Micro Expression Recognition Using Delaunay Triangulation and Voronoi Tessellation

Abstract

Facial Expression Recognition is a visual cue used for conveying emotions and intentions between human beings. The micro-expressions (MEs) are not visible to the human eye, making it challenging to capture the minute changes in the facial areas as the expressions change. As a result, automating the detection of ME is a challenging task. This work utilizes Delaunay Triangulation and Voronoi Diagram properties to segment Region of Interest (ROI) based on Action Unit indexes. The ROI-based feature extraction aided in improving the performance of the Micro-Expression Recognition (MER) system. The Cross-Database Evaluation (CDE) and Holdout Database Evaluation (HDE) are performed on three publicly available datasets CASMEII, SAMM, and SMIC (HS). The proposed approach resulted in an improved Unweighted Average Recall (UAR) and Unweighted F1 (UF1) scores by 6.09% and 4.36%, respectively. The results obtained with CDE and HDE demonstrate that the proposed model is robust compared to earlier studies.

KEYWORDS:

• Action Units (AU)
• Delaunay triangulation
• Ensemble model
• Geometric feature
• Micro-expression recognition (MER)
• Texture feature
• Voronoi diagram

ACKNOWLEDGEMENTS

Conceptualization: Rashmi Adyapady R., Annappa B.; Methodology: Rashmi Adyapady R.; Formal analysis and investigation: Rashmi Adyapady R.; Writing – original draft preparation: Rashmi Adyapady R.; Writing – review and editing: Annappa B.; Supervision: Annappa B.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Rashmi Adyapady R.

Rashmi Adyapady R received an MTech degree in the Department of Computer Science and Engineering from NMAM Institute of Technology, Nitte, Karkala in the year 2014. Her areas of interest are human- computer interaction, machine learning, and deep learning. She is currently pursuing PhD degree in the Department of Computer Science and Engineering at National Institute of Technology Karnataka, Surathkal, Mangalore, India.

B. Annappa

B Annappa is currently serving as a professor at the Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore, India. He has more than 25 years of experience in teaching and research. He holds PhD and MTech in computer science and engineering from National Institute of Technology Karnataka, Surathkal and BE in computer science and engineering from Govt BDT College of Engineering, Davangere affiliated to Mysore University, Karnataka. He is a Fellow of Institution of Engineers and a Senior member of IEEE and ACM. He is a Life member of the Computer Society of India, Indian Society of Technical Education, Cloud Computing Innovation Council of India, and Advanced Computing and Communications Society. His research interests include cloud computing, big data analytics, distributed computing, software engineering, and process mining. He has published more than 100 research papers in international conferences and journals. He was the organizing Chair of International conference ADCONS-2013, and he is one of the General Chair of DISCOVER’19. He is in the technical program committee of many international conferences and reviewer of journals. He was the Chair of the IEEE Computer Society Chapter India Council (2017–2018) and was the Chair of the IEEE Mangalore subsection during 2018. Email: [email protected]