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Aria Everyday Activities Dataset

20 February 2024
Zhaoyang Lv
Nickolas Charron
Pierre Moulon
Alexander Gamino
Cheng Peng
Chris Sweeney
Edward Miller
Huixuan Tang
Jeff Meissner
Jing Dong
Kiran Somasundaram
Luis Pesqueira
Mark Schwesinger
Omkar M. Parkhi
Qiao Gu
R. D. Nardi
Shangyi Cheng
Steve Saarinen
Vijay Baiyya
Yuyang Zou
Richard Newcombe
Jakob Julian Engel
Xiaqing Pan
Carl Ren
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Abstract

We present Aria Everyday Activities (AEA) Dataset, an egocentric multimodal open dataset recorded using Project Aria glasses. AEA contains 143 daily activity sequences recorded by multiple wearers in five geographically diverse indoor locations. Each of the recording contains multimodal sensor data recorded through the Project Aria glasses. In addition, AEA provides machine perception data including high frequency globally aligned 3D trajectories, scene point cloud, per-frame 3D eye gaze vector and time aligned speech transcription. In this paper, we demonstrate a few exemplar research applications enabled by this dataset, including neural scene reconstruction and prompted segmentation. AEA is an open source dataset that can be downloaded from https://www.projectaria.com/datasets/aea/. We are also providing open-source implementations and examples of how to use the dataset in Project Aria Tools https://github.com/facebookresearch/projectaria_tools.

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