Survey on Emotion Recognition through Posture Detection and the possibility of its application in Virtual Reality
This survey synthesizes existing research on emotion recognition via posture detection, with potential applications in virtual reality, but it is incremental as it does not introduce new methods.
The survey reviewed 19 papers on emotion recognition using posture detection, finding that multimodal approaches achieved the highest accuracy.
A survey is presented focused on using pose estimation techniques in Emotional recognition using various technologies normal cameras, and depth cameras for real-time, and the potential use of VR and inputs including images, videos, and 3-dimensional poses described in vector space. We discussed 19 research papers collected from selected journals and databases highlighting their methodology, classification algorithm, and the used datasets that relate to emotion recognition and pose estimation. A benchmark has been made according to their accuracy as it was the most common performance measurement metric used. We concluded that the multimodal Approaches overall made the best accuracy and then we mentioned futuristic concerns that can improve the development of this research topic.