DocumentCode
2066363
Title
Adaptive particle filter based pose estimation using a monocular camera model
Author
Goli, Mohammad ; Ghanbari, Ahmad ; Janabi-Sharifi, Farrokh ; Khosroshahi, Ghader Karimian
Author_Institution
Sch. of Eng., Emerging Technol. Univ. of Tabriz, Tabriz, Iran
fYear
2010
fDate
25-27 Oct. 2010
Firstpage
1
Lastpage
6
Abstract
Camera full pose estimation using only a monocular camera model is an important topic in the field of visual servoing. In this paper a simple adaptive method for updating the weights of particle filter is proposed. Using this method, the efficiency of particle filter in estimating the full pose of camera is improved. Results of the proposed method are compared with those of generic particle filter (PF) and EKF under the same condition through an intensive computer simulation.
Keywords
cameras; particle filtering (numerical methods); pose estimation; visual servoing; adaptive particle filter; intensive computer simulation; monocular camera model; pose estimation; visual servoing; Atmospheric measurements; Cameras; Computational modeling; Estimation; Hidden Markov models; Particle filters; Particle measurements; Bayesian filter; extended Kalman filter; particle filter; pose estimation; visual servoing;
fLanguage
English
Publisher
ieee
Conference_Titel
Optomechatronic Technologies (ISOT), 2010 International Symposium on
Conference_Location
Toronto, ON
Print_ISBN
978-1-4244-7684-8
Type
conf
DOI
10.1109/ISOT.2010.5687313
Filename
5687313
Link To Document