Fusion of color and depth information for human actions recognition

2020 ◽  
Author(s):  
Viacheslav V. Voronin ◽  
Marina Zhdanova ◽  
Evgenii Semenishchev ◽  
Aleksander Zelensky ◽  
Olga Tokareva
Keyword(s):  
Depth Information ◽  
Human Actions ◽  
Human Actions Recognition

Research on Applied Technology in Human Action Recognition Based on Skeleton Information

2013 ◽  
Vol 859 ◽  
pp. 498-502 ◽  
Author(s):  
Zhi Qiang Wei ◽  
Ji An Wu ◽  
Xi Wang
Keyword(s):  
Data Analysis ◽  
Action Recognition ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Experimental Results ◽  
Human Actions ◽  
Applied Technology ◽  
Feature Sequence ◽  
Human Actions Recognition

In order to realize the identification of human daily actions, a method of identifying human daily actions is realized in this paper, which transforms this problem into converting human action recognition into analyzing feature sequence. Then the feature sequence combined with improved LCS algorithm could realize the human actions recognition. Data analysis and experimental results show the recognition rate of this method is high and speed is fast, and this applied technology will have broad prospects.

Human Action Recognition Based on Improved MIL

2015 ◽  
Vol 713-715 ◽  
pp. 2152-2155 ◽  
Author(s):  
Shao Ping Zhu
Keyword(s):  
Computer Vision ◽  
Action Recognition ◽  
Heuristic Algorithm ◽  
Human Action Recognition ◽  
Human Action ◽  
Image Sequences ◽  
Multiple Instance Learning ◽  
New Method ◽  
Human Actions ◽  
Human Actions Recognition

According to the problem that achieves robust human actions recognition from image sequences in computer vision, using the Iterative Querying Heuristic algorithm as a guide, a improved Multiple Instance Learning (MIL) method is proposed for human action recognition in video image sequences. Experiments show that the new method can quickly recognize human actions and achieve high recognition rates, and on the Weizmann database validate our analysis.

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