A New Approach to Human Motion Sequence Recognition with Application to Diving Actions

2005 ◽  
pp. 487-496
Author(s):  
Shiming Xiang ◽  
Changshui Zhang ◽  
Xiaoping Chen ◽  
Naijiang Lu
Keyword(s):  
Human Motion ◽  
New Approach ◽  
Sequence Recognition ◽  
Motion Sequence

scholarly journals A Flexible and Stretchable Self-Powered Nanogenerator in Basketball Passing Technology Monitoring

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2584
Author(s):  
Changjun Jia ◽  
Yongsheng Zhu ◽  
Fengxin Sun ◽  
Tianming Zhao ◽  
Rongda Xing ◽  
...  
Keyword(s):  
Real Time ◽  
Inorganic Salt ◽  
Rapid Development ◽  
Human Motion ◽  
Small Scale ◽  
New Approach ◽  
Motion Data ◽  
Fifth Generation ◽  
Self Powered ◽  
Generation Technology

The rapid development of the fifth generation technology poses more challenges in the human motion inspection field. In this study, a nanogenerator, made by PVDF, ionic hydrogel, and PDMS, is used. Furthermore, a transparent, stretchable, and biocompatible PENG (TSB-PENG) is presented, which can be used as a self-powered sensor attached to the athlete’s joints, which helps to monitor the training and improve the subject’s performance. This device shows the ability to maintain a relatively stable output, under various external environments (e.g., inorganic salt, organic matter and temperature). Additionally, TSB-PENG can supply power to small-scale electronic equipment, such as Bluetooth transmitting motion data in real time. This study can provide a new approach to designing lossless, real-time, portable, and durable self-powered sensors in the sports motoring field.

Effect of Angular Momentum in ZMP on Human Motion Planning

2017 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Goobong Chung ◽  
Yujiang Xiang
Keyword(s):  
Angular Momentum ◽  
Motion Planning ◽  
High Speed ◽  
Human Motion ◽  
Lagrangian Method ◽  
New Approach ◽  
Zero Moment Point ◽  
Low Speed ◽  
Zero Moment

Zero moment point (ZMP) is an important balance criterion for human motion planning. An important term in the ZMP formula is the rate of angular momentum (RAM) of each link. It is not trivial to compute this term compared to other terms in ZMP formula. In this paper, we first propose an efficient recursive Lagrangian method for calculating the rate of angular momentum in ZMP. This new approach gives a direct way to calculate the rate of angular momentum for each link. Secondly, we evaluate the effects of RAM in ZMP on human motion predictions for walking and running. These two motions are characterized as low speed and high speed motions respectively. We conclude that it is critical to include RAM in ZMP to predict accurate high speed motion. It has relatively less effect on low speed motion.

Hybrid predictive dynamics: a new approach to simulate human motion

2012 ◽  
Vol 28 (3) ◽  
pp. 199-224 ◽  
Author(s):  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Human Motion ◽  
Predictive Dynamics ◽  
New Approach

scholarly journals Activity and Individual Human Recognition in Infrared Imagery

2010 ◽  
pp. 224-236 ◽  
Author(s):  
Bir Bhanu ◽  
Ju Han
Keyword(s):  
Human Activity ◽  
Individual Recognition ◽  
Activity Patterns ◽  
Human Motion ◽  
Infrared Imagery ◽  
Motion Sequence ◽  
Spatiotemporal Representation ◽  
Mouse Dynamics ◽  
Thermal Infrared Imagery ◽  
Human Activity Patterns

In this chapter the Authors introduce the concepts behind the mouse dynamics biometric technology, present a generic architecture of the detector used to collect and process mouse dynamics, and study the various factors used to build the user’s signature. The Authors will also provide an updated survey on the researches and industrial implementations related to the technology, and study possible applications in computer security.In this chapter, we investigate repetitive human activity patterns and individual recognition in thermal infrared imagery, where human motion can be easily detected from the background regardless of the lighting conditions and colors of the human clothing and surfaces, and backgrounds. We employ an efficient spatiotemporal representation for human repetitive activity and individual recognition, which represents human motion sequence in a single image while preserving spatiotemporal characteristics. A statistical approach is used to extract features for activity and individual recognition. Experimental results show that the proposed approach achieves good performance for repetitive human activity and individual recognition.

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