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unplugged-system/external/libaom/aom_dsp/flow_estimation/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 "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(&current_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(&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) {
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(&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);
// 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(&current_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(&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) {
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(&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);
// 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;
}
}
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