1 Introduction  
2 Holistic methods  
2.1 Active Appearance Model  
2.2 Fitting algorithms  
2.3 Other extensions  
3 Constrained local methods  
3.1 Problem formulation  
3.2 Local appearance model  
3.3 Face shape models  
3.4 Landmark point detection via optimization  
4 Regression-based methods  
4.1 Direct regression methods  
4.2 Cascaded regression methods  
4.3 Deep learning based methods  
4.4 Discussion: regression-based methods  
5 Discussions: relationships among methods in three major categories  
6 Facial landmark detection “in-the-wild”  
6.1 Head Poses  
6.2 Occlusion  
6.3 Facial expression  
7 Related topics  
7.1 Face detection for facial landmark detection  
7.2 Facial landmark tracking  
7.3 3D facial landmark detection  
8 Databases and evaluations  
8.1 Landmark annotations  
8.2 Databases  
8.3 Evaluation and discussion  
8.4 Software  
9 Conclusion