Imaging and characterization of facial strain in long video sequences

Abstract

This paper presents a method for computing strain images of a deformable object in a video sequence. The method includes two steps: in the first step, motion data between a pair of video frames is generated using a robust optical flow algorithm. In the second step, a strain image is computed by applying a gradient filter to the motion data. The efficacy of the method was demonstrated using 30 video sequences that captured human facial expressions under different lighting conditions. Several key factors and their impact on the quality of strain images were also discussed.