# Unifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis

arXiv: https://arxiv.org/abs/1606.00822 · HTML: https://mlsanity.com/paper/1606.00822/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Jun 2016.

## Built on by (most cited first, 1 of 1)

- [Can we truly transfer an actor's genuine happiness to avatars? An investigation into virtual, real, posed and spontaneous faces](https://mlsanity.com/paper/2312.02128/) (2023)

## Abstract (arXiv)

Previous approaches to model and analyze facial expression analysis use three different techniques: facial action units, geometric features and graph based modelling. However, previous approaches have treated these technique separately. There is an interrelationship between these techniques. The facial expression analysis is significantly improved by utilizing these mappings between major geometric features involved in facial expressions and the subset of facial action units whose presence or absence are unique to a facial expression. This paper combines dimension reduction techniques and image classification with search space pruning achieved by this unique subset of facial action units to significantly prune the search space. The performance results on the publicly facial expression database shows an improvement in performance by 70% over time while maintaining the emotion recognition correctness.