Human gait recognition via deterministic learning

2012 ◽  
Vol 35 ◽  
pp. 92-102 ◽  
Author(s):  
Wei Zeng ◽  
Cong Wang
Keyword(s):  
Gait Recognition ◽  
Human Gait ◽  
Deterministic Learning

Human gait recognition based on deterministic learning and knowledge fusion through multiple walking views

2020 ◽  
Vol 357 (4) ◽  
pp. 2471-2491 ◽  
Author(s):  
Muqing Deng ◽  
Tingchang Fan ◽  
Jiuwen Cao ◽  
Siu-Ying Fung ◽  
Jing Zhang
Keyword(s):  
Gait Recognition ◽  
Human Gait ◽  
Deterministic Learning ◽  
Knowledge Fusion

Human gait recognition based on deterministic learning and Kinect sensor

2018 ◽  
Author(s):  
Hao Zhen ◽  
Muqing Deng ◽  
Peng Lin ◽  
Cong Wang
Keyword(s):  
Gait Recognition ◽  
Human Gait ◽  
Kinect Sensor ◽  
Deterministic Learning

Model-Based Human Gait Recognition Via Deterministic Learning

2013 ◽  
Vol 6 (2) ◽  
pp. 218-229 ◽  
Author(s):  
Wei Zeng ◽  
Cong Wang ◽  
Yuanqing Li
Keyword(s):  
Gait Recognition ◽  
Human Gait ◽  
Deterministic Learning ◽  
Model Based

Human gait recognition based on deterministic learning through multiple views fusion

2016 ◽  
Vol 78 ◽  
pp. 56-63 ◽  
Author(s):  
Muqing Deng ◽  
Cong Wang ◽  
Qingfeng Chen
Keyword(s):  
Gait Recognition ◽  
Human Gait ◽  
Multiple Views ◽  
Deterministic Learning

Deterministic learning for human gait recognition

2016 ◽  
Author(s):  
Feifei Yang ◽  
Wenjie Si ◽  
Wei Zeng ◽  
Qian Wang
Keyword(s):  
Gait Recognition ◽  
Human Gait ◽  
Deterministic Learning

Video-based Indoor Human Gait Recognition Using Depth Imaging and Hidden Markov Model: A Smart System for Smart Home

2010 ◽  
Vol 20 (1) ◽  
pp. 120-128 ◽  
Author(s):  
Md. Zia Uddin ◽  
Tae-Seong Kim ◽  
Jeong Tai Kim
Keyword(s):  
Hidden Markov ◽  
Gait Recognition ◽  
Smart Homes ◽  
The Elderly ◽  
Recognition System ◽  
Home Healthcare ◽  
Human Gait ◽  
Depth Imaging ◽  
Smart System ◽  
Spatiotemporal Features

Smart homes that are capable of home healthcare and e-Health services are receiving much attention due to their potential for better care of the elderly and disabled in an indoor environment. Recently the Center for Sustainable Healthy Buildings at Kyung Hee University has developed a novel indoor human activity recognition methodology based on depth imaging of a user’s activities. This system utilizes Independent Component Analysis to extract spatiotemporal features from a series of depth silhouettes of various activities. To recognise the activities from the spatiotemporal features, trained Hidden Markov Models of the activities would be used. In this study, this technique has been extended to recognise human gaits (including normal and abnormal). Since this system could be of great significance for the caring of the elderly, to promote and preserve their health and independence, the gait recognition system would be considered a primary function of the smart system for smart homes. The indoor gait recognition system is trained to detect abnormal gait patterns and generate warnings. The system works in real-time and is aimed to be installed at smart homes. This paper provides the information for further development of the system for their application in the future.

Human gait recognition using firefly template segmentation

2021 ◽  
pp. 1-11
Author(s):  
Sankara Rao Palla ◽  
Gupteswar Sahu ◽  
Priyadarsan Parida
Keyword(s):  
Gait Recognition ◽  
Human Gait
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