# Real-time emotion recognition for gaming using deep convolutional network features

arXiv: https://arxiv.org/abs/1408.3750 · HTML: https://mlsanity.com/paper/1408.3750/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Aug 2014.

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

- [Facial Emotion Recognition in VR Games](https://mlsanity.com/paper/2312.06925/) (2023)

## Abstract (arXiv)

The goal of the present study is to explore the application of deep convolutional network features to emotion recognition. Results indicate that they perform similarly to other published models at a best recognition rate of 94.4%, and do so with a single still image rather than a video stream. An implementation of an affective feedback game is also described, where a classifier using these features tracks the facial expressions of a player in real-time.