1 Introduction
2 Background
2.1 Brief History of Facial Expression Analysis (FEA) under Occlusion
2.2 Methods for Representing Facial Expressions
2.3 Major Types and Characteristics of Facial Occlusion
3 Related Databases
4 Automatic Facial Expression Analysis Approaches
4.1 Feature Reconstruction Approach
4.2 Sparse Representation Approach
4.3 Sub-region based Approach
4.4 Statistical Model based Approach
4.5 3D Data based Approach
4.6 Deep Learning Approach
4.7 Summary of FEA Approaches
4.8 Top Five Benchmark Approaches
5 Effect of Occlusion on Facial Expression
5.1 Computer Vision Investigation
5.2 Human Perception Investigation
5.3 Summary of Effect of Occlusion
6 Challenges and Opportunities
6.1 Database Creation and Labeling
6.2 Occlusion Detection and System Integration
6.3 Other Features
6.4 Multiple Modalities and Deep Learning
6.5 A Few Additional Issues
7 Conclusion