| /* | |
| * (c) 2010 The WebM project authors. All Rights Reserved. | |
| * | |
| * Use of this source code is governed by a BSD-style license | |
| * that can be found in the LICENSE file in the root of the source | |
| * tree. An additional intellectual property rights grant can be found | |
| * in the file PATENTS. All contributing project authors may | |
| * be found in the AUTHORS file in the root of the source tree. | |
| */ | |
| #include <memory.h> | |
| #include <math.h> | |
| #include <time.h> | |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| #include <assert.h> | |
| #include "av1/encoder/ransac.h" | |
| #define MAX_MINPTS 4 | |
| #define MAX_DEGENERATE_ITER 10 | |
| #define MINPTS_MULTIPLIER 5 | |
| //////////////////////////////////////////////////////////////////////////////// | |
| // 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[1]; | |
| *(proj++) = y + mat[0]; | |
| 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[3] * x + mat[2] * y + mat[1]; | |
| *(proj++) = -mat[2] * x + mat[3] * y + mat[0]; | |
| 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[3] * x + mat[2] * y + mat[1]; | |
| *(proj++) = mat[4] * x + mat[5] * y + mat[0]; | |
| points += stride_points - 2; | |
| proj += stride_proj - 2; | |
| } | |
| } | |
| static void project_points_double_homography(double *mat, double *points, | |
| double *proj, const int n, | |
| const int stride_points, | |
| const int stride_proj) { | |
| int i; | |
| double x, y, Z, Z_inv; | |
| for (i = 0; i < n; ++i) { | |
| x = *(points++), y = *(points++); | |
| Z_inv = mat[7] * x + mat[6] * y + 1; | |
| assert(fabs(Z_inv) > 0.00001); | |
| Z = 1. / Z_inv; | |
| *(proj++) = (mat[1] * x + mat[0] * y + mat[3]) * Z; | |
| *(proj++) = (mat[2] * x + mat[4] * y + mat[4]) * Z; | |
| points += stride_points - 2; | |
| proj += stride_proj - 2; | |
| } | |
| } | |
| static int get_rand_indices(int npoints, int minpts, int *indices, | |
| unsigned int *seed) { | |
| int i, j; | |
| int ptr = rand_r(seed) % npoints; | |
| if (minpts > npoints) return 0; | |
| indices[0] = ptr; | |
| ptr = (ptr == npoints - 1 ? 0 : ptr + 1); | |
| i = 1; | |
| while (i < minpts) { | |
| int index = rand_r(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; | |
| } | |
| static int ransac(double *matched_points, int npoints, int *number_of_inliers, | |
| int *best_inlier_mask, double *best_params, const int minpts, | |
| const int paramdim, IsDegenerateFunc is_degenerate, | |
| NormalizeFunc normalize, DenormalizeFunc denormalize, | |
| FindTransformationFunc find_transformation, | |
| ProjectPointsDoubleFunc projectpoints) { | |
| static const double INLIER_THRESHOLD_NORMALIZED = 0.1; | |
| static const double INLIER_THRESHOLD_UNNORMALIZED = 1.0; | |
| static const double PROBABILITY_REQUIRED = 0.9; | |
| static const double EPS = 1e-12; | |
| static const int MIN_TRIALS = 20; | |
| const double inlier_threshold = | |
| (normalize && denormalize ? INLIER_THRESHOLD_NORMALIZED | |
| : INLIER_THRESHOLD_UNNORMALIZED); | |
| int N = 10000, trial_count = 0; | |
| int i; | |
| int ret_val = 0; | |
| unsigned int seed = (unsigned int)npoints; | |
| int max_inliers = 0; | |
| double best_variance = 0.0; | |
| double params[MAX_PARAMDIM]; | |
| WarpedMotionParams wm; | |
| double points1[2 * MAX_MINPTS]; | |
| double points2[2 * MAX_MINPTS]; | |
| int indices[MAX_MINPTS] = { 0 }; | |
| double *best_inlier_set1; | |
