The Analysis of Facial Feature Deformation using Optical Flow Algorithm
This work addresses facial expression recognition by quantifying deformation patterns, but it is incremental as it applies an existing method to a specific domain.
The paper analyzed facial feature deformation for different expressions using an optical flow algorithm, finding that eye and mouth deformations are significant in most expressions except happy, where cheeks and mouths dominate, with maximum magnitude of 9x10^-4 for surprise and minimum of 0.4x10^-4 for angry.
Facial features deformed according to the intended facial expression. Specific facial features are associated with specific facial expression, i.e. happy means the deformation of mouth. This paper presents the study of facial feature deformation for each facial expression by using an optical flow algorithm and segmented into three different regions of interest. The deformation of facial features shows the relation between facial the and facial expression. Based on the experiments, the deformations of eye and mouth are significant in all expressions except happy. For happy expression, cheeks and mouths are the significant regions. This work also suggests that different facial features' intensity varies in the way that they contribute to the recognition of the different facial expression intensity. The maximum magnitude across all expressions is shown by the mouth for surprise expression which is 9x10-4. While the minimum magnitude is shown by the mouth for angry expression which is 0.4x10-4.