Facial Expression Analysis and Estimation Based on Facial Salient Points and Action Unit (AUs)

Abstract

Humans use their facial expressions as one of the most effective, quick, and natural ways to convey their feelings and intentions to others. In this research, presents the analyses of human facial structure along with its components using Facial Action Units (AUs) and Geometric structures for identifying human facial expressions. The approach considers facial components such as Nose, Mouth, eyes and eye brows for FER. Nostril contours such as left lower tip, right lower tip, and centre tip are considered as salient points of Nose. Various salient points for Mouth are extracted from the left and right end point, upper and lower lip mid points along with curve. These salient points are extracted for all facial expression of the same subject considering neutral face as reference. The Geometric structure for neutral face is mapped along with other facial expression faces. The deformation is estimated using the Euclidean distance. The classification algorithms such as LibSVM, MLP, RF has achieved classification accuracy of 86.56% on an average. The findings of the experiments show that the extraction of picture characteristics is more efficient in terms of computing and gives promising outcomes.