x-RAGE: eXtended Reality -- Action & Gesture Events Dataset
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arXiv
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| Format: | Preprint |
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2024
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| author | Parmar, Vivek Bane, Dwijay Sarwar, Syed Shakib Stangherlin, Kleber De Salvo, Barbara Suri, Manan |
| author_facet | Parmar, Vivek Bane, Dwijay Sarwar, Syed Shakib Stangherlin, Kleber De Salvo, Barbara Suri, Manan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_19486 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | x-RAGE: eXtended Reality -- Action & Gesture Events Dataset Parmar, Vivek Bane, Dwijay Sarwar, Syed Shakib Stangherlin, Kleber De Salvo, Barbara Suri, Manan Computer Vision and Pattern Recognition Emerging Technologies 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. |
| title | x-RAGE: eXtended Reality -- Action & Gesture Events Dataset |
| topic | Computer Vision and Pattern Recognition Emerging Technologies |
| url | https://arxiv.org/abs/2410.19486 |