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On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2024-02-29

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Xin HE

https://orcid.org/0000-0001-8229-8143

Zetao CHEN

https://orcid.org/0000-0002-5596-5008

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Frontiers of Information Technology & Electronic Engineering  2024 Vol.25 No.5 P.755-762

http://doi.org/10.1631/FITEE.2400011


SEVAR: a stereo event camera dataset for virtual and augmented reality


Author(s):  Yuda DONG, Zetao CHEN, Xin HE, Lijun LI, Zichao SHU, Yinong CAO, Junchi FENG, Shijie LIU, Chunlai LI, Jianyu WANG

Affiliation(s):  Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China; more

Corresponding email(s):   dongyuda21@mails.ucas.ac.cn, zetao-chen@ylab.ac.cn, xinhe@ucas.ac.cn

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Yuda DONG, Zetao CHEN, Xin HE, Lijun LI, Zichao SHU, Yinong CAO, Junchi FENG, Shijie LIU, Chunlai LI, Jianyu WANG. SEVAR: a stereo event camera dataset for virtual and augmented reality[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(5): 755-762.

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Abstract: 
Event cameras, characterized by their low latency, large dynamic range, and extremely high temporal resolution, have recently received increasing attention. These features make them particularly well-suited for virtual/augmented reality (VR/AR) applications. To facilitate the development of three-dimensional (3D) perception and navigation algorithms in VR/AR applications using event cameras, we introduce the Stereo Event camera dataset for Virtual and Augmented Reality (SEVAR), which comprises a wide variety of head-mounted indoor sequences, including scenarios with rapid motion and a large dynamic range. We present the first comprehensive set of VR/AR datasets captured with an event-based stereo camera, a regular stereo camera at 30 Hz, and an inertial measurement unit at 1000 Hz. The camera placement, field of view (FoV), and resolution match those of the head-mounted device, such as Meta Quest Pro. All sensors are time-synchronized in the hardware. Ground truth poses captured by a motion capture system are also available for trajectory evaluation. The sequences include several common scenarios, and cover the specific challenges targeted by event cameras. The dataset can be found at https://github.com/sevar-dataset/sevar.

SEVAR:用于虚拟和增强现实场景的双目事件相机数据集

董宇达1,3,陈泽涛4,何欣?1,2,李立俊4,舒子超4,曹易农1,3
冯俊驰1,3,刘世界1,李春来1,2,王建宇1,2
1中国科学院大学杭州高等研究院,中国杭州市,310024
2中国科学院上海技术物理研究所,中国上海市,200083
3中国科学院大学,中国北京市,100049
4甬江实验室,中国宁波市,130021
摘要:近年来,事件相机以其低延迟、高动态范围和高时间分辨率等特点受到越来越多关注。这些特点使它特别适合应用于虚拟和增强现实(VR/AR)领域。为了促进事件相机在VR/AR应用中的三维感知和定位算法的发展,我们引入用于虚拟和增强现实场景的双目事件相机数据集(SEVAR)。该数据集以头戴式设备为主体,覆盖几种常见的室内场景序列,包括面向事件相机的快速运动和高动态范围的挑战性情景。我们发布了第一组VR/AR场景的感知和定位数据集,该数据集由双目事件体相机、30 Hz双目标准相机和1000 Hz惯性测量单元采集。相机的放置方式、视场和分辨率与商用头戴设备(如Meta Quest Pro)相似。所有传感器在硬件上进行时间同步。为更好地开展定位精度和轨迹的评估,提供了由动作捕捉系统捕捉的位姿真值。数据集见https://github.com/sevar-dataset/sevar。

关键词:同步定位与地图构建(SLAM)数据集;事件相机;虚拟和增强现实(VR/AR)

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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