Difference between revisions of "Publications/robert-seidowsky.15.visapp"
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| id = robert-seidowsky.15.visapp |
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| + | | identifier = doi:10.5220/0005292002680276 |
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@InProceedings<nowiki>{</nowiki> robert-seidowsky.15.visapp, |
@InProceedings<nowiki>{</nowiki> robert-seidowsky.15.visapp, |
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author = <nowiki>{</nowiki>Myriam Robert-Seidowsky and Jonathan Fabrizio and |
author = <nowiki>{</nowiki>Myriam Robert-Seidowsky and Jonathan Fabrizio and |
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S\'everine Dubuisson<nowiki>}</nowiki>, |
S\'everine Dubuisson<nowiki>}</nowiki>, |
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| − | title = <nowiki>{</nowiki><nowiki>{</nowiki>TextTrail |
+ | title = <nowiki>{</nowiki><nowiki>{</nowiki>TextTrail<nowiki>}</nowiki>: <nowiki>{</nowiki>A<nowiki>}</nowiki> Robust Text Tracking Algorithm In Wild |
Environments<nowiki>}</nowiki>, |
Environments<nowiki>}</nowiki>, |
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booktitle = <nowiki>{</nowiki>Proceedings of the 10th International Conference on |
booktitle = <nowiki>{</nowiki>Proceedings of the 10th International Conference on |
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complex situations starting from only one detection step |
complex situations starting from only one detection step |
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without needing another one to reinitialize the tracking |
without needing another one to reinitialize the tracking |
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| − | model.<nowiki>}</nowiki> |
+ | model.<nowiki>}</nowiki>, |
| + | doi = <nowiki>{</nowiki>10.5220/0005292002680276<nowiki>}</nowiki> |
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<nowiki>}</nowiki> |
<nowiki>}</nowiki> |
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Latest revision as of 17:01, 27 May 2021
- Authors
- Myriam Robert-Seidowsky, Jonathan Fabrizio, Séverine Dubuisson
- Where
- Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISAPP)
- Type
- inproceedings
- Projects
- Olena
- Date
- 2015-03-01
Abstract
In this paper, we propose TextTrail, a robust new algorithm dedicated to text tracking in uncontrolled environments (strong motion of camera and objects, partial occlusions, blur, etc.). It is based on a particle filter framework whose correction step has been improved. Firstwe compare some likelihood functions and introduce a new one that integrates tangent distance. We show that the likelihood function has a strong influence on the text tracking performances. Secondly, we compare our tracker with another and finally present an example of application. TextTrail has been tested on real video sequences and has proven its efficiency. In particular, it can track texts in complex situations starting from only one detection step without needing another one to reinitialize the tracking model.
Documents
Bibtex (lrde.bib)
@InProceedings{ robert-seidowsky.15.visapp,
author = {Myriam Robert-Seidowsky and Jonathan Fabrizio and
S\'everine Dubuisson},
title = {{TextTrail}: {A} Robust Text Tracking Algorithm In Wild
Environments},
booktitle = {Proceedings of the 10th International Conference on
Computer Vision Theory and Applications (VISAPP)},
month = mar,
year = {2015},
pages = {268--276},
abstract = {In this paper, we propose TextTrail, a robust new
algorithm dedicated to text tracking in uncontrolled
environments (strong motion of camera and objects, partial
occlusions, blur, etc.). It is based on a particle filter
framework whose correction step has been improved. First,
we compare some likelihood functions and introduce a new
one that integrates tangent distance. We show that the
likelihood function has a strong influence on the text
tracking performances. Secondly, we compare our tracker
with another and finally present an example of application.
TextTrail has been tested on real video sequences and has
proven its efficiency. In particular, it can track texts in
complex situations starting from only one detection step
without needing another one to reinitialize the tracking
model.},
doi = {10.5220/0005292002680276}
}