/// <summary>
/// detect facial features using the given image and face coordinates
/// </summary>
/// <param name="img">image object containing the face</param>
/// <param name="face_tx">The top left x coordinate of the detected face within the image object</param>
/// <param name="face_ty">The top left y coordinate of the detected face within the image object</param>
/// <param name="face_bx">The bottom right x coordinate of the detected face within the image object</param>
/// <param name="face_by">The bottom right y coordinate of the detected face within the image object</param>
void classHumunculus::analyseFace(classimage *img, int face_tx, int face_ty, int face_bx, int face_by)
{
int x,y,c,xx,yy,w,h;
int lateral_symetry,lefteye_x,righteye_x,lefteye_y,righteye_y,mouth_y,mouth_width;
//dimensions of the face within the original image
w = face_bx - face_tx;
h = face_by - face_ty;
//dump the face region into a separate image of fixed dimensions
for (x=0;x<FACE_IMAGE_SIZE;x++)
{
xx = face_tx + ((x * w)/ FACE_IMAGE_SIZE);
for (y=0;y<FACE_IMAGE_SIZE;y++)
{
yy = face_ty + ((y * h) / FACE_IMAGE_SIZE);
for (c=0;c<3;c++)
face->image[x][y][c] = img->image[xx][yy][c];
}
}
//face->updateIntegralImage();
//detect the positions of features within the face image
detectFeatures(lateral_symetry, lefteye_x, righteye_x, lefteye_y, righteye_y, mouth_y, mouth_width);
detectKeypoints(lateral_symetry, lefteye_x, righteye_x, lefteye_y, righteye_y, mouth_y, mouth_width);
}
InitResult KltHomographyInit::addFirstFrame(FramePtr frame_ref)
{
reset();
detectFeatures(frame_ref, px_ref_, f_ref_);
if(px_ref_.size() < 100)
{
SVO_WARN_STREAM_THROTTLE(2.0, "First image has less than 100 features. Retry in more textured environment.");
return FAILURE;
}
frame_ref_ = frame_ref;
px_cur_.insert(px_cur_.begin(), px_ref_.begin(), px_ref_.end());
return SUCCESS;
}
InitResult KltHomographyInit::addFirstFrame(FramePtr frame_ref, Matrix3d orient, Vector3d pos)
{
reset();
detectFeatures(frame_ref, px_ref_, f_ref_);
if(px_ref_.size() < 100)
{
SVO_WARN_STREAM_THROTTLE(2.0, "First image has less than 100 features. Retry in more textured environment.");
return FAILURE;
}
frame_ref_ = frame_ref;
px_cur_.insert(px_cur_.begin(), px_ref_.begin(), px_ref_.end());
T_first_frame_real_scale = SE3(orient, pos);
frame_ref_->T_f_w_ = T_first_frame_real_scale;
return SUCCESS;
}
// 确保添加的第一帧检测到的特征点数大于100
InitResult Initialization::addFirstFrame(FramePtr frame_ref)
{
reset();
detectFeatures(frame_ref, px_ref_, f_ref_);
if (px_ref_.size() < 100)
{
std::cerr << "First image has less than 100 features. Retry in more textured environment." << std::endl;
return FAILURE;
}
int detect_features_num = px_ref_.size();
// 将这一帧图像做为参考帧
frame_ref_ = frame_ref;
// 先设置当前帧的特征与参考帧的特征一致
px_cur_.insert(px_cur_.begin(), px_ref_.begin(), px_ref_.end());
return SUCCESS;
}
void DetailedFaceDetector::processFrame()
{
cv::Mat frame = getMostRecentFrame();
if(frame.empty()) return;
detectFaces(frame);
//only detect features if the FaceDetector has updates!
if(hasUpdates)
{
//only detect other features if the face detector had updates
if(detectWhat > 0)
detectFeatures(frame);
//since this object disables autoNotify, do it manually now!
//this is to avoid double updates to the controllers and
//only update when necessary
notifyControllers();
}
}
