Silhouette Analysis for Human Action Recognition Based on Supervised Temporal t-SNE and Incremental Learning

2015 ◽  
Vol 24 (10) ◽  
pp. 3203-3217 ◽  
Author(s):  
Jian Cheng ◽  
Haijun Liu ◽  
Feng Wang ◽  
Hongsheng Li ◽  
Ce Zhu
Keyword(s):  
Action Recognition ◽  
Incremental Learning ◽  
Human Action Recognition ◽  
Human Action ◽  
Silhouette Analysis

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

Deep Learning for Human Action Recognition Survey

2018 ◽  
Vol 6 (10) ◽  
pp. 323-328
Author(s):  
K.Kiruba . ◽  
D. Shiloah Elizabeth ◽  
C Sunil Retmin Raj
Keyword(s):  
Deep Learning ◽  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action

Human Action Recognition Based on Discriminative Sparse Coding Video Representation

ROBOT ◽  
2012 ◽  
Vol 34 (6) ◽  
pp. 745 ◽  
Author(s):  
Bin WANG ◽  
Yuanyuan WANG ◽  
Wenhua XIAO ◽  
Wei WANG ◽  
Maojun ZHANG
Keyword(s):  
Action Recognition ◽  
Sparse Coding ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Representation
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