DocumentCode
46522
Title
3D Object Retrieval With Multitopic Model Combining Relevance Feedback and LDA Model
Author
Biao Leng ; Jiabei Zeng ; Ming Yao ; Zhang Xiong
Author_Institution
Dept. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
Volume
24
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
94
Lastpage
105
Abstract
View-based 3D model retrieval uses a set of views to represent each object. Discovering the complex relationship between multiple views remains challenging in 3D object retrieval. Recent progress in the latent Dirichlet allocation (LDA) model leads us to propose its use for 3D object retrieval. This LDA approach explores the hidden relationships between extracted primordial features of these views. Since LDA is limited to a fixed number of topics, we further propose a multitopic model to improve retrieval performance. We take advantage of a relevance feedback mechanism to balance the contributions of multiple topic models with specified numbers of topics. We demonstrate our improved retrieval performance over the state-of-the-art approaches.
Keywords
feature extraction; image retrieval; relevance feedback; 3D object retrieval; LDA model; latent Dirichlet allocation model; multitopic model; primordial feature extraction; relevance feedback mechanism; view-based 3D model retrieval; Databases; Feature extraction; Shape; Solid modeling; Three-dimensional displays; Vectors; Visualization; 3D object retrieval; multi-topic model; relevance feedback;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2014.2372618
Filename
6960880
Link To Document