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Facial Landmark Detection

Facial expression is a rich source of information which provides an important communication channel for human interaction. People use them to reveal intent, display affection, and express emotion. Automated tracking and analysis of such visual cues would greatly benefit human-computer interaction. A crucial initial step in many affect sensing, face recognition, and human behavior understanding systems is the detection of certain facial feature points such as eyebrows, corners of eyes, and lips.

While facial landmark detection algorithms have seen considerable progress over the recent years, they still struggle under occlusion, in adverse lighting conditions and the presence of extreme pose variations. Our work specifically focuses on addressing such challenging scenarios using various computer vision and machine learning techniques.

Publications

I. Masi, W. AbdAlmageed, F. Chan, J. Choi, S. Harel, J. Kim, K. Kim, J. Leksut, S. Rawls, Y. Wu, T. Hassner, G. Medioni, L.-P. Morency, P. Natarajan, R. Nevatia. Learning Pose-Aware Models for Pose-Invariant Face Recognition in the Wild. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

K. Kim, F.-J. Chang, J. Choi, L.-P. Morency, R. Nevatia and G. Medioni. Local-Global Landmark Confidences for Face Recognition. In Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition (FG), 2017

Y. Li, T. Baltrusaitis and L.-P. Morency. Constrained Ensemble Initialization for Facial Landmark Tracking in Video. In Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition (FG), 2017

K. Kim, T. Baltrusaitis, A. Zadeh, L.-P. Morency and G. Medioni, Holistically Constrained Local Model: Going Beyond Frontal Poses for Facial Landmark Detection, In Proceedings of the British Machine Vision Conference (BMVC), 2016

T. BaltruĊĦaitis, P. Robinson and L.-P. Morency, OpenFace: An Open Source Facial Behavior Analysis Toolkit, In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), 2016

S. Ghosh, E. Laksana, S. Scherer, and L.-P. Morency, A Multi-label Convolutional Neural Network Approach to Cross-Domain Action Unit Detection. In Proceedings of International Conference on Affective Computing and Intelligent Interaction (ACII), 2015

M. Khademi and L.-P. Morency, Relative Facial Action Unit Detection. In Proceedings of the IEEE Winter conference on Applications of Computer Vision (WACV), 2014

T. Baltrusaitis, P. Robinson and L.-P. Morency. Constrained Local Neural Fields for Robust Facial Landmark Detection in the Wild. ICCV Workshop on 300 Faces in the Wild, 2013

T.Baltrusaitis, P. Robinson and L.-P. Morency. 3D Constrained Local Model for Rigid and Non-Rigid Facial Tracking. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012

G. Stratou, A. Ghosh, P. Debevec and L.-P. Morency. Effect of Illumination on Automatic Expression Recognition: A Novel 3D Relightable Facial Database. In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2011