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Project Aria: A New Tool for Egocentric Multi-Modal AI Research (2308.13561v3)

Published 24 Aug 2023 in cs.HC and cs.CV

Abstract: Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception. These future devices will need to be all-day wearable in a socially acceptable form-factor to support always available, context-aware and personalized AI applications. Our team at Meta Reality Labs Research built the Aria device, an egocentric, multi-modal data recording and streaming device with the goal to foster and accelerate research in this area. In this paper, we describe the Aria device hardware including its sensor configuration and the corresponding software tools that enable recording and processing of such data.

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Authors (74)
  1. Jakob Engel (11 papers)
  2. Kiran Somasundaram (8 papers)
  3. Michael Goesele (11 papers)
  4. Albert Sun (2 papers)
  5. Alexander Gamino (3 papers)
  6. Andrew Turner (12 papers)
  7. Arjang Talattof (2 papers)
  8. Arnie Yuan (1 paper)
  9. Bilal Souti (1 paper)
  10. Brighid Meredith (2 papers)
  11. Cheng Peng (177 papers)
  12. Chris Sweeney (18 papers)
  13. Cole Wilson (1 paper)
  14. Dan Barnes (9 papers)
  15. Daniel DeTone (14 papers)
  16. David Caruso (4 papers)
  17. Derek Valleroy (1 paper)
  18. Dinesh Ginjupalli (1 paper)
  19. Duncan Frost (6 papers)
  20. Edward Miller (6 papers)
Citations (46)

Summary

  • The paper presents Project Aria, a groundbreaking wearable device that captures detailed egocentric sensor data to boost context-aware AI research.
  • It outlines a sophisticated sensor suite and real-time recording tools that ensure precise data synchronization and robust machine perception.
  • By integrating privacy safeguards and modular sensor configurations, the tool supports diverse applications such as AR, mapping, and activity recognition.

Overview of Project Aria: A New Tool for Egocentric Multi-Modal AI Research

Project Aria, developed by Meta Reality Labs Research, represents a significant advancement in the pursuit of egocentric, multi-modal AI research. This device is designed to capture and stream data from wearers in a socially acceptable, all-day wearable form factor, thus facilitating research aimed at context-aware and personalized AI applications. The paper meticulously outlines the hardware configurations, software tools, and machine perception functionalities associated with Project Aria, underscoring its potential to foster advancements in AI that seamlessly integrate with everyday human interactions.

Device Specifications and Capabilities

The core of the Project Aria device is its multi-modal sensor suite, which emulates the expected sensor stack in future augmented reality (AR) glasses aimed at machine perception rather than human consumption. The sensors are tightly calibrated and time-aligned, featuring cameras, IMUs, microphones, a magnetometer, barometer, GNSS receiver, and Wi-Fi/Bluetooth transceiver. Such configurations generate comprehensive egocentric data streams essential for sophisticated machine perception tasks, including Visual SLAM and eye-tracking. A paramount attribute is the device's form factor, weighing approximately 75g to ensure practicality and comfort for extended wear, thereby facilitating ecologically valid data capture.

Recording Tools and Data Management

Accompanying the Project Aria device are robust recording tools enabled via a mobile companion app, allowing for real-time sensor configuration and data management. The app facilitates the interaction with the device, selecting recording profiles that balance power and data utilization against specific research needs. Post-recording, data extraction via USB and optional uploads to Machine Perception Services allow researchers comprehensive access to raw and processed sensor data streams. Utilizing VRS file format, Project Aria supports large-scale data handling, with software libraries provided for efficient data interaction and visualization.

Machine Perception Services

Crucial to Project Aria's integration into research environments are its Machine Perception Services (MPS), delivering foundational capabilities such as 6-DoF device trajectories, online sensor calibration, semi-dense point clouds, and eye gaze tracking. These services leverage advanced algorithms for precise environment and user understanding, ensuring that data retrieved from the device is optimally processed for accuracy and robustness. Such enhancements mitigate typical challenges inherent in egocentric data collection, including varied motion, lighting, and environmental conditions.

Privacy and Ethical Considerations

The researchers' commitment to responsible innovation is evidenced by the stringent privacy measures incorporated into Project Aria. The device includes features like recording indicator LEDs and privacy switches to empower wearers with control over their data and respect bystander privacy. These considerations are outlined alongside Meta's Responsible Innovation Principles, ensuring that Project Aria not only serves as a tool for technological development but adheres to ethical standards of data protection and privacy.

Research Applications and Future Directions

Project Aria facilitates exploration across numerous research domains: life-long mapping, scene reconstruction, object interaction, activity recognition, summarization, and question answering. Its unique combination of modular sensor data and machine perception functionalities provides a versatile platform for studying long-term, personalized AI use cases. The device enables advancements in computational paradigms that demand contextualized AI, thus promoting seamless human-device interaction reflective of natural human behaviors.

Conclusion

The introduction of Project Aria signifies a pivotal step toward realizing complex, egocentric AI systems that harmonize with human activities and enhance contextual interactions in the digital and physical realms. By offering high-fidelity sensor data and sophisticated perception services, it lays the groundwork for future AR technologies driven by human-centric designs and responsible innovation. As researchers continue to employ Project Aria, its broad applicability will likely reveal deeper insights into human-machine symbiosis in AI-driven environments.

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