Abstract : In this paper, we present a comparative study that concerns relevance feedback (RF) algorithms in the context of content-based 3D object retrieval. In this study, we employ RF algorithms which range from query modification and multiple queries to one-class support vector machines (SVM). Furthermore, we employ pseudo relevance feedback (PRF) and show that it can considerably improve the performance of content-based retrieval. Our comparative study is based upon extensive experiments that take into account datasets containing generic as well as CAD models.
https://hal.inria.fr/hal-00758974
Contributeur : Panagiotis Papadakis
<>
Soumis le : vendredi 30 novembre 2012 - 11:29:32
Dernière modification le : mercredi 26 septembre 2018 - 16:32:03
Document(s) archivé(s) le : vendredi 1 mars 2013 - 03:45:08
Panagiotis Papadakis, Ioannis Pratikakis, Trafalis Theodore, Theoharis Theoharis, Stavros Perantonis. Relevance Feedback in Content-based 3D Object Retrieval A Comparative Study. Computer-Aided Design and Applications, CAD Solutions LLC (imprimé) and Taylor & Francis Online (en ligne), 2008, 〈http://cadanda.homestead.com/CAD_5_5__753-763.pdf〉. 〈10.3722/cadaps.2008.753-763〉. 〈hal-00758974〉
