Conference Paper

A New Feature Integration Approach and Its Application to 3D Model Retrieval

Dept. of Comput. Sci. & Inf. Eng., Chung Hua Univ., Hsinchu, Taiwan
DOI: 10.1109/IIH-MSP.2009.255 Conference: Intelligent Information Hiding