@inproceedings{a9ae7cff8dbb4acb84b2f0766dea2ae2,
title = "Markerless identification and tracking for scalable image database",
abstract = "In this paper we present a novel approach for object identification and tracking in large image datasets. Objects of interest are represented by feature points and descriptors extracted and compared to a set of reference data. An optimized matching paradigm is designed to deal with scalable image databases while keeping a good recognition rate in real-life environment conditions. Experiments are conducted to evaluate the effectiveness of the method and the obtained results demonstrate a true interest of the proposed approach.",
keywords = "Descriptors, identification, realtime, scalable image database, tracking",
author = "Madjid Maidi and Marius Preda and Yassine Lehiani",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.",
year = "2014",
month = jan,
day = "28",
doi = "10.1109/ICIP.2014.7025080",
language = "English",
series = "2014 IEEE International Conference on Image Processing, ICIP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "403--407",
booktitle = "2014 IEEE International Conference on Image Processing, ICIP 2014",
}