You are not logged in.

Convergence of object focused simultaneous estimation of optical flow and state dynamics

Bauer,N, Pathirana,P, Ekanayake,S and Srinivasan,M 2014, Convergence of object focused simultaneous estimation of optical flow and state dynamics, International Journal of Advanced Robotic Systems, vol. 11, pp. 1-11, doi: 10.5772/58698.

Attached Files
Name Description MIMEType Size Downloads

Title Convergence of object focused simultaneous estimation of optical flow and state dynamics
Author(s) Bauer,N
Pathirana,PORCID iD for Pathirana,P orcid.org/0000-0001-8014-7798
Ekanayake,S
Srinivasan,M
Journal name International Journal of Advanced Robotic Systems
Volume number 11
Start page 1
End page 11
Total pages 11
Publisher InTech – Open Access Publisher
Place of publication Rijeka, Croatia
Publication date 2014-10-02
ISSN 1729-8806
1729-8814
Keyword(s) Optical flow
Simultaneous estimation
Tracking
Science & Technology
Technology
Robotics
UNCERTAIN SYSTEMS
SEQUENCE
VISION
Summary The purpose of this study is to prove the convergence of the simultaneous estimation of the optical flow and object state (SEOS) method. The SEOS method utilizes dynamic object parameter information when calculating optical flow in tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires the minimization of an error function containing the object's physical parameter data. When this function is discretized, the Euler-Lagrange equations form a system of linear equations. The system is arranged such that its property matrix is positive definite symmetric, proving the convergence of the Gauss-Seidel iterative methods. The system of linear equations produced by SEOS can alternatively be resolved by Jacobi iterative schemes. The positive definite symmetric property is not sufficient for Jacobi convergence. The convergence of SEOS for a block diagonal Jacobi is proved by analysing the Euclidean norm of the Jacobi matrix. In this paper, we also investigate the use of SEOS for tracking individual objects within a video sequence. The illustrations provided show the effectiveness of SEOS for localizing objects within a video sequence and generating optical flow results.
Language eng
DOI 10.5772/58698
Field of Research 099999 Engineering not elsewhere classified
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, InTech – Open Access Publisher
Persistent URL http://hdl.handle.net/10536/DRO/DU:30069283

Document type: Journal Article
Collections: School of Engineering
Institute for Frontier Materials
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 183 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Mon, 02 Feb 2015, 10:31:21 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.