static Shape StartShapeFromDetPar(
const DetPar& detpar_roi, // in: detpar wrt the ROI
const Image& face_roi, // in
const Shape& meanshape, // in
ESTART estart) // in: use mouth etc. to posn start shape?
{
CV_Assert(estart == ESTART_RECT_ONLY ||
estart == ESTART_EYES ||
estart == ESTART_EYE_AND_MOUTH);
Shape startshape;
Shape meanshape1(meanshape);
if (estart == ESTART_EYE_AND_MOUTH && // use both eyes and mouth?
Valid(detpar_roi.mouthx) &&
Valid(detpar_roi.lex) &&
Valid(detpar_roi.rex))
{
FlipIfLeftFacing(meanshape1, detpar_roi.eyaw, face_roi.cols);
startshape = AlignMeanShapeToBothEyesAndMouth(detpar_roi, meanshape1);
FlipIfLeftFacing(startshape, detpar_roi.eyaw, face_roi.cols);
}
else if (Valid(detpar_roi.lex) && // use both eyes?
Valid(detpar_roi.rex))
{
FlipIfLeftFacing(meanshape1, detpar_roi.eyaw, face_roi.cols);
// TODO Tune the following code, what approach is best?
if (detpar_roi.eyaw == EYAW00)
startshape = AlignMeanShapeToBothEyesEstMouth(detpar_roi, meanshape1);
else
startshape = AlignMeanShapeToBothEyesNoMouth(detpar_roi, meanshape1);
FlipIfLeftFacing(startshape, detpar_roi.eyaw, face_roi.cols);
}
else if (estart == ESTART_EYE_AND_MOUTH && // use left eye and mouth?
Valid(detpar_roi.mouthx) &&
Valid(detpar_roi.lex))
{
FlipIfLeftFacing(meanshape1, detpar_roi.eyaw, face_roi.cols);
startshape = AlignMeanShapeToLeftEyeAndMouth(detpar_roi, meanshape1);
FlipIfLeftFacing(startshape, detpar_roi.eyaw, face_roi.cols);
}
else if (estart == ESTART_EYE_AND_MOUTH && // use right eye and mouth?
Valid(detpar_roi.mouthx) &&
Valid(detpar_roi.rex))
{
FlipIfLeftFacing(meanshape1, detpar_roi.eyaw, face_roi.cols);
startshape = AlignMeanShapeToRightEyeAndMouth(detpar_roi, meanshape1);
FlipIfLeftFacing(startshape, detpar_roi.eyaw, face_roi.cols);
}
else // last resort: use the face det rectangle (can't use facial features)
{
startshape =
AlignMeanShapeToFaceDetRect(detpar_roi, meanshape1,
FACERECT_SCALE_WHEN_NO_EYES, face_roi);
}
return JitterPointsAt00(startshape);
}
static Shape PinMeanShape( // align mean shape to the pinned points
const Shape& pinned, // in: at least two of these points must be set
const Shape& meanshape) // in
{
CV_Assert(pinned.rows == meanshape.rows);
int ipoint, nused = 0; // number of points used in pinned
for (ipoint = 0; ipoint < meanshape.rows; ipoint++)
if (PointUsed(pinned, ipoint))
nused++;
if (nused < 2)
Err("Need at least two pinned landmarks");
// Create an anchor shape (the pinned landmarks) and an alignment shape (the
// points in meanshape that correspond to those pinned landmarks). Do that by
// copying the used points in pinned to pinned_used, and the corresponding
// points in meanshape to meanused.
Shape pinned_used(nused, 2), mean_used(nused, 2);
int i = 0;
for (ipoint = 0; ipoint < meanshape.rows; ipoint++)
if (PointUsed(pinned, ipoint))
{
pinned_used(i, IX) = pinned(ipoint, IX);
pinned_used(i, IY) = pinned(ipoint, IY);
mean_used(i, IX) = meanshape(ipoint, IX);
mean_used(i, IY) = meanshape(ipoint, IY);
i++;
}
CV_Assert(i == nused);
// transform meanshape to pose generated by aligning mean_used to pinned_used
Shape TransformedShape(
AlignShape(meanshape, AlignmentMat(mean_used, pinned_used)));
return JitterPointsAt00(TransformedShape);
}
static Shape StartShapeFromDetPar(
const DetPar& detpar_roi, // in: detpar wrt the ROI
const Image& face_roi, // in
const Shape& meanshape, // in
ESTART estart) // in: use mouth etc. to posn start shape?
