IEEE Trans Image Process. 2015 Jan;24(1):94-105. doi: 10.1109/TIP.2014.2372618. Epub 2014 Nov 20.
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.
基于视图的 3D 模型检索使用一组视图来表示每个对象。在 3D 对象检索中,发现多个视图之间的复杂关系仍然具有挑战性。最近潜在狄利克雷分配(LDA)模型的进展促使我们提出将其用于 3D 对象检索。这种 LDA 方法探索了这些视图提取的原始特征之间隐藏的关系。由于 LDA 仅限于固定数量的主题,我们进一步提出了多主题模型来提高检索性能。我们利用相关性反馈机制来平衡具有指定数量主题的多个主题模型的贡献。我们展示了我们在最新方法上的改进检索性能。