Summary of Ringgesture: a Ring-based Mid-air Gesture Typing System Powered by a Deep-learning Word Prediction Framework, By Junxiao Shen et al.
RingGesture: A Ring-Based Mid-Air Gesture Typing System Powered by a Deep-Learning Word Prediction Framework
by Junxiao Shen, Roger Boldu, Arpit Kalla, Michael Glueck, Hemant Bhaskar Surale Amy Karlson
First submitted to arxiv on: 8 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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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 key challenge in developing lightweight augmented reality (AR) glasses is the need for an additional input device to enable intuitive hand tracking and typing. This paper proposes RingGesture, a ring-based mid-air gesture typing technique that utilizes electrodes to track gestures and inertial measurement units (IMUs) for hand tracking. The method allows for seamless cursor navigation through hand movements, similar to raycast-based mid-air gesture typing in VR headsets. To enhance accuracy and input speed, the authors propose Score Fusion, a deep-learning word prediction framework comprising three components: word-gesture decoding, spatial spelling correction, and lightweight contextual language models. Comparative and longitudinal studies demonstrate the effectiveness of RingGesture (average text entry speed: 27.3 words per minute) and the superiority of Score Fusion (28.2% improvement in uncorrected Character Error Rate). The system received a System Usability Score of 83, indicating excellent usability. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about making it easier to use lightweight augmented reality glasses. One problem with these glasses is that they don’t have multiple cameras like other AR devices, so people can’t track their hands as easily. The authors came up with a new way to type on the glasses using hand movements, called RingGesture. It uses special sensors to track the movement of your hands and translate it into typing on the screen. They also developed a system that helps predict what you’re going to type next, making it faster and more accurate. Tests showed that this system worked well and was easy to use. |
Keywords
» Artificial intelligence » Deep learning » Tracking
