Problem
Research questions and friction points this paper is trying to address.
egocentric capture
low-cost
stereo-inertial
crowdsourced data
open-source
Ego-OSCAR: Egocentric Open source Stereo CAptuRe System
🤖 AI Summary
This work addresses the high cost and limited scalability of existing first-person data collection systems by proposing and open-sourcing a low-cost (under $200 per unit), extensible head-mounted stereo visual-inertial sensing platform. The system integrates hardware-synchronized global-shutter stereo cameras, a 6-axis IMU, an embedded Linux board, and a real-time microcontroller, enabling high-quality crowdsourced data acquisition in unstructured environments. It features a complete software-hardware stack, including hardware-accelerated recording, an IMU sampling daemon, and precise time synchronization. The project contributes approximately 550 hours of synchronized stereo video with IMU data, annotated with full-temporal free-form action captions and per-frame 3D hand reconstructions—marking the first open-source integration of affordable hardware, real-time feedback, accurate time synchronization, and large-scale annotations.
📝 Abstract
We present Ego-OSCAR, an open-hardware, low-cost, head-mounted stereo-inertial capture device for egocentric data collection in the wild. EgoOSCAR pairs a hardware-synchronized global-shutter stereo camera with a 6- axis IMU, an embedded Linux SBC for on-device video encoding, and a realtime microcontroller for user feedback and watchdog functions. The complete bill of materials is under USD 200 per unit, using only commercially available components and 3D-printed parts. Alongside the device, we release a complete software stack (hardware-accelerated recording pipeline, IMU sampling daemon, time-synchronization tooling, and watchdog firmware) and roughly 550 hours of egocentric stereo video per camera with synchronized IMU, collected by a distributed contributor network across everyday indoor environments. The release is annotated rather than raw: free-form action captions cover essentially the entire recorded timeline with an open vocabulary, and per-frame 3D hand reconstructions ship alongside per-session stereo calibration. Ego-OSCAR does not aim to match the per-unit fidelity of research-grade systems such as Project Aria; it aims to be the cheapest defensible substrate for crowdsourced egocentric capture, and to lower the activation energy for any team that wants to collect egocentric data at scale. All hardware designs, software, and the dataset are open-sourced
Innovation
Methods, ideas, or system contributions that make the work stand out.
egocentric capture
stereo-inertial system
open-source hardware
low-cost sensing
3D hand reconstruction
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