Stacked Filter Bank based descriptor for Human Action Recognition from Depth Sequences

2019 ◽  
Author(s):  
P. Rathnakara Shetty ◽  
B.H. Shekar ◽  
Leonid Mestetsky ◽  
M. Manju Prasad
Keyword(s):  
Action Recognition ◽  
Filter Bank ◽  
Human Action Recognition ◽  
Human Action ◽  
Depth Sequences

Skeleton embedded motion body partition for human action recognition using depth sequences

2018 ◽  
Vol 143 ◽  
pp. 56-68 ◽  
Author(s):  
Xiaopeng Ji ◽  
Jun Cheng ◽  
Wei Feng ◽  
Dapeng Tao
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Depth Sequences

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
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