| double *best_inlier_set2; | |
| double *inlier_set1; | |
| double *inlier_set2; | |
| double *corners1; | |
| double *corners2; | |
| double *image1_coord; | |
| int *inlier_mask; | |
| double *cnp1, *cnp2; | |
| double T1[9], T2[9]; | |
| *number_of_inliers = 0; | |
| if (npoints < minpts * MINPTS_MULTIPLIER || npoints == 0) { | |
| printf("Cannot find motion with %d matches\n", npoints); | |
| return 1; | |
| } | |
| memset(&wm, 0, sizeof(wm)); | |
| best_inlier_set1 = | |
| (double *)aom_malloc(sizeof(*best_inlier_set1) * npoints * 2); | |
| best_inlier_set2 = | |
| (double *)aom_malloc(sizeof(*best_inlier_set2) * npoints * 2); | |
| inlier_set1 = (double *)aom_malloc(sizeof(*inlier_set1) * npoints * 2); | |
| inlier_set2 = (double *)aom_malloc(sizeof(*inlier_set2) * 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); | |
| inlier_mask = (int *)aom_malloc(sizeof(*inlier_mask) * npoints); | |
| if (!(best_inlier_set1 && best_inlier_set2 && inlier_set1 && inlier_set2 && | |
| corners1 && corners2 && image1_coord && inlier_mask)) { | |
| ret_val = 1; | |
| goto finish_ransac; | |
| } | |
| for (cnp1 = corners1, cnp2 = corners2, i = 0; i < npoints; ++i) { | |
| *(cnp1++) = *(matched_points++); | |
| *(cnp1++) = *(matched_points++); | |
| *(cnp2++) = *(matched_points++); | |
| *(cnp2++) = *(matched_points++); | |
| } | |
| matched_points -= 4 * npoints; | |
| if (normalize && denormalize) { | |
| normalize(corners1, npoints, T1); | |
| normalize(corners2, npoints, T2); | |
| } | |
| while (N > trial_count) { | |
| int num_inliers = 0; | |
| double sum_distance = 0.0; | |
| double sum_distance_squared = 0.0; | |
| 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; | |
| } | |
| i = 0; | |
| while (i < minpts) { | |
| int index = indices[i]; | |
| // add to list | |
| points1[i * 2] = corners1[index * 2]; | |
| points1[i * 2 + 1] = corners1[index * 2 + 1]; | |
| points2[i * 2] = corners2[index * 2]; | |
| points2[i * 2 + 1] = corners2[index * 2 + 1]; | |
| i++; | |
| } | |
| degenerate = is_degenerate(points1); | |
| if (num_degenerate_iter > MAX_DEGENERATE_ITER) { | |
| ret_val = 1; | |
| goto finish_ransac; | |
| } | |
| } | |
| if (find_transformation(minpts, points1, points2, params)) { | |
| trial_count++; | |
| continue; | |
| } | |
| projectpoints(params, 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); | |
| inlier_mask[i] = distance < inlier_threshold; | |
| if (inlier_mask[i]) { | |
| inlier_set1[num_inliers * 2] = corners1[i * 2]; | |
| inlier_set1[num_inliers * 2 + 1] = corners1[i * 2 + 1]; | |
| inlier_set2[num_inliers * 2] = corners2[i * 2]; | |
| inlier_set2[num_inliers * 2 + 1] = corners2[i * 2 + 1]; | |
| num_inliers++; | |
| sum_distance += distance; | |
| sum_distance_squared += distance * distance; | |
| } | |
| } | |
| if (num_inliers >= max_inliers && num_inliers > 1) { | |
| int temp; | |
| double fracinliers, pNoOutliers, mean_distance, variance; | |
| assert(num_inliers > 1); | |
| mean_distance = sum_distance / ((double)num_inliers); | |
| variance = sum_distance_squared / ((double)num_inliers - 1.0) - | |
| mean_distance * mean_distance * ((double)num_inliers) / | |
| ((double)num_inliers - 1.0); | |
| if ((num_inliers > max_inliers) || | |
| (num_inliers == max_inliers && variance < best_variance)) { | |
| best_variance = variance; | |
| max_inliers = num_inliers; | |
| memcpy(best_params, params, paramdim * sizeof(*best_params)); | |
