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-rw-r--r--third_party/aom/av1/encoder/ransac.c603
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diff --git a/third_party/aom/av1/encoder/ransac.c b/third_party/aom/av1/encoder/ransac.c
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+++ b/third_party/aom/av1/encoder/ransac.c
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+/*
+ * 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 <memory.h>
+#include <math.h>
+#include <time.h>
+#include <stdio.h>
+#include <stdlib.h>
+#include <assert.h>
+
+#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(&current_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(&current_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(&current_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);
+}
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