Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild

التفاصيل البيبلوغرافية
العنوان: Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild
المؤلفون: Ma, Lingni, Ye, Yuting, Hong, Fangzhou, Guzov, Vladimir, Jiang, Yifeng, Postyeni, Rowan, Pesqueira, Luis, Gamino, Alexander, Baiyya, Vijay, Kim, Hyo Jin, Bailey, Kevin, Fosas, David Soriano, Liu, C. Karen, Liu, Ziwei, Engel, Jakob, De Nardi, Renzo, Newcombe, Richard
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics
الوصف: We introduce Nymeria - a large-scale, diverse, richly annotated human motion dataset collected in the wild with multiple multimodal egocentric devices. The dataset comes with a) full-body ground-truth motion; b) multiple multimodal egocentric data from Project Aria devices with videos, eye tracking, IMUs and etc; and c) a third-person perspective by an additional observer. All devices are precisely synchronized and localized in on metric 3D world. We derive hierarchical protocol to add in-context language descriptions of human motion, from fine-grain motion narration, to simplified atomic action and high-level activity summarization. To the best of our knowledge, Nymeria dataset is the world's largest collection of human motion in the wild; first of its kind to provide synchronized and localized multi-device multimodal egocentric data; and the world's largest motion-language dataset. It provides 300 hours of daily activities from 264 participants across 50 locations, total travelling distance over 399Km. The language descriptions contain 301.5K sentences in 8.64M words from a vocabulary size of 6545. To demonstrate the potential of the dataset, we evaluate several SOTA algorithms for egocentric body tracking, motion synthesis, and action recognition. Data and code are open-sourced for research (c.f. https://www.projectaria.com/datasets/nymeria).
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2406.09905
رقم الأكسشن: edsarx.2406.09905
قاعدة البيانات: arXiv