| memcpy(best_inlier_set1, inlier_set1, | |
| num_inliers * 2 * sizeof(*best_inlier_set1)); | |
| memcpy(best_inlier_set2, inlier_set2, | |
| num_inliers * 2 * sizeof(*best_inlier_set2)); | |
| memcpy(best_inlier_mask, inlier_mask, | |
| npoints * sizeof(*best_inlier_mask)); | |
| assert(npoints > 0); | |
| fracinliers = (double)num_inliers / (double)npoints; | |
| pNoOutliers = 1 - pow(fracinliers, minpts); | |
| pNoOutliers = fmax(EPS, pNoOutliers); | |
| pNoOutliers = fmin(1 - EPS, pNoOutliers); | |
| assert(fabs(1.0 - pNoOutliers) > 0.00001); | |
| temp = (int)(log(1.0 - PROBABILITY_REQUIRED) / log(pNoOutliers)); | |
| if (temp > 0 && temp < N) { | |
| N = AOMMAX(temp, MIN_TRIALS); | |
| } | |
| } | |
| } | |
| trial_count++; | |
| } | |
| find_transformation(max_inliers, best_inlier_set1, best_inlier_set2, | |
| best_params); | |
| if (normalize && denormalize) { | |
| denormalize(best_params, T1, T2); | |
| } | |
| *number_of_inliers = max_inliers; | |
| finish_ransac: | |
| aom_free(best_inlier_set1); | |
| aom_free(best_inlier_set2); | |
| aom_free(inlier_set1); | |
| aom_free(inlier_set2); | |
| aom_free(corners1); | |
| aom_free(corners2); | |
| aom_free(image1_coord); | |
| aom_free(inlier_mask); | |
| 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 is_degenerate_homography(double *p) { | |
| return is_collinear3(p, p + 2, p + 4) || is_collinear3(p, p + 2, p + 6) || | |
| is_collinear3(p, p + 4, p + 6) || is_collinear3(p + 2, p + 4, p + 6); | |
| } | |
| int ransac_translation(double *matched_points, int npoints, | |
| int *number_of_inliers, int *best_inlier_mask, | |
| double *best_params) { | |
| return ransac(matched_points, npoints, number_of_inliers, best_inlier_mask, | |
| best_params, 3, 2, is_degenerate_translation, | |
| NULL, // normalize_homography, | |
| NULL, // denormalize_rotzoom, | |
| find_translation, project_points_double_translation); | |
| } | |
| int ransac_rotzoom(double *matched_points, int npoints, int *number_of_inliers, | |
| int *best_inlier_mask, double *best_params) { | |
| return ransac(matched_points, npoints, number_of_inliers, best_inlier_mask, | |
| best_params, 3, 4, is_degenerate_affine, | |
| NULL, // normalize_homography, | |
| NULL, // denormalize_rotzoom, | |
| find_rotzoom, project_points_double_rotzoom); | |
| } | |
| int ransac_affine(double *matched_points, int npoints, int *number_of_inliers, | |
| int *best_inlier_mask, double *best_params) { | |
| return ransac(matched_points, npoints, number_of_inliers, best_inlier_mask, | |
| best_params, 3, 6, is_degenerate_affine, | |
| NULL, // normalize_homography, | |
| NULL, // denormalize_affine, | |
| find_affine, project_points_double_affine); | |
| } | |
| int ransac_homography(double *matched_points, int npoints, | |
| int *number_of_inliers, int *best_inlier_mask, | |
| double *best_params) { | |
| const int result = | |
| ransac(matched_points, npoints, number_of_inliers, best_inlier_mask, | |
| best_params, 4, 8, is_degenerate_homography, | |
| NULL, // normalize_homography, | |
| NULL, // denormalize_homography, | |
| find_homography, project_points_double_homography); | |
| if (!result) { | |
| // normalize so that H33 = 1 | |
| int i; | |
| const double m = 1.0 / best_params[8]; | |
| assert(fabs(best_params[8]) > 0.00001); | |
| for (i = 0; i < 8; ++i) best_params[i] *= m; | |
| best_params[8] = 1.0; | |
| } | |
| return result; | |
| } |