ParaHome：面向人-物交互3D生成建模的日常家庭活动参数化
ParaHome: Parameterizing Everyday Home Activities Towards 3D Generative Modeling of Human-Object Interactions
AI总结：
本文提出ParaHome系统，通过多视角相机和可穿戴设备捕获家庭场景中的人-物3D交互数据，构建含486分钟序列的数据集，并验证其在生成建模中的潜力。
摘要：
为了使机器能够理解人类在日常生活中与物理世界的交互方式，需要在自然环境中捕获3D交互信号，使人们能够在一系列顺序和随意操作中与多个物体互动。为实现这一目标，我们引入了ParaHome系统，该系统旨在捕获常见家庭环境中人类和物体的动态3D运动。我们的系统采用多视角设置，包含70个同步RGB摄像头，以及可穿戴动作捕捉设备，包括基于IMU的全身套装和手部动作捕捉手套。利用ParaHome系统，我们收集了一个新的人-物交互数据集，包含38名参与者的207次捕获中的486分钟序列，在三个关键方面提供了进步：（1）在情境化家庭环境中捕获身体运动和灵巧的手部操作运动以及多个物体；（2）涵盖顺序和并发操作，并配有文本描述；（3）包含由3D参数化模型表示的多部件铰接物体。我们展示了系统设计的详细理由，并进行了关键的生成建模实验，以证明我们数据集的潜力。
英文摘要：
To enable machines to understand the way humans interact with the physical world in daily life, 3D interaction signals should be captured in natural settings, allowing people to engage with multiple objects in a range of sequential and casual manipulations. To achieve this goal, we introduce our ParaHome system designed to capture dynamic 3D movements of humans and objects within a common home environment. Our system features a multi-view setup with 70 synchronized RGB cameras, along with wearable motion capture devices including an IMU-based body suit and hand motion capture gloves. By leveraging the ParaHome system, we collect a new human-object interaction dataset, including 486 minutes of sequences across 207 captures with 38 participants, offering advancements with three key aspects: (1) capturing body motion and dexterous hand manipulation motion alongside multiple objects within a contextual home environment; (2) encompassing sequential and concurrent manipulations paired with text descriptions; and (3) including articulated objects with multiple parts represented by 3D parameterized models. We present detailed design justifications for our system, and perform key generative modeling experiments to demonstrate the potential of our dataset.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
