Refactored videostab module. Added normalization into motion estimators.
This commit is contained in:
parent
258afe7cc2
commit
9d871abd32
@ -66,8 +66,7 @@ enum MotionModel
|
||||
};
|
||||
|
||||
CV_EXPORTS Mat estimateGlobalMotionLeastSquares(
|
||||
const std::vector<Point2f> &points0, const std::vector<Point2f> &points1,
|
||||
int model = AFFINE, float *rmse = 0);
|
||||
int npoints, Point2f *points0, Point2f *points1, int model = AFFINE, float *rmse = 0);
|
||||
|
||||
struct CV_EXPORTS RansacParams
|
||||
{
|
||||
@ -80,16 +79,24 @@ struct CV_EXPORTS RansacParams
|
||||
RansacParams(int size, float thresh, float eps, float prob)
|
||||
: size(size), thresh(thresh), eps(eps), prob(prob) {}
|
||||
|
||||
static RansacParams translation2dMotionStd() { return RansacParams(1, 0.5f, 0.5f, 0.99f); }
|
||||
static RansacParams translationAndScale2dMotionStd() { return RansacParams(2, 0.5f, 0.5f, 0.99f); }
|
||||
static RansacParams linearSimilarity2dMotionStd() { return RansacParams(2, 0.5f, 0.5f, 0.99f); }
|
||||
static RansacParams affine2dMotionStd() { return RansacParams(3, 0.5f, 0.5f, 0.99f); }
|
||||
static RansacParams homography2dMotionStd() { return RansacParams(4, 0.5f, 0.5f, 0.99f); }
|
||||
static RansacParams default2dMotion(MotionModel model)
|
||||
{
|
||||
CV_Assert(model < UNKNOWN);
|
||||
if (model == TRANSLATION)
|
||||
return RansacParams(1, 0.5f, 0.5f, 0.99f);
|
||||
if (model == TRANSLATION_AND_SCALE)
|
||||
return RansacParams(2, 0.5f, 0.5f, 0.99f);
|
||||
if (model == LINEAR_SIMILARITY)
|
||||
return RansacParams(2, 0.5f, 0.5f, 0.99f);
|
||||
if (model == AFFINE)
|
||||
return RansacParams(3, 0.5f, 0.5f, 0.99f);
|
||||
return RansacParams(4, 0.5f, 0.5f, 0.99f);
|
||||
}
|
||||
};
|
||||
|
||||
CV_EXPORTS Mat estimateGlobalMotionRobust(
|
||||
const std::vector<Point2f> &points0, const std::vector<Point2f> &points1,
|
||||
int model = AFFINE, const RansacParams ¶ms = RansacParams::affine2dMotionStd(),
|
||||
int model = AFFINE, const RansacParams ¶ms = RansacParams::default2dMotion(AFFINE),
|
||||
float *rmse = 0, int *ninliers = 0);
|
||||
|
||||
class CV_EXPORTS GlobalMotionEstimatorBase
|
||||
|
@ -51,8 +51,44 @@ namespace cv
|
||||
namespace videostab
|
||||
{
|
||||
|
||||
// does isotropic normalization
|
||||
static Mat normalizePoints(int npoints, Point2f *points)
|
||||
{
|
||||
float cx = 0.f, cy = 0.f;
|
||||
for (int i = 0; i < npoints; ++i)
|
||||
{
|
||||
cx += points[i].x;
|
||||
cy += points[i].y;
|
||||
}
|
||||
cx /= npoints;
|
||||
cy /= npoints;
|
||||
|
||||
float d = 0.f;
|
||||
for (int i = 0; i < npoints; ++i)
|
||||
{
|
||||
points[i].x -= cx;
|
||||
points[i].y -= cy;
|
||||
d += sqrt(sqr(points[i].x) + sqr(points[i].y));
|
||||
}
|
||||
d /= npoints;
|
||||
|
||||
float s = sqrt(2.f) / d;
|
||||
for (int i = 0; i < npoints; ++i)
|
||||
{
|
||||
points[i].x *= s;
|
||||
points[i].y *= s;
|
||||
}
|
||||
|
||||
Mat_<float> T = Mat::eye(3, 3, CV_32F);
|
||||
T(0,0) = T(1,1) = s;
|
||||
T(0,2) = -cx*s;
|
||||
T(1,2) = -cy*s;
|
||||
return T;
|
||||
}
|
||||
|
||||
|
||||
static Mat estimateGlobMotionLeastSquaresTranslation(
|
||||
int npoints, const Point2f *points0, const Point2f *points1, float *rmse)
