Gesture based fear recognition using nonperformance dataset from VR horror games

Emotion recognition is a rising trend in related fields. Existing research mainly aims at the emotion recognition based on single or multi modalities on performance datasets. However, there is little research focusing on gesture-based emotion recognition using non-performance emotional datasets. In this article, we proposed a non-performance emotional data collection scheme using VR to construct a high-quality nonperformance dataset in gesture modality with fear labels. Then we proposed an optimized algorithm for gesture-based fear recognition using BLSTM on this dataset with the accuracy of up to 71.43%. Our work could be applied in many domains such as potentially domestic violence detection and VR game evaluation.