Skip to Main content Skip to Navigation
Journal articles

Relevance Feedback in Content-based 3D Object Retrieval A Comparative Study

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.
Document type :
Journal articles
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download

https://hal.inria.fr/hal-00758974
Contributor : Panagiotis Papadakis <>
Submitted on : Friday, November 30, 2012 - 11:29:32 AM
Last modification on : Wednesday, September 26, 2018 - 4:32:03 PM
Long-term archiving on: : Friday, March 1, 2013 - 3:45:08 AM

File

Papadakis-CAD_A08-Relevance-Fe...
Publisher files allowed on an open archive

Identifiers

Citation

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, ⟨10.3722/cadaps.2008.753-763⟩. ⟨hal-00758974⟩

Share

Metrics

Record views

160

Files downloads

540