Aria Gen 2 Pilot Dataset

2025-10-17

AI Summary

Wearable devices lack high-quality, multimodal, egocentric datasets that support joint modeling of user state, environmental structure, and human-device interaction across diverse daily activities. Method: This work introduces a systematic framework for constructing an open, multimodal, egocentric dataset using Aria Gen 2 smart glasses. It captures synchronized RGB video, inertial measurement unit (IMU) data, audio, and algorithmic outputs from primary participants and their social companions during five everyday activities—cleaning, cooking, eating, gaming, and outdoor walking. The collection employs a cross-user synchronization paradigm and incremental release strategy to enhance generalizability, robustness, and practical utility. Contribution/Results: The dataset is publicly available at projectaria.com and accompanied by the open-source Project Aria Tools toolkit, providing standardized APIs and processing examples. It establishes critical infrastructure for embodied intelligence and ubiquitous perception research, enabling reproducible, large-scale studies of real-world wearable sensing.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Multi-modal Vision

Application Category

• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search

Abstract

The Aria Gen 2 Pilot Dataset (A2PD) is an egocentric multimodal open dataset captured using the state-of-the-art Aria Gen 2 glasses. To facilitate timely access, A2PD is released incrementally with ongoing dataset enhancements. The initial release features Dia'ane, our primary subject, who records her daily activities alongside friends, each equipped with Aria Gen 2 glasses. It encompasses five primary scenarios: cleaning, cooking, eating, playing, and outdoor walking. In each of the scenarios, we provide comprehensive raw sensor data and output data from various machine perception algorithms. These data illustrate the device's ability to perceive the wearer, the surrounding environment, and interactions between the wearer and the environment, while maintaining robust performance across diverse users and conditions. The A2PD is publicly available at projectaria.com, with open-source tools and usage examples provided in Project Aria Tools.

Problem

• Captures egocentric multimodal data from daily activities
• Provides raw sensor data and machine perception outputs
• Enables perception of wearer, environment and their interactions

Innovation

• Aria Gen 2 glasses capture multimodal egocentric dataset
• Dataset includes raw sensor data and perception algorithms
• Open-source tools provided for data access and usage