Aria Everyday Activities Dataset
This dataset addresses the need for open, multimodal egocentric data for researchers in computer vision and AI, though it is incremental as it builds on existing dataset efforts.
The authors introduced the Aria Everyday Activities (AEA) Dataset, a multimodal egocentric dataset recorded with Project Aria glasses, containing 143 daily activity sequences from diverse indoor locations, and demonstrated applications like neural scene reconstruction and prompted segmentation.
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.