Embedding Human and Articulated Object Interaction (HAOI) in 3D is an important direction for a deeper human activity understanding. Different from previous works that use parametric and CAD models to represent humans and objects, in this work, we propose a novel 3D geometric primitive-based language to encode both humans and objects. Given our new paradigm, humans and objects are all compositions of primitives instead of heterogeneous entities. Thus, mutual information learning may be achieved between the limited 3D data of humans and different object categories. Moreover, considering the simplicity of the expression and the richness of the information it contains, we choose the superquadric as the primitive representation. To explore an effective embedding of HAOI for the machine, we build a new benchmark on 3D HAOI consisting of primitives together with their images and propose a task requiring machines to recover 3D HAOI using primitives from images. Moreover, we propose a baseline of single-view 3D reconstruction on HAOI. We believe this primitive-based 3D HAOI representation would pave the way for 3D HAOI studies. Our code and data are available at https://mvig-rhos.com/p3haoi.

翻译：嵌入人体与铰接物体交互（HAOI）的三维空间建模是实现深度人类活动理解的重要方向。与以往使用参数化模型和CAD模型表征人体与物体的工作不同，本文提出一种新颖的基于三维几何基元的语言来统一编码人体与物体。基于这一新范式，人体与物体均被表示为基元的组合而非异质实体，从而能够在有限的人体三维数据与不同物体类别之间实现互信息学习。考虑到表达的简洁性与信息丰富性，我们选择超二次曲面作为基元表征。为探索机器对HAOI的有效嵌入，我们构建了一个包含基元及其图像的新型3D HAOI基准数据集，并提出一项要求机器从图像中利用基元重建3D HAOI的任务。此外，我们提出了基于单视图的HAOI三维重建基线方法。我们相信这种基于基元的3D HAOI表征将为HAOI研究铺平道路。代码与数据已开源在https://mvig-rhos.com/p3haoi。