|
||||
int npoints, Point2f *points0, Point2f *points1, float *rmse)
|
||||
{
|
||||
Mat_<float> M = Mat::eye(3, 3, CV_32F);
|
||||
for (int i = 0; i < npoints; ++i)
|
||||
@ -62,6 +98,7 @@ static Mat estimateGlobMotionLeastSquaresTranslation(
|
||||
}
|
||||
M(0,2) /= npoints;
|
||||
M(1,2) /= npoints;
|
||||
|
||||
if (rmse)
|
||||
{
|
||||
*rmse = 0;
|
||||
@ -70,13 +107,17 @@ static Mat estimateGlobMotionLeastSquaresTranslation(
|
||||
sqr(points1[i].y - points0[i].y - M(1,2));
|
||||
*rmse = sqrt(*rmse / npoints);
|
||||
}
|
||||
|
||||
return M;
|
||||
}
|
||||
|
||||
|
||||
static Mat estimateGlobMotionLeastSquaresTranslationAndScale(
|
||||
int npoints, const Point2f *points0, const Point2f *points1, float *rmse)
|
||||
int npoints, Point2f *points0, Point2f *points1, float *rmse)
|
||||
{
|
||||
Mat_<float> T0 = normalizePoints(npoints, points0);
|
||||
Mat_<float> T1 = normalizePoints(npoints, points1);
|
||||
|
||||
Mat_<float> A(2*npoints, 3), b(2*npoints, 1);
|
||||
float *a0, *a1;
|
||||
Point2f p0, p1;
|
||||
@ -103,13 +144,17 @@ static Mat estimateGlobMotionLeastSquaresTranslationAndScale(
|
||||
M(0,0) = M(1,1) = sol(0,0);
|
||||
M(0,2) = sol(1,0);
|
||||
M(1,2) = sol(2,0);
|
||||
return M;
|
||||
|
||||
return T1.inv() * M * T0;
|
||||
}
|
||||
|
||||
|
||||
static Mat estimateGlobMotionLeastSquaresLinearSimilarity(
|
||||
int npoints, const Point2f *points0, const Point2f *points1, float *rmse)
|
||||
int npoints, Point2f *points0, Point2f *points1, float *rmse)
|
||||
{
|
||||
Mat_<float> T0 = normalizePoints(npoints, points0);
|
||||
Mat_<float> T1 = normalizePoints(npoints, points1);
|
||||
|
||||
Mat_<float> A(2*npoints, 4), b(2*npoints, 1);
|
||||
float *a0, *a1;
|
||||
Point2f p0, p1;
|
||||
@ -138,13 +183,17 @@ static Mat estimateGlobMotionLeastSquaresLinearSimilarity(
|
||||
M(1,0) = -sol(1,0);
|
||||
M(0,2) = sol(2,0);
|
||||
M(1,2) = sol(3,0);
|
||||
return M;
|
||||
|
||||
return T1.inv() * M * T0;
|
||||
}
|
||||
|
||||
|
||||
static Mat estimateGlobMotionLeastSquaresAffine(
|
||||
int npoints, const Point2f *points0, const Point2f *points1, float *rmse)
|
||||
int npoints, Point2f *points0, Point2f *points1, float *rmse)
|
||||
{
|
||||
Mat_<float> T0 = normalizePoints(npoints, points0);
|
||||
Mat_<float> T1 = normalizePoints(npoints, points1);
|
||||
|
||||
Mat_<float> A(2*npoints, 6), b(2*npoints, 1);
|
||||
float *a0, *a1;
|
||||
Point2f p0, p1;
|
||||
@ -172,24 +221,22 @@ static Mat estimateGlobMotionLeastSquaresAffine(
|
||||
for (int j = 0; j < 3; ++j, ++k)
|
||||
M(i,j) = sol(k,0);
|
||||
|
||||
return M;
|
||||
return T1.inv() * M * T0;
|
||||
}
|
||||
|
||||
|
||||
Mat estimateGlobalMotionLeastSquares(
|
||||
const vector<Point2f> &points0, const vector<Point2f> &points1, int model, float *rmse)
|
||||
int npoints, Point2f *points0, Point2f *points1, int model, float *rmse)
|
||||
{
|
||||
CV_Assert(model <= AFFINE);
|
||||
CV_Assert(points0.size() == points1.size());
|
||||
|
||||
typedef Mat (*Impl)(int, const Point2f*, const Point2f*, float*);
|
||||
typedef Mat (*Impl)(int, Point2f*, Point2f*, float*);
|
||||
static Impl impls[] = { estimateGlobMotionLeastSquaresTranslation,
