• 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