Summary of Survey on Emotion Recognition Through Posture Detection and the Possibility Of Its Application in Virtual Reality, by Leina Elansary et al.
Survey on Emotion Recognition through Posture Detection and the possibility of its application in Virtual Reality
by Leina Elansary, Zaki Taha, Walaa Gad
First submitted to arxiv on: 3 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel survey is presented, leveraging pose estimation techniques for real-time emotional recognition using cameras, VR, and multimodal inputs. The study analyzes 19 papers from selected journals and databases, highlighting methodologies, classification algorithms, and datasets related to emotion recognition and pose estimation. A benchmark is established based on accuracy, a common performance metric used. The survey concludes that multimodal approaches achieve the best accuracy, paving the way for future developments in this research topic. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study explores using cameras and virtual reality to recognize emotions in real-time. Researchers analyzed 19 papers to understand how they work and what makes them successful. They found that combining different types of data, like images and videos, leads to better results. This discovery can help us develop new ways to recognize emotions and improve our interactions with technology. |
Keywords
» Artificial intelligence » Classification » Pose estimation