|
||||
estimateGlobMotionLeastSquaresTranslationAndScale,
|
||||
estimateGlobMotionLeastSquaresLinearSimilarity,
|
||||
estimateGlobMotionLeastSquaresAffine };
|
||||
|
||||
int npoints = static_cast<int>(points0.size());
|
||||
return impls[model](npoints, &points0[0], &points1[0], rmse);
|
||||
return impls[model](npoints, points0, points1, rmse);
|
||||
}
|
||||
|
||||
|
||||
@ -200,22 +247,22 @@ Mat estimateGlobalMotionRobust(
|
||||
CV_Assert(model <= AFFINE);
|
||||
CV_Assert(points0.size() == points1.size());
|
||||
|
||||
typedef Mat (*Impl)(int, const Point2f*, const Point2f*, float*);
|
||||
static Impl impls[] = { estimateGlobMotionLeastSquaresTranslation,
|
||||
estimateGlobMotionLeastSquaresTranslationAndScale,
|
||||
estimateGlobMotionLeastSquaresLinearSimilarity,
|
||||
estimateGlobMotionLeastSquaresAffine };
|
||||
|
||||
const int npoints = static_cast<int>(points0.size());
|
||||
const int niters = static_cast<int>(ceil(log(1 - params.prob) /
|
||||
log(1 - pow(1 - params.eps, params.size))));
|
||||
|
||||
RNG rng(0);
|
||||
// current hypothesis
|
||||
vector<int> indices(params.size);
|
||||
vector<Point2f> subset0(params.size), subset1(params.size);
|
||||
vector<Point2f> subset0best(params.size), subset1best(params.size);
|
||||
vector<Point2f> subset0(params.size);
|
||||
vector<Point2f> subset1(params.size);
|
||||
|
||||
// best hypothesis
|
||||
vector<Point2f> subset0best(params.size);
|
||||
vector<Point2f> subset1best(params.size);
|
||||
Mat_<float> bestM;
|
||||
int ninliersMax = -1;
|
||||
|
||||
RNG rng(0);
|
||||
Point2f p0, p1;
|
||||
float x, y;
|
||||
|
||||
@ -239,7 +286,8 @@ Mat estimateGlobalMotionRobust(
|
||||
subset1[i] = points1[indices[i]];
|
||||
}
|
||||
|
||||
Mat_<float> M = impls[model](params.size, &subset0[0], &subset1[0], 0);
|
||||
Mat_<float> M = estimateGlobalMotionLeastSquares(
|
||||
params.size, &subset0[0], &subset1[0], model, 0);
|
||||
|
||||
int ninliers = 0;
|
||||
for (int i = 0; i < npoints; ++i)
|
||||
@ -260,8 +308,9 @@ Mat estimateGlobalMotionRobust(
|
||||
}
|
||||
|
||||
if (ninliersMax < params.size)
|
||||
// compute rmse
|
||||
bestM = impls[model](params.size, &subset0best[0], &subset1best[0], rmse);
|
||||
// compute RMSE
|
||||
bestM = estimateGlobalMotionLeastSquares(
|
||||
params.size, &subset0best[0], &subset1best[0], model, rmse);
|
||||
else
|
||||
{
|
||||
subset0.resize(ninliersMax);
|
||||
@ -278,7 +327,8 @@ Mat estimateGlobalMotionRobust(
|
||||
j++;
|
||||
}
|
||||
}
|
||||
bestM = impls[model](ninliersMax, &subset0[0], &subset1[0], rmse);
|
||||
bestM = estimateGlobalMotionLeastSquares(
|
||||
ninliersMax, &subset0[0], &subset1[0], model, rmse);
|
||||
}
|
||||
|
||||
if (ninliers)
|
||||
@ -332,16 +382,11 @@ PyrLkRobustMotionEstimator::PyrLkRobustMotionEstimator(MotionModel model)
|
||||
setDetector(new GoodFeaturesToTrackDetector());
|
||||
setOptFlowEstimator(new SparsePyrLkOptFlowEstimator());
|
||||
setMotionModel(model);
|
||||
if (model == TRANSLATION)
|
||||
setRansacParams(RansacParams::translation2dMotionStd());
|
||||
else if (model == TRANSLATION_AND_SCALE)
|
||||
setRansacParams(RansacParams::translationAndScale2dMotionStd());
