Optical Flow Based Expression Suppression in Video
Jesse Brizzi, Dmitry B. Goldgof, Sudeep Sarkar, Matthew Shreve · 2014
In this paper we propose a novel method for suppressing facial expressions in video sequences based on analysis of apparent strain in the face. The proposed method performs continuous optical strain analysis on a target face for all frames in a video. This analysis is used in conjunction with strain maps for every frame to counteract the elastic deformation of the facial tissue and keep the expression neutral. The method is capable of suppressing out all expression types without the need of training for specific expressions and is demonstrated on a publicly available data set. In addition, we test our method using publicly available expression (smile) recognition program that is included with OpenCV to quantify the suppression results. Our method shows an average reduction of expression detection confidence, the confidence of an expression present in a single frame, of nearly 90%.