IEEE Trans Pattern Anal Mach Intell. 2023 Jun;45(6):6846-6866. doi: 10.1109/TPAMI.2020.2986648. Epub 2023 May 5.
Egocentric vision (a.k.a. first-person vision-FPV) applications have thrived over the past few years, thanks to the availability of affordable wearable cameras and large annotated datasets. The position of the wearable camera (usually mounted on the head) allows recording exactly what the camera wearers have in front of them, in particular hands and manipulated objects. This intrinsic advantage enables the study of the hands from multiple perspectives: localizing hands and their parts within the images; understanding what actions and activities the hands are involved in; and developing human-computer interfaces that rely on hand gestures. In this survey, we review the literature that focuses on the hands using egocentric vision, categorizing the existing approaches into: localization (where are the hands or parts of them?); interpretation (what are the hands doing?); and application (e.g., systems that used egocentric hand cues for solving a specific problem). Moreover, a list of the most prominent datasets with hand-based annotations is provided.
自我中心视觉（也称为第一人称视觉-FPV）应用在过去几年中蓬勃发展，这要归功于价格实惠的可穿戴相机和大型标注数据集的可用性。可穿戴相机的位置（通常安装在头部）允许记录相机佩戴者面前的准确内容，特别是手和操作的对象。这种内在优势使我们能够从多个角度研究手：在图像中定位手及其部分；理解手参与的动作和活动；并开发依赖手势的人机界面。在本次调查中，我们回顾了使用自我中心视觉的文献，将现有的方法分为三类：定位（手或手的部分在哪里？）；解释（手在做什么？）；以及应用（例如，使用自我中心手线索解决特定问题的系统）。此外，还提供了带有手部标注的最突出数据集列表。