|
||||
else if (model == LINEAR_SIMILARITY)
|
||||
setRansacParams(RansacParams::linearSimilarity2dMotionStd());
|
||||
else if (model == AFFINE)
|
||||
setRansacParams(RansacParams::affine2dMotionStd());
|
||||
else if (model == HOMOGRAPHY)
|
||||
setRansacParams(RansacParams::homography2dMotionStd());
|
||||
|
||||
RansacParams ransac = RansacParams::default2dMotion(model);
|
||||
ransac.size *= 2; // we use more points than needed, but result looks better
|
||||
setRansacParams(ransac);
|
||||
|
||||
setMaxRmse(0.5f);
|
||||
setMinInlierRatio(0.1f);
|
||||
setGridSize(Size(0,0));
|
||||
@ -362,6 +407,7 @@ Mat PyrLkRobustMotionEstimator::estimate(const Mat &frame0, const Mat &frame1, b
|
||||
keypointsPrev_.push_back(KeyPoint((x+1)*dx, (y+1)*dy, 0.f));
|
||||
}
|
||||
|
||||
// draw keypoints
|
||||
/*Mat img;
|
||||
drawKeypoints(frame0, keypointsPrev_, img);
|
||||
imshow("frame0_keypoints", img);
|
||||
@ -374,10 +420,9 @@ Mat PyrLkRobustMotionEstimator::estimate(const Mat &frame0, const Mat &frame1, b
|
||||
optFlowEstimator_->run(frame0, frame1, pointsPrev_, points_, status_, noArray());
|
||||
|
||||
size_t npoints = points_.size();
|
||||
pointsPrevGood_.clear();
|
||||
pointsPrevGood_.reserve(npoints);
|
||||
pointsGood_.clear();
|
||||
pointsGood_.reserve(npoints);
|
||||
pointsPrevGood_.clear(); pointsPrevGood_.reserve(npoints);
|
||||
pointsGood_.clear(); pointsGood_.reserve(npoints);
|
||||
|
||||
for (size_t i = 0; i < npoints; ++i)
|
||||
{
|
||||
if (status_[i])
|
||||
|
@ -338,16 +338,18 @@ void TwoPassStabilizer::runPrePassIfNecessary()
|
||||
WobbleSuppressorBase *wobbleSuppressor = static_cast<WobbleSuppressorBase*>(wobbleSuppressor_);
|
||||
doWobbleSuppression_ = dynamic_cast<NullWobbleSuppressor*>(wobbleSuppressor) == 0;
|
||||
|
||||
bool okEst;
|
||||
bool ok = true, ok2 = true;
|
||||
|
||||
while (!(frame = frameSource_->nextFrame()).empty())
|
||||
{
|
||||
if (frameCount_ > 0)
|
||||
{
|
||||
motions_.push_back(motionEstimator_->estimate(prevFrame, frame));
|
||||
motions_.push_back(motionEstimator_->estimate(prevFrame, frame, &ok));
|
||||
|
||||
if (doWobbleSuppression_)
|
||||
{
|
||||
Mat M = wobbleSuppressor_->motionEstimator()->estimate(prevFrame, frame, &okEst);
|
||||
if (okEst)
|
||||
Mat M = wobbleSuppressor_->motionEstimator()->estimate(prevFrame, frame, &ok2);
|
||||
if (ok2)
|
||||
motions2_.push_back(M);
|
||||
else
|
||||
motions2_.push_back(motions_.back());
|
||||
@ -363,7 +365,12 @@ void TwoPassStabilizer::runPrePassIfNecessary()
|
||||
prevFrame = frame;
|
||||
frameCount_++;
|
||||
|
||||
log_->print(".");
|
||||
if (ok)
|
||||
{
|
||||
if (ok2) log_->print(".");
|
||||
else log_->print("?");
|
||||
}
|
||||
else log_->print("x");
|
||||
}
|
||||
|
||||
for (int i = 0; i < radius_; ++i)
|
||||
|
@ -55,7 +55,7 @@ WobbleSuppressorBase::WobbleSuppressorBase() : motions_(0), stabilizationMotions
|
||||
{
|
||||
PyrLkRobustMotionEstimator *est = new PyrLkRobustMotionEstimator();
|
||||
est->setMotionModel(HOMOGRAPHY);
|
||||
est->setRansacParams(RansacParams::homography2dMotionStd());
|
||||
est->setRansacParams(RansacParams::default2dMotion(HOMOGRAPHY));
|
