scholarly journals Human Action Recognition using Multi-Kernel Learning for Temporal Residual Network

2019 ◽  
Author(s):  
Saima Nazir ◽  
Yu Qian ◽  
Muhammad Yousaf ◽  
Sergio Velastin ◽  
Ebroul Izquierdo ◽  
...  
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Kernel Learning ◽  
Residual Network

Localized Multiple Kernel Learning for Realistic Human Action Recognition in Videos

2011 ◽  
Vol 21 (9) ◽  
pp. 1193-1202 ◽  
Author(s):  
Yan Song ◽  
Yan-Tao Zheng ◽  
Sheng Tang ◽  
Xiangdong Zhou ◽  
Yongdong Zhang ◽  
...  
Keyword(s):  
Action Recognition ◽  
Multiple Kernel Learning ◽  
Human Action Recognition ◽  
Human Action ◽  
Kernel Learning ◽  
Multiple Kernel

Multi-Channel MKL for Video Human Action Recognition

2014 ◽  
Vol 599-601 ◽  
pp. 1571-1574
Author(s):  
Jia Ding ◽  
Yang Yi ◽  
Ze Min Qiu ◽  
Jun Shi Liu
Keyword(s):  
Action Recognition ◽  
Recognition Rate ◽  
Multiple Kernel Learning ◽  
Human Action Recognition ◽  
Human Action ◽  
Image Understanding ◽  
Kernel Learning ◽  
Bag Of Visual Words ◽  
Visual Words ◽  
Multiple Kernel

Human action recognition in videos plays an important role in the field of computer vision and image understanding. A novel method of multi-channel bag of visual words and multiple kernel learning is proposed in this paper. The videos are described by multi-channel bag of visual words, and a multiple kernel learning classifier is used for action classification, in which each kernel function of the classifier corresponds to a video channel in order to avoid the noise interference from other channels. The proposed approach improves the ability in distinguishing easily confused actions. Experiments on KTH show that the presented method achieves remarkable performance on the average recognition rate, and obtains comparable recognition rate with state-of-the-art methods.

scholarly journals An extension of kernel learning methods using a modified Log-Euclidean distance for fast and accurate skeleton-based Human Action Recognition

2018 ◽  
Vol 175 ◽  
pp. 32-43 ◽  
Author(s):  
Enjie Ghorbel ◽  
Jacques Boonaert ◽  
Rémi Boutteau ◽  
Stéphane Lecoeuche ◽  
Xavier Savatier
Keyword(s):  
Action Recognition ◽  
Euclidean Distance ◽  
Human Action Recognition ◽  
Human Action ◽  
Kernel Learning ◽  
Learning Methods

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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