Aria Everyday Activities Dataset
Authors: name: Zhaoyang Lv, name: Nickolas Charron, name: Pierre Moulon, name: Alexander Gamino, name: Cheng Peng, name: Chris Sweeney, name: Edward Miller, name: Huixuan Tang, name: Jeff Meissner, name: Jing Dong, name: Kiran Somasundaram, name: Luis Pesqueira, name: Mark Schwesinger, name: Omkar Parkhi, name: Qiao Gu, name: Renzo De Nardi, name: Shangyi Cheng, name: Steve Saarinen, name: Vijay Baiyya, name: Yuyang Zou, name: Richard Newcombe, name: Jakob Julian Engel, name: Xiaqing Pan, name: Carl Ren

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 projectaria.com. We are also providing open-source implementations and
examples of how to use the dataset in Project Aria Tools.