{
Shape startshape;
switch (estart)
{
case ESTART_RECT_ONLY:
startshape = EstartRectOnly(detpar_roi, face_roi, meanshape);
break;
case ESTART_EYES:
startshape = EstartEyes(detpar_roi, face_roi, meanshape);
break;
case ESTART_EYE_AND_MOUTH:
startshape = EstartEyeMouth(detpar_roi, face_roi, meanshape);
break;
default:
Err("Invalid estart %d", estart);
}
return JitterPointsAt00(startshape);
}
Shape ConformShapeToMod( // Return a copy of inshape conformed to the model
VEC& b, // io: eigvec weights, 2n x 1
const Shape& inshape, // in: the current position of the landmarks
const Shape& meanshape, // in: n x 2
const VEC& eigvals, // in: neigs x 1
const MAT& eigvecs, // in: 2n x neigs
const MAT& eigvecsi, // in: neigs x 2n, inverse of eigvecs
const double bmax, // in: for LimitB
const VEC& pointweights) // in: contribution of each point to the pose
{
Shape shape(inshape.clone());
// estimate the pose which transforms the shape into the model space
// (use the b from previous iterations of the ASM)
MAT modelshape(AsColVec(meanshape) + eigvecs * b);
modelshape = DimKeep(modelshape, shape.rows, 2); // redim back to 2 columns
const MAT pose(AlignmentMat(modelshape, shape, Buf(pointweights)));
// transform the shape into the model space
modelshape = TransformShape(shape, pose.inv(cv::DECOMP_LU));
// update shape model params b to match modelshape, then limit b
b = eigvecsi * AsColVec(modelshape - meanshape);
LimitB(b, eigvals, bmax);
// generate conformedshape from the model using the limited b
// (we generate as a column vec, then redim back to 2 columns)
const Shape conformedshape(DimKeep(eigvecs * b, shape.rows, 2));
// back to image space
return JitterPointsAt00(TransformShape(meanshape + conformedshape, pose));
}
static void StartShapeAndRoi( // we have the facerect, now get the rest
Shape& startshape, // out: the start shape we are looking for
Image& face_roi, // out: ROI around face, possibly rotated upright
DetPar& detpar_roi, // out: detpar wrt to face_roi
DetPar& detpar, // io: detpar wrt to img (has face rect on entry)
const Image& img, // in: the image (grayscale)
const vec_Mod& mods, // in: a vector of models, one for each yaw range
// (use only estart, and meanshape)
StasmCascadeClassifier cascade)
{
PossiblySetRotToZero(detpar.rot); // treat small rots as zero rots
FaceRoiAndDetPar(face_roi, detpar_roi, // get ROI around face
img, detpar, false);
DetectEyesAndMouth(detpar_roi, // use OpenCV eye and mouth detectors
face_roi, cascade);
// Some face detectors return the face rotation, some don't (in
// the call to NextFace_ just made via NextStartShapeAndRoi).
// If we don't have the rotation, then estimate it from the eye
// angle, if the eyes are available.
if (!Valid(detpar.rot)) // don't have the face rotation?
{
detpar_roi.rot = EstRotFromEyeAngle(detpar_roi);
PossiblySetRotToZero(detpar_roi.rot);
detpar.rot = detpar_roi.rot;
if (detpar.rot != 0)
{
// face is rotated: rotate ROI and re-get the eyes and mouth
// TODO: Prevent bogus OpenCV assert fail face_roi.data == img.data.
face_roi = Image(0,0);
FaceRoiAndDetPar(face_roi, detpar_roi,
img, detpar, false);
DetectEyesAndMouth(detpar_roi, // use OpenCV eye and mouth detectors
face_roi, cascade);
}
}
if (trace_g)
lprintf("%-6.6s yaw %3.0f rot %3.0f ",
EyawAsString(detpar_roi.eyaw), detpar_roi.yaw, detpar_roi.rot);
else
logprintf("%-6.6s yaw %3.0f rot %3.0f ",
EyawAsString(detpar_roi.eyaw), detpar_roi.yaw, detpar_roi.rot);
// select an ASM model based on the face's yaw
const Mod* mod = mods[ABS(EyawAsModIndex(detpar_roi.eyaw, mods))];
const ESTART estart = mod->Estart_();
CV_Assert(estart == ESTART_EYES || estart == ESTART_EYE_AND_MOUTH);
startshape = StartShapeFromDetPar(detpar_roi,
face_roi, mod->MeanShape_(), estart);
if (IsLeftFacing(detpar_roi.eyaw))
FlipImgInPlace(face_roi);
JitterPointsAt00(startshape);
}
