A Survey on 3D Skeleton-Based Action Recognition Using Learning Method

Three-dimensional skeleton-based action recognition (3D SAR) has gained important attention within the computer vision community, owing to the inherent advantages offered by skeleton data. As a result, a plethora of impressive works, including those based on conventional handcrafted features and learned feature extraction methods, have been conducted over the years. However, prior surveys on action recognition have primarily focused on video or red-green-blue (RGB) data-dominated approaches, with limited coverage of reviews related to skeleton data. Furthermore, despite the extensive application of deep learning methods in this field, there has been a notable absence of research that provides an introductory…

• NS
  Natural Science Foundation of Shenzhen City

  Award: JCYJ20230807120801002
• NN
  National Natural Science Foundation of China

  Award: 62203476