LATIDIA · Robótica

EgoKit: Hacia la recopilación unificada de datos egocéntricos de bajo costo con dispositivos heterogéneos

arXiv: 2605.16797v2Tipo de anuncio: replace-cross Resumen: El video egocéntrico se utiliza cada vez más como fuente de datos para el aprendizaje de robots, la comprensión de actividades y la investigación de IA incorporada, pero su recopilación a escala sigue siendo

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arXiv:2605.16797v2 Announce Type: replace-cross Abstract: Egocentric video is increasingly used as a data source for robot learning, activity understanding, and embodied AI research, but collecting it at scale remains fragmented in practice: each candidate host device, such as an Android phone, iPhone, iPad, smart glasses, or extended reality (XR) headset, exposes a different SDK, a different policy on raw camera access, and different limitations on external USB cameras and on-device tracking. Synchronized ego-view and wrist-view capture is therefore typically obtained by either committing to a single proprietary platform or building one-off rigs that do not transfer across devices. To address this gap, we present EgoKit, a toolkit that exposes the