4th International Conference on Computer and Knowledge Engineering-ICCKE2014 , 2014-10-29

Title : ( Marker based Human Pose Estimation Using Annealed Particle Swarm Optimization with Search Space Partitioning )

Authors: ashraf sharifi , Ahad Harati , Abedin Vahedian Mazloum ,

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In this paper, a marker based human pose estimation from multi-view video sequences is presented. The pose estimation problem is defined as optimization of the 45 parameters which define body pose model and is solved using particle swarm optimization (PSO). The objective of this optimization is to maximize a fitness function which formulates how much body model matches with 2D marker’s coordinate in video frames. In this algorithm a sampling covariance matrix is used in the first part of the velocity equation of PSO that is annealed with iterations. One of the major problems of this algorithm is the high number of parameters that define the pose of the body model. To tackle this problem, we divide the optimization into six stages that exploit the hierarchical structure of the model. The first stage optimizes the six parameters that define the global orientation and position of the body. Other stages are related to optimization of right and left hand, right and left leg and head orientation, respectively.

Keywords

marker based human motion tracking; particle swarm optimization
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@inproceedings{paperid:1047436,
author = {Sharifi, Ashraf and Harati, Ahad and Vahedian Mazloum, Abedin},
title = {Marker based Human Pose Estimation Using Annealed Particle Swarm Optimization with Search Space Partitioning},
booktitle = {4th International Conference on Computer and Knowledge Engineering-ICCKE2014},
year = {2014},
location = {مشهد, IRAN},
keywords = {marker based human motion tracking; particle swarm optimization (PSO)},
}

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%0 Conference Proceedings
%T Marker based Human Pose Estimation Using Annealed Particle Swarm Optimization with Search Space Partitioning
%A Sharifi, Ashraf
%A Harati, Ahad
%A Vahedian Mazloum, Abedin
%J 4th International Conference on Computer and Knowledge Engineering-ICCKE2014
%D 2014

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