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Ego-OSCAR:自我中心開源立體捕捉系統

Ego-OSCAR: Egocentric Open source Stereo CAptuRe System

August 8, 2026
作者: Gunjan Paul, Senthil Palanisamy, Satpal Singh Rathore, Pratyush Kumar Patnaik, Shubhanshu Khatana, Abhishek Anand
cs.AI

摘要

我們提出 Ego-OSCAR,這是一款開放硬體、低成本、頭戴式立體慣性捕捉裝置,用於在真實環境中進行自我中心資料收集。Ego-OSCAR 將硬體同步的全域快門立體相機與 6 軸慣性測量單元(IMU)、用於裝置端視訊編碼的嵌入式 Linux 單板電腦(SBC),以及用於使用者回饋和看門狗功能的即時微控制器相結合。整套物料清單每台不到 200 美元,僅使用市售元件和 3D 列印零件。除裝置本身外,我們還釋出了完整的軟體堆疊(硬體加速錄製管線、IMU 取樣守護行程、時間同步工具和看門狗韌體),以及由分散式貢獻者網絡在日常室內環境中收集的約 550 小時自我中心立體視訊(每台相機)及同步 IMU 資料。這份釋出資料是經過標註而非原始資料:自由形式的動作描述以開放詞彙涵蓋了幾乎整個錄製時間軸,同時提供逐幀 3D 手部重建與逐次會話的立體校準。Ego-OSCAR 的目標並非在單機保真度上比肩 Project Aria 等研究級系統;其目標是成為群眾外包自我中心捕捉最經濟可行的基礎平台,並降低任何團隊大規模收集自我中心資料的啟用門檻。所有硬體設計、軟體及資料集均以開放原始碼形式釋出。
English
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