Annealed particle filter based on particle swarm optimization for articulated three-dimensional human motion tracking

2010 ◽  
Vol 49 (1) ◽  
pp. 017204 ◽  
Author(s):  
Xiangyang Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Filter ◽  
Motion Tracking ◽  
Three Dimensional ◽  
Particle Swarm ◽  
Human Motion ◽  
Swarm Optimization ◽  
Human Motion Tracking ◽  
Annealed Particle Filter

scholarly journals A Review on Particle Swarm Optimization Algorithm and Its Variants to Human Motion Tracking

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Sanjay Saini ◽  
Dayang Rohaya Bt Awang Rambli ◽  
M. Nordin B. Zakaria ◽  
Suziah Bt Sulaiman
Keyword(s):  
Computer Vision ◽  
Particle Swarm Optimization ◽  
Motion Tracking ◽  
Particle Swarm ◽  
Search Space ◽  
Human Motion ◽  
Video Sequences ◽  
High Dimensional ◽  
Swarm Optimization ◽  
Human Motion Tracking

Automatic human motion tracking in video sequences is one of the most frequently tackled tasks in computer vision community. The goal of human motion capture is to estimate the joints angles of human body at any time. However, this is one of the most challenging problem in computer vision and pattern recognition due to the high-dimensional search space, self-occlusion, and high variability in human appearance. Several approaches have been proposed in the literature using different techniques. However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space. This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. An attempt is made to provide a guide for the researchers working in the field of PSO based human motion tracking from video sequences. Additionally, the paper also presents the performance of various model evaluation search strategies within PSO tracking framework for 3D pose tracking.

scholarly journals Markerless Human Motion Tracking Using Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0127833 ◽  
Author(s):  
Sanjay Saini ◽  
Nordin Zakaria ◽  
Dayang Rohaya Awang Rambli ◽  
Suziah Sulaiman
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Tracking ◽  
Particle Swarm ◽  
Human Motion ◽  
Swarm Optimization ◽  
Human Motion Tracking

Fault diagnosis based on new particle swarm optimization particle filter

2013 ◽  
Vol 32 (2) ◽  
pp. 432-435
Author(s):  
Zhi-min CHEN ◽  
Yu-ming BO ◽  
Pan-long WU ◽  
Meng-chu TIAN ◽  
Shao-xin LI ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Particle Filter ◽  
Particle Swarm ◽  
Swarm Optimization
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