370 lines
13 KiB
C
370 lines
13 KiB
C
/*
|
|
* (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;
|
|
}
|