Video action recognition: A survey

Abstract

In recent years, as computer vision technology advances quickly, video action recognition has become a research hotspot. However, the field of video action recognition still faces many problems and challenges, such as the complex temporal dynamics of video data and the high computation cost caused by the explosive growth of video data. This paper summarizes the algorithms of video action recognition, and introduces them in two parts, namely, traditional handcrafted representation methods and deep learning representation methods. Among them, the traditional handcrafted representation methods are divided into two categories: Holistic Representation Methods and Local Representation Methods; The deep learning representation methods can be divided into RGB data based methods and Kinect-Based methods according to the type of input data modality. This paper focuses on the methods based on RGB data. This paper introduces the representative achievements according to different research directions, compares the advantages and disadvantages of various algorithms, and finally puts forward the prospect of the future development direction.