||||
setMotionEstimator(est);
|
||||
}
|
||||
|
||||
|
@ -67,6 +67,8 @@ void printHelp()
|
||||
"Arguments:\n"
|
||||
" -m, --model=(transl|transl_and_scale|linear_sim|affine|homography)\n"
|
||||
" Set motion model. The default is affine.\n"
|
||||
" --subset=(<int_number>|auto)\n"
|
||||
" Number of random samples per one motion hypothesis. The default is auto.\n"
|
||||
" --outlier-ratio=<float_number>\n"
|
||||
" Motion estimation outlier ratio hypothesis. The default is 0.5.\n"
|
||||
" --min-inlier-ratio=<float_number>\n"
|
||||
@ -116,10 +118,12 @@ void printHelp()
|
||||
" --ws-model=(transl|transl_and_scale|linear_sim|affine|homography)\n"
|
||||
" Set wobble suppression motion model (must have more DOF than motion \n"
|
||||
" estimation model). The default is homography.\n"
|
||||
" --ws-min-inlier-ratio=<float_number>\n"
|
||||
" Minimum inlier ratio to decide if estimated motion is OK. The default is 0.1.\n"
|
||||
" --ws-subset=(<int_number>|auto)\n"
|
||||
" Number of random samples per one motion hypothesis. The default is auto.\n"
|
||||
" --ws-outlier-ratio=<float_number>\n"
|
||||
" Motion estimation outlier ratio hypothesis. The default is 0.5.\n"
|
||||
" --ws-min-inlier-ratio=<float_number>\n"
|
||||
" Minimum inlier ratio to decide if estimated motion is OK. The default is 0.1.\n"
|
||||
" --ws-nkps=<int_number>\n"
|
||||
" Number of keypoints to find in each frame. The default is 1000.\n"
|
||||
" --ws-extra-kps=<int_number>\n"
|
||||
@ -147,8 +151,9 @@ int main(int argc, const char **argv)
|
||||
const char *keys =
|
||||
"{ 1 | | | | }"
|
||||
"{ m | model | affine| }"
|
||||
"{ | min-inlier-ratio | 0.1 | }"
|
||||
"{ | subset | auto | }"
|
||||
"{ | outlier-ratio | 0.5 | }"
|
||||
"{ | min-inlier-ratio | 0.1 | }"
|
||||
"{ | nkps | 1000 | }"
|
||||
"{ | extra-kps | 0 | }"
|
||||
"{ sm | save-motions | no | }"
|
||||
@ -170,8 +175,9 @@ int main(int argc, const char **argv)
|
||||
"{ ws | wobble-suppress | no | }"
|
||||
"{ | ws-period | 30 | }"
|
||||
"{ | ws-model | homography | }"
|
||||
"{ | ws-min-inlier-ratio | 0.1 | }"
|
||||
"{ | ws-subset | auto | }"
|
||||
"{ | ws-outlier-ratio | 0.5 | }"
|
||||
"{ | ws-min-inlier-ratio | 0.1 | }"
|
||||
"{ | ws-nkps | 1000 | }"
|
||||
"{ | ws-extra-kps | 0 | }"
|
||||
"{ sm2 | save-motions2 | no | }"
|
||||
@ -230,6 +236,8 @@ int main(int argc, const char **argv)
|
||||
|
||||
est->setDetector(new GoodFeaturesToTrackDetector(argi("ws-nkps")));
|
||||
RansacParams ransac = est->ransacParams();
|
||||
if (arg("ws-subset") != "auto")
|
||||
ransac.size = argi("ws-subset");
|
||||
ransac.eps = argf("ws-outlier-ratio");
|
||||
est->setRansacParams(ransac);
|
||||
est->setMinInlierRatio(argf("ws-min-inlier-ratio"));
|
||||
@ -288,6 +296,8 @@ int main(int argc, const char **argv)
|
||||
|
||||
est->setDetector(new GoodFeaturesToTrackDetector(argi("nkps")));
|
||||
RansacParams ransac = est->ransacParams();
|
||||
if (arg("subset") != "auto")
|
||||
ransac.size = argi("subset");
|
||||
ransac.eps = argf("outlier-ratio");
|
||||
est->setRansacParams(ransac);
|
||||
est->setMinInlierRatio(argf("min-inlier-ratio"));
|
||||
|
Loading…
Reference in New Issue
Block a user