Abstract
With the emergence of Kinect, many research results have emerged in human action recognition based on skeleton information, which has promoted the development of human-computer interaction. In this paper, from the skeleton data obtained by Kinect, static features and dynamic features are extracted, and the two are merged; SVM classifier is used for action recognition. It is verified on the MSR Daily Activity 3D data set, and the experimental results show that the method in this paper improves the accuracy of action recognition.
| Original language | English |
|---|---|
| Article number | 012190 |
| Journal | Journal of Physics: Conference Series |
| Volume | 1693 |
| Issue number | 1 |
| DOIs | |
| State | Published - 16 Dec 2020 |
| Externally published | Yes |
| Event | 2020 3rd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2020 - Hulun Buir, Inner Mongolia, China Duration: 25 Sep 2020 → 27 Sep 2020 |