Advances of Science and Technology. 7th EAI International Conference, ICAST 2019, Bahir Dar, Ethiopia, August 2–4, 2019, Proceedings

Research Article

Basic Facial Expressions Analysis on a 3D Model: Based on Action Units and the Nose Tip

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  • @INPROCEEDINGS{10.1007/978-3-030-43690-2_32,
        author={Meareg Hailemariam},
        title={Basic Facial Expressions Analysis on a 3D Model: Based on Action Units and the Nose Tip},
        proceedings={Advances of Science and Technology. 7th EAI International Conference, ICAST 2019, Bahir Dar, Ethiopia, August 2--4, 2019, Proceedings},
        proceedings_a={ICAST},
        year={2020},
        month={6},
        keywords={3D facial expressions Facial expression analysis FACS Action Units Blendshapes},
        doi={10.1007/978-3-030-43690-2_32}
    }
    
  • Meareg Hailemariam
    Year: 2020
    Basic Facial Expressions Analysis on a 3D Model: Based on Action Units and the Nose Tip
    ICAST
    Springer
    DOI: 10.1007/978-3-030-43690-2_32
Meareg Hailemariam1,*
  • 1: Addis Ababa University
*Contact email: meareg.abreha@aau.edu.et

Abstract

Facial expressions play a significant role in conveying emotions with a widespread use across diverse cultures and societies globally. In particular, the expressions anger, sadness, fear, disgust, surprise, happiness and also neutral are considered universal. 2D and 3D avatar models are used to simulate facial expressions and have different applications in many domains. In this work, we consider a 3D model with facial expressions as a platform to analyze the basic set of expressions. We considered direction weighted intensity values of the FACS Action Units (i.e., also referred here as shape keys) relative to the nose tip, serving as a reference point, to generate direction weighted score for each target expression. The scores also give numerical validations for the repeated correlations indicated between a specific set of expressions (i.e., anger vs. sadness, and fear vs. disgust) in other research works that focus on developing techniques for facial expressions recognition and classification. In addition, the normal distribution of these seven expressions was depicted and gave a close to bell-curve shape which is an indication of a common phenomenon in nature.