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Four papers in Face and Gesture 2017 on Facial Landmark & Expression Detection and Suicidal Ideation.

March 20, 2017

Members of the MultiComp Lab had 4 papers accepted at Face and Gesture 2017 (FG’17, http://www.fg2017.org/).

“Investigating Facial Behavior Indicators of Suicidal Ideation” (Laksana et. al.) explores how smiling, frowning, eyebrow raising, and head motion behaviors correlate with suiciadal tendencies.

“Local-Global Landmark Confidences for Face Recognition”  (Kim et. al.) fuse local confidence based on local predictors of each facial landmark, and global confidence based on a 3D rendered face model to improve the quality of Face Recognition.

“Constrained Ensemble Initialization for Facial Landmark Tracking in Video” (Li et. al.) describe a novel initialization procedure that can help with cascaded regression based facial landmark detection and tracking in videos

“Curriculum Learning for Facial Expression Recognition”  (Gui et. al.) present a novel learning technique for deep learning methods that leads to better generalization for emotion recognition from facial expressions.