期刊论文

Wei, Yantao

英文

International Journal of Distributed Sensor Networks

1550-1477

2020

16

2

10.1177/1550147720907830

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been financially supported by the National Natural Science Foundation of China under Grant 61502195, the Natural Science Foundation of Hubei Province under Grant 2018CFB691, the Fundamental Research Funds for the Central Universities under Grants CCNU19QN023 and CCNU18QN020, and the Humanities and Social Sciences Foundation of the Ministry of Education under Grant 19YJC880079.

本校为第一且通讯机构

Human activity recognition using depth videos remains a challenging problem while in some applications the available training samples is limited. In this article, we propose a new method for human activity recognition by crafting an integrated descriptor called multi-level fused features for depth sequences and devising a fast broad learning system based on matrix decomposition for classification. First, the surface normals are computed from original depth maps; the histogram of the surface normal orientations is obtained as a low-level feature by accumulating the contributions from normals, t...