Space-time representation of people based on 3D skeletal data: A review

• Published in: Computer vision and image understanding Vol. 158; pp. 85 - 105
• Main Authors: Han, Fei, Reily, Brian, Hoff, William, Zhang, Hao
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.05.2017
• Subjects: 3D visual perception; Human representation; Skeleton data; Space-time features; Survey; Human representation; Skeleton data; Survey; Space-time features; 3D visual perception
• ISSN: 1077-3142; 1090-235X
• DOI: 10.1016/j.cviu.2017.01.011

•First survey dedicated to human representations based on 3D skeleton data.•Our survey is comprehensive and covers the most recent and advanced approaches.•An insightful categorization and analysis of the 3D skeleton-based representations is provided. Spatiotemporal human representation based on 3D visual perception data is a rapidly growing research area. Representations can be broadly categorized into two groups, depending on whether they use RGB-D information or 3D skeleton data. Recently, skeleton-based human representations have been intensively studied and kept attracting an increasing attention, due to their robustness to variations of viewpoint, human body scale and motion speed as well as the realtime, online performance. This paper presents a comprehensive survey of existing space-time representations of people based on 3D skeletal data, and provides an informative categorization and analysis of these methods from the perspectives, including information modality, representation encoding, structure and transition, and feature engineering. We also provide a brief overview of skeleton acquisition devices and construction methods, enlist a number of benchmark datasets with skeleton data, and discuss potential future research directions.