 |
 |
|
|
| inria-00436742, version 1 |
 |
|
|
|
| Voir la fiche détaillée |  BibTeX EndNote TEI RefWorks |
|
|
|||||||
| IEEE Int. Conf. on Image Processing, ICIP'09 (2009) |
|
| This paper proposes a new way to achieve feature point tracking using the entropy of the image. Sum of Squared Differences (SSD) is widely considered in differential trackers such as the KLT. Here, we consider another metric called Mutual Information (MI), which is far less sensitive to changes in the lighting condition and to a wide class of non-linear image transformation. Since mutual-information is used as an energy function to be maximized to track each points, a new feature selection, which is optimal for this metric, is proposed. Results under various complex conditions are presented. Comparison with the classical KLT tracker are proposed. |
|
|
|
|
|
|
|
|
|
| a – | |
| b – | |
| 1 : | LAGADIC (INRIA - IRISA) |
|
CNRS : UMR6074 – INRIA – Université de Rennes 1 |
|
|
|
|
|
|
|
|
|
| Domaine | : | Informatique/Robotique |
| inria-00436742, version 1 | |
| http://hal.inria.fr/inria-00436742/fr/ | |
| oai:hal.inria.fr:inria-00436742_v1 | |
| Contributeur : Eric Marchand | |
| Déposé pour le compte de : | |
| Soumis le : Vendredi 27 Novembre 2009, 16:42:53 | |
| Dernière modification le : Lundi 30 Novembre 2009, 10:01:38 | |
