Action Recognition Based on Optimal Joint Selection and Discriminative Depth Descriptor

The 13th Asian Conference on Computer Vision 2016 Haomiao NiHong LiuXiangdong WangYueliang Qian

This paper proposes a novel human action recognition using the decision-level fusion of both skeleton and depth sequence. Firstly, a state-of-the-art descriptor RBPL, relative body part locations, is adopted to represent skeleton... (read more)

PDF

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.