# A Dynamic 3D Spontaneous Micro-expression Database: Establishment and Evaluation

arXiv: https://arxiv.org/abs/2108.00166 · HTML: https://mlsanity.com/paper/2108.00166/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 73 references that are in the map.
- First posted on arXiv 31 Jul 2021.

## Builds on (most cited first, 14 of 14)

- [OFF-ApexNet on Micro-expression Recognition System](https://mlsanity.com/paper/1805.08699/) (2018)
- [Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition](https://mlsanity.com/paper/1902.03634/) (2019)
- [Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods](https://mlsanity.com/paper/1511.00423/) (2015)
- [Less is More: Micro-expression Recognition from Video using Apex Frame](https://mlsanity.com/paper/1606.01721/) (2016)
- [Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition](https://mlsanity.com/paper/1805.08417/) (2018)
- [Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions](https://mlsanity.com/paper/1901.04656/) (2019)
- [LEARNet Dynamic Imaging Network for Micro Expression Recognition](https://mlsanity.com/paper/1904.09410/) (2019)
- [Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks](https://mlsanity.com/paper/1904.01390/) (2019)
- [A Survey of Automatic Facial Micro-expression Analysis: Databases, Methods and Challenges](https://mlsanity.com/paper/1806.05781/) (2018)
- [Objective Classes for Micro-Facial Expression Recognition](https://mlsanity.com/paper/1708.07549/) (2017)
- [A Review on Facial Micro-Expressions Analysis: Datasets, Features and Metrics](https://mlsanity.com/paper/1805.02397/) (2018)
- [ICE-GAN: Identity-aware and Capsule-Enhanced GAN with Graph-based Reasoning for Micro-Expression Recognition and Synthesis](https://mlsanity.com/paper/2005.04370/) (2020)
- [Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition](https://mlsanity.com/paper/1907.09160/) (2019)
- [Towards Reading Beyond Faces for Sparsity-Aware 4D Affect Recognition](https://mlsanity.com/paper/2002.03157/) (2020)

## Abstract (arXiv)

Micro-expressions are spontaneous, unconscious facial movements that show people's true inner emotions and have great potential in related fields of psychological testing. Since the face is a 3D deformation object, the occurrence of an expression can arouse spatial deformation of the face, but limited by the available databases are 2D videos, lacking the description of 3D spatial information of micro-expressions. Therefore, we proposed a new micro-expression database containing 2D video sequences and 3D point clouds sequences. The database includes 373 micro-expressions sequences, and these samples were classified using the objective method based on facial action coding system, as well as the non-objective method that combines video contents and participants' self-reports. We extracted 2D and 3D features using the local binary patterns on three orthogonal planes (LBP-TOP) and curvature algorithms, respectively, and evaluated the classification accuracies of these two features and their fusion results with leave-one-subject-out (LOSO) and 10-fold cross-validation. Further, we performed various neural network algorithms for database classification, the results show that classification accuracies are improved by fusing 3D features than using only 2D features. The database offers original and cropped micro-expression samples, which will facilitate the exploration and research on 3D Spatio-temporal features of micro-expressions.