/* * Copyright (c) 2016, Alliance for Open Media. All rights reserved * * This source code is subject to the terms of the BSD 2 Clause License and * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License * was not distributed with this source code in the LICENSE file, you can * obtain it at www.aomedia.org/license/software. 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 www.aomedia.org/license/patent. */ #include #include #include #include #include #include #include "av1/encoder/ransac.h" #include "av1/encoder/mathutils.h" #include "av1/encoder/random.h" #define MAX_MINPTS 4 #define MAX_DEGENERATE_ITER 10 #define MINPTS_MULTIPLIER 5 #define INLIER_THRESHOLD 1.0 #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, const int n, const int stride_points, const int stride_proj); static void project_points_double_translation(double *mat, double *points, double *proj, const int n, const int stride_points, const 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, const int n, const int stride_points, const 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, const int n, const int stride_points, const 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)); 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) { const int np2 = np * 2; double *a = (double *)aom_malloc(sizeof(*a) * (np2 * 7 + 42)); 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, double *params_by_motion, int num_desired_motions, const int minpts, IsDegenerateFunc is_degenerate, FindTransformationFunc find_transformation, ProjectPointsDoubleFunc projectpoints) { static const double PROBABILITY_REQUIRED = 0.9; static const double EPS = 1e-12; int N = 10000, 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_malloc(sizeof(RANSAC_MOTION) * num_desired_motions); for (i = 0; i < num_desired_motions; ++i) { motions[i].inlier_indices = (int *)aom_malloc(sizeof(*motions->inlier_indices) * npoints); clear_motion(motions + i, npoints); } current_motion.inlier_indices = (int *)aom_malloc(sizeof(*current_motion.inlier_indices) * npoints); clear_motion(¤t_motion, npoints); worst_kept_motion = motions; if (!(points1 && points2 && corners1 && corners2 && image1_coord && motions && current_motion.inlier_indices)) { ret_val = 1; goto finish_ransac; } cnp1 = corners1; cnp2 = corners2; for (i = 0; i < npoints; ++i) { *(cnp1++) = *(matched_points++); *(cnp1++) = *(matched_points++); *(cnp2++) = *(matched_points++); *(cnp2++) = *(matched_points++); } while (N > 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) { int temp; double fracinliers, pNoOutliers, mean_distance, dtemp; 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); fracinliers = (double)current_motion.num_inliers / (double)npoints; pNoOutliers = 1 - pow(fracinliers, minpts); pNoOutliers = fmax(EPS, pNoOutliers); pNoOutliers = fmin(1 - EPS, pNoOutliers); dtemp = log(1.0 - PROBABILITY_REQUIRED) / log(pNoOutliers); temp = (dtemp > (double)INT32_MAX) ? INT32_MAX : dtemp < (double)INT32_MIN ? INT32_MIN : (int)dtemp; if (temp > 0 && temp < N) { N = AOMMAX(temp, MIN_TRIALS); } // 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 + (MAX_PARAMDIM - 1) * i); } 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); 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); } int ransac_translation(int *matched_points, int npoints, int *num_inliers_by_motion, double *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); } int ransac_rotzoom(int *matched_points, int npoints, int *num_inliers_by_motion, double *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); } int ransac_affine(int *matched_points, int npoints, int *num_inliers_by_motion, double *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); }