Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering

An Efficient Object Tracking Algorithm of Sports Video

Authors
Hongyuan Guo
Corresponding Author
Hongyuan Guo
Available Online February 2016.
DOI
10.2991/iccsae-15.2016.67How to use a DOI?
Keywords
sports video; particle filter; mean- shift; hybrid tracking; algorithm
Abstract

This paper studies the moving object tracking technology for sports video and puts forward an optimized hybrid tracking method. First, particle filter algorithm is adopted to predict the position of moving target, and then compute comparability between object model and object on the estimated position, if the comparability is less than a certain threshold value, we consider the object’s dynamic model has changed and need to modify the dynamic model; if the comparability is more than a certain threshold value, we consider the object’s dynamic model has not changed and don’t need to modify the dynamic model, in this way we can find the dynamic model of optimization. Finally we use this dynamic model of optimization in mean- shift algorithm, and compute object’s true position.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
Series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
10.2991/iccsae-15.2016.67
ISSN
2352-538X
DOI
10.2991/iccsae-15.2016.67How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hongyuan Guo
PY  - 2016/02
DA  - 2016/02
TI  - An Efficient Object Tracking Algorithm of Sports Video
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 348
EP  - 352
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.67
DO  - 10.2991/iccsae-15.2016.67
ID  - Guo2016/02
ER  -