transformation(motions[i].num_inliers, points1, points2, |
| params_by_motion[i].params); |
| memcpy(params_by_motion[i].inliers, motions[i].inlier_indices, |
| sizeof(*motions[i].inlier_indices) * npoints); |
| } |
| num_inliers_by_motion[i] = motions[i].num_inliers; |
| } |
| |
| finish_ransac: |
| aom_free(points1); |
| aom_free(points2); |
| aom_free(corners1); |
| aom_free(corners2); |
| aom_free(image1_coord); |
| aom_free(current_motion.inlier_indices); |
| if (motions) { |
| for (i = 0; i < num_desired_motions; ++i) { |
| aom_free(motions[i].inlier_indices); |
| } |
| aom_free(motions); |
| } |
| |
| return ret_val; |
| } |
| |
| static int is_collinear3(double *p1, double *p2, double *p3) { |
| static const double collinear_eps = 1e-3; |
| const double v = |
| (p2[0] - p1[0]) * (p3[1] - p1[1]) - (p2[1] - p1[1]) * (p3[0] - p1[0]); |
| return fabs(v) < collinear_eps; |
| } |
| |
| static int is_degenerate_translation(double *p) { |
| return (p[0] - p[2]) * (p[0] - p[2]) + (p[1] - p[3]) * (p[1] - p[3]) <= 2; |
| } |
| |
| static int is_degenerate_affine(double *p) { |
| return is_collinear3(p, p + 2, p + 4); |
| } |
| |
| static int ransac_translation(int *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions) { |
| return ransac(matched_points, npoints, num_inliers_by_motion, |
| params_by_motion, num_desired_motions, 3, |
| is_degenerate_translation, find_translation, |
| project_points_double_translation); |
| } |
| |
| static int ransac_rotzoom(int *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions) { |
| return ransac(matched_points, npoints, num_inliers_by_motion, |
| params_by_motion, num_desired_motions, 3, is_degenerate_affine, |
| find_rotzoom, project_points_double_rotzoom); |
| } |
| |
| static int ransac_affine(int *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions) { |
| return ransac(matched_points, npoints, num_inliers_by_motion, |
| params_by_motion, num_desired_motions, 3, is_degenerate_affine, |
| find_affine, project_points_double_affine); |
| } |
| |
| RansacFunc av1_get_ransac_type(TransformationType type) { |
| switch (type) { |
| case AFFINE: return ransac_affine; |
| case ROTZOOM: return ransac_rotzoom; |
| case TRANSLATION: return ransac_translation; |
| default: assert(0); return NULL; |
| } |
| } |
| |
| static int ransac_translation_double_prec(double *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions) { |
| return ransac_double_prec(matched_points, npoints, num_inliers_by_motion, |
| params_by_motion, num_desired_motions, 3, |
| is_degenerate_translation, find_translation, |
| project_points_double_translation); |
| } |
| |
| static int ransac_rotzoom_double_prec(double *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions) { |
| return ransac_double_prec(matched_points, npoints, num_inliers_by_motion, |
| params_by_motion, num_desired_motions, 3, |
| is_degenerate_affine, find_rotzoom, |
| project_points_double_rotzoom); |
| } |
| |
| static int ransac_affine_double_prec(double *matched_points, int npoints, |
| int *num_inliers_by_motion, |
| MotionModel *params_by_motion, |
| int num_desired_motions) { |
| return ransac_double_prec(matched_points, npoints, num_inliers_by_motion, |
| params_by_motion, num_desired_motions, 3, |
| is_degenerate_affine, find_affine, |
| project_points_double_affine); |
| } |
| |
| RansacFuncDouble av1_get_ransac_double_prec_type(TransformationType type) { |
| switch (type) { |
| case AFFINE: return ransac_affine_double_prec; |
| case ROTZOOM: return ransac_rotzoom_double_prec; |
| case TRANSLATION: return ransac_translation_double_prec; |
| default: assert(0); return NULL; |
| } |
| } |