3D skeleton-based human action classification: A survey

作者：Lo Presti, Liliana^*; La Cascia, Marco

来源：Pattern Recognition, 2016, 53: 130-147.

DOI：10.1016/j.patcog.2015.11.019

• Action recognition
• Skeleton
• Body joint
• Body pose representation
• Action classification

In recent years, there has been a proliferation of works on human action classification from depth sequences. These works generally present methods and/or feature representations for the classification of actions from sequences of 3D locations of human body joints and/or other sources of data, such as depth maps and RGB videos. @@@ This survey highlights motivations and challenges of this very recent research area by presenting technologies and approaches for 3D skeleton-based action classification. The work focuses on aspects such as data pre-processing, publicly available benchmarks and commonly used accuracy measurements. Furthermore, this survey introduces a categorization of the most recent works in 3D skeleton-based action classification according to the adopted feature representation. @@@ This paper aims at being a starting point for practitioners who wish to approach the study of 3D action classification and gather insights on the main challenges to solve in this emerging field.

• 出版日期2016-5