TextTrail - A Robust Text Tracking Algorithm In Wild Environments

Myriam Robert-Seidowsky, Jonathan Fabrizio, Séverine Dubuisson


In this paper, we propose TextTrail, a new robust 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 which integrates tangent distance. We show that this likelihood has a strong influence on the text tracking performances. Secondly, we compare our tracker with a similar one and finally an example of application is presented. 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 model.


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Paper Citation

in Harvard Style

Robert-Seidowsky M., Fabrizio J. and Dubuisson S. (2015). TextTrail - A Robust Text Tracking Algorithm In Wild Environments . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 268-276. DOI: 10.5220/0005292002680276

in Bibtex Style

author={Myriam Robert-Seidowsky and Jonathan Fabrizio and Séverine Dubuisson},
title={TextTrail - A Robust Text Tracking Algorithm In Wild Environments},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},

in EndNote Style

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - TextTrail - A Robust Text Tracking Algorithm In Wild Environments
SN - 978-989-758-091-8
AU - Robert-Seidowsky M.
AU - Fabrizio J.
AU - Dubuisson S.
PY - 2015
SP - 268
EP - 276
DO - 10.5220/0005292002680276