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Merge pull request #250 from Lydorn/patch-1

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Update LandmarkDetectorUtils.cpp
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Tadas Baltrusaitis 2017-09-19 10:19:43 +01:00 committed by GitHub
commit c6a26861e6
1 changed files with 6 additions and 6 deletions
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lib/local/LandmarkDetector/src/LandmarkDetectorUtils.cpp
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@ -14,20 +14,20 @@
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
@ -1443,8 +1443,8 @@ bool DetectSingleFaceHOG(cv::Rect_<double>& o_region, const cv::Mat_<uchar>& int
if(use_preferred)
{
dist = sqrt((preference.x - (face_detections[0].width/2 + face_detections[0].x)) * (preference.x - (face_detections[0].width/2 + face_detections[0].x)) +
(preference.y - (face_detections[0].height/2 + face_detections[0].y)) * (preference.y - (face_detections[0].height/2 + face_detections[0].y)));
dist = sqrt((preference.x - (face_detections[i].width/2 + face_detections[i].x)) * (preference.x - (face_detections[i].width/2 + face_detections[i].x)) +
(preference.y - (face_detections[i].height/2 + face_detections[i].y)) * (preference.y - (face_detections[i].height/2 + face_detections[i].y)));
better = dist < best_so_far;
}
else