scholarly journals Sensor Network Oriented Human Motion Segmentation With Motion Change Measurement

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 9281-9291 ◽  
Author(s):  
Yang Liu ◽  
Lin Feng ◽  
Shenglan Liu ◽  
Muxin Sun
Keyword(s):  
Sensor Network ◽  
Motion Segmentation ◽  
Human Motion ◽  
Change Measurement

Human motion segmentation based on structure constraint matrix factorization

2021 ◽  
Vol 65 (1) ◽  
Author(s):  
Hongbo Gao ◽  
Fang Guo ◽  
Juping Zhu ◽  
Zhen Kan ◽  
Xinyu Zhang
Keyword(s):  
Matrix Factorization ◽  
Motion Segmentation ◽  
Human Motion ◽  
Constraint Matrix ◽  
Structure Constraint

Sensor network oriented human motion capture via wearable intelligent system

2021 ◽  
Author(s):  
Sen Qiu ◽  
Hongkai Zhao ◽  
Nan Jiang ◽  
Donghui Wu ◽  
Guangcai Song ◽  
...  
Keyword(s):  
Sensor Network ◽  
Motion Capture ◽  
Intelligent System ◽  
Human Motion ◽  
Human Motion Capture

scholarly journals IMM Filter Based Human Tracking Using a Distributed Wireless Sensor Network

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Sen Zhang ◽  
Wendong Xiao ◽  
Jun Gong
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Node ◽  
Computing System ◽  
Human Motion ◽  
Wireless Sensor ◽  
Human Tracking ◽  
Multiple Model ◽  
Tracking Accuracy ◽  
Node Selection

This paper proposes a human tracking approach in a distributed wireless sensor network. Most of the efforts on human tracking focus on vision techniques. However, most vision-based approaches to moving object detection involve intensive real-time computations. In this paper, we present an algorithm for human tracking using low-cost range wireless sensor nodes which can contribute lower computational burden based on a distributed computing system, while the centralized computing system often makes some information from sensors delay. Because the human target often moves with high maneuvering, the proposed algorithm applies the interacting multiple model (IMM) filter techniques and a novel sensor node selection scheme developed considering both the tracking accuracy and the energy cost which is based on the tacking results of IMM filter at each time step. This paper also proposed a novel sensor management scheme which can manage the sensor node effectively during the sensor node selection and the tracking process. Simulations results show that the proposed approach can achieve superior tracking accuracy compared to the most recent human motion tracking scheme.

scholarly journals Low-Rank Transfer Human Motion Segmentation

2019 ◽  
Vol 28 (2) ◽  
pp. 1023-1034 ◽  
Author(s):  
Lichen Wang ◽  
Zhengming Ding ◽  
Yun Fu
Keyword(s):  
Motion Segmentation ◽  
Human Motion ◽  
Low Rank
Sign in / Sign up

Export Citation Format

Share Document