首个基于事件相机的第一视角手势数据集，助力低功耗虚拟现实手势识别。
x-RAGE: eXtended Reality -- Action & Gesture Events Dataset
- 采用事件相机捕捉第一视角手势，突破传统视觉帧率限制。
- 公开首个面向元宇宙场景的事件相机手势数据集，支持神经形态计算。
- 适合研究低功耗、实时手势识别的学者与开发者。
随着元宇宙兴起及可穿戴设备关注增加，基于手势的人机交互变得愈发重要。近年来，为支持虚拟现实/增强现实头显和眼镜的手势识别，多个聚焦第一人称视角（egocentric）的数据集相继出现。然而，传统帧式视觉在数据带宽需求和捕捉快速运动方面存在局限。为此，类生物启发的事件相机成为有吸引力的替代方案。本文首次提出面向元宇宙应用的事件相机驱动的第一人称手势数据集——x-RAGE，旨在推动神经形态、低功耗的XR手势识别技术发展。该数据集已公开发布于 https://gitlab.com/NVM_IITD_Research/xrage。
原文摘要 · Abstract (English)
With the emergence of the Metaverse and focus on wearable devices in the recent years gesture based human-computer interaction has gained significance. To enable gesture recognition for VR/AR headsets and glasses several datasets focusing on egocentric i.e. first-person view have emerged in recent years. However, standard frame-based vision suffers from limitations in data bandwidth requirements as well as ability to capture fast motions. To overcome these limitation bio-inspired approaches such as event-based cameras present an attractive alternative. In this work, we present the first event-camera based egocentric gesture dataset for enabling neuromorphic, low-power solutions for XR-centric gesture recognition. The dataset has been made available publicly at the following URL: https://gitlab.com/NVM_IITD_Research/xrage.
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