跳至内容
  • 首页
  • 资讯
  • 资源下载
  • 行业方案
  • Job招聘
  • Paper论文
  • Patent专利
  • 映维会员
  • 导航收录
  • 合作
  • 关于
  • 微信群
  • All
  • XR
  • CV
  • CG
  • HCI
  • Video
  • Optics
  • Perception
  • Reconstruction

Gesture2Text: A Generalizable Decoder for Word-Gesture Keyboards in XR Through Trajectory Coarse Discretization and Pre-training

小编 广东客   |   分类:HCI   |   2025年3月27日

Note: We don't have the ability to review paper

PubDate: Otc 2024

Teams:Meta,University of Bristol

Writers:Junxiao Shen, Khadija Khaldi, Enmin Zhou, Hemant Bhaskar Surale, Amy Karlson

PDF:Gesture2Text: A Generalizable Decoder for Word-Gesture Keyboards in XR Through Trajectory Coarse Discretization and Pre-training

Abstract

Text entry with word-gesture keyboards (WGK) is emerging as a popular method and becoming a key interaction for Extended Reality (XR). However, the diversity of interaction modes, keyboard sizes, and visual feedback in these environments introduces divergent word-gesture trajectory data patterns, thus leading to complexity in decoding trajectories into text. Template-matching decoding methods, such as SHARK

2, are commonly used for these WGK systems because they are easy to implement and configure. However, these methods are susceptible to decoding inaccuracies for noisy trajectories. While conventional neural-network-based decoders (neural decoders) trained on word-gesture trajectory data have been proposed to improve accuracy, they have their own limitations: they require extensive data for training and deep-learning expertise for implementation. To address these challenges, we propose a novel solution that combines ease of implementation with high decoding accuracy: a generalizable neural decoder enabled by pre-training on large-scale coarsely discretized word-gesture trajectories. This approach produces a ready-to-use WGK decoder that is generalizable across mid-air and on-surface WGK systems in augmented reality (AR) and virtual reality (VR), which is evident by a robust average Top-4 accuracy of 90.4% on four diverse datasets. It significantly outperforms SHARK

2 with a 37.2% enhancement and surpasses the conventional neural decoder by 7.4%. Moreover, the Pre-trained Neural Decoder's size is only 4 MB after quantization, without sacrificing accuracy, and it can operate in real-time, executing in just 97 milliseconds on Quest 3.

本文链接:https://paper.nweon.com/16249

您可能还喜欢...

  • d42195409175426e756eb12e06cea4fe-thumb-medium

    Holoscopic 3D Micro-Gesture Database for Wearable Device Interaction

    2020年07月29日 映维

  • 99f814c8e1ef9785e33a51aaf30b1f36-thumb-medium

    High-Fidelity Interaction for Virtual and Augmented Reality

    2020年11月04日 映维

  • Text Typing in VR Using Smartphones Touchscreen and HMD

    2021年04月06日 映维

关注:

RSS 最新AR/VR行业分享

  • 映维日报:Meta实现Quest 3同时渲染3个高保真虚拟化身,乐山职高203万元招标VR教学中心 2025年8月5日
  • 乐山第一职业高级中学203万元招标建设VR教学中心 2025年8月5日
  • 黑河瑷珲历史陈列馆51.6万元采购MR沉浸式体验设备 2025年8月5日
  • 浙江省立同德医院40万元招标VR认知康复系统 2025年8月5日
  • Meta突破性技术实现Quest 3同时渲染3个高保真虚拟化身 2025年8月5日

RSS 最新AR/VR专利

  • Samsung Patent | Worktable system and manufacturing method of display panel using the same 2025年7月31日
  • Nvidia Patent | Ego-machine simulation using hardware in-loop 2025年7月31日
  • Samsung Patent | Universal controller for use with either hand 2025年7月31日
  • Sony Patent | Systems and methods for electronic game control and game controller configurations with emg sensing 2025年7月31日
  • Meta Patent | Wearable band structure with flexible printed circuit strain-relief integration, and systems and methods of use thereof 2025年7月31日

RSS 最新AR/VR行业招聘

  • Microsoft AR/VR Job | High Performance Compute, Director 2025年6月5日
  • Microsoft AR/VR Job | Data Center Technician/ Technicien de Centre de Données 2025年6月3日
  • Microsoft AR/VR Job | Senior Product Designer 2025年5月16日
  • Apple AR/VR Job | AirPlay Audio Engineer 2025年3月27日
  • Apple AR/VR Job | iOS Perception Engineer 2025年3月27日
  • 首页
  • 资讯
  • 资源下载
  • 行业方案
  • Job招聘
  • Paper论文
  • Patent专利
  • 映维会员
  • 导航收录
  • 合作
  • 关于
  • 微信群

联系微信:ovalics

版权所有:广州映维网络有限公司 © 2025

备案许可:粤ICP备17113731号-2

备案 粤公网安备 44011302004835号

友情链接: AR/VR行业导航

读者QQ群:251118691

Quest QQ群:526200310

开发者QQ群:688769630

Paper