Paper Info
Title
Articulated human pose tracking based on game theory
Abstract
Human pose tracking is among the most popular hotspots in the field of computer vision. In this paper, we propose a novel game theory based method for tracking two dimensional articulated human poses in monocular video sequences. A new probability scheme of game theory is introduced into human pose tracking to find optimal solutions of human poses. The possible limb positions are modeled as strategies of agents who play normal form game with adjacent agents. Likelihood measurements and distance constraints are applied to calculate the payoffs of each of the strategies. Finally, the Nash equilibria are found for each normal form game and the human poses are estimated based on them. In the experiments, the effectiveness and efficiency of the proposed algorithm is fully exhibited.
Year
DOI
Venue
2013
10.1109/ICIP.2013.6738526
ICIP
Keywords
Field
DocType
two-dimensional articulated human poses,articulated human pose tracking,nash equilibrium,limb positions,pose estimation,monocular video sequences,nash equilibria,game theory,image sequences,computer vision,likelihood measurement,probability scheme,distance constraint,adjacent agents,human pose estimation,probability,normal form game
Computer vision,Pose tracking,Computer science,3D pose estimation,Pose,Monocular video,Artificial intelligence,Game theory,Articulated body pose estimation,Normal-form game,Nash equilibrium
Conference
ISSN
Citations 
PageRank 
1522-4880
0
0.34
References 
Authors
10
3
Name
Order
Citations
PageRank
Chenguang Liu110.69
H. D. Cheng21900138.13
Vicki H. Allan322529.29