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Automatic Facial Expression Recognition—A Circumcenter–Incenter–Centroid (CIC) Trio Feature-Induced Approach

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Abstract

Facial expression is directly related to the changes in the shape of a face. The Active Appearance Model (AAM) can be used to determine the geometrical position of basic components by earmarking landmark points. The landmark points which are congruent upon the basic facial expressions are considered for the generation of triangle set encompassing the face. In this context, the area of the triangle formed by connecting the Circumcenter, Incenter, and Centroid is considered as the key shape descriptor. This novel feature is learned with Multi-Layer Perceptron (MLP) for the classification of expressions in six atomic classes viz Anger, Disgust, Fear, Happiness, Sadness, and Surprise. The proposed system is tested on four well-known benchmark databases viz. I. The Extended Cohn–Kanade (CK+) II. Japanese Female Facial Expression (JAFFE) III. Multimedia Imaging (MMI) and, IV. Multimedia Understanding Group (MUG) database. Overwhelming impressive results on these four databases confirm the effectiveness and efficiency of our proposed method.

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Funding

This research is funded by UGC and Council Of Scientific And Industrial Research (CSIR), Grant no [UGC-Ref. No.: 3437/(OBC)(NET-JAN 2017)].

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Authors and Affiliations

  1. Department of Computer and System Sciences, Visva-Bharati University, Santiniketan, 731235, India

    Avishek Nandi, Paramartha Dutta & Md Nasir

Authors
  1. Avishek Nandi
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  2. Paramartha Dutta
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  3. Md Nasir
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Corresponding author

Correspondence to Avishek Nandi.

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Conflict of interest

The MUG database is provided by Dr. A. Delopoulos and the MUG database is provided by Prof. Maja Pantic. Author Avishek Nandi thanks the University Grant Commission (UGC), India for providing NET-JRF fellowship (UGC-Ref. No.: 3437/(OBC)(NET-JAN 2017)) for this research. Author Md Nasir thanks the Department of Science and Technology, Govt. of India for providing the DST-INSPIRE fellowship for conducting this research. Author Paramartha Dutta is a Senior Professor at Visva-Bharati University.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Thanks to University Grant Commission (UGC), India for providing NET-JRF fellowship to Avishek Nandi for conduction this research (UGC-Ref. No.: 3437/(OBC)(NET-JAN 2017)), The MUG database is provided by Dr. A. Delopoulos and the MUG database are provided by Prof. Maja Pantic.

This article is part of the topical collection “Next-Generation Digital Transformation through Intelligent Computing” guest edited by PN Suganthan, Paramartha Dutta, Jyotsna Kumar Mandal and Somnath Mukhopadhyay.

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Nandi, A., Dutta, P. & Nasir, M. Automatic Facial Expression Recognition—A Circumcenter–Incenter–Centroid (CIC) Trio Feature-Induced Approach. SN COMPUT. SCI. 3, 8 (2022). https://doi.org/10.1007/s42979-021-00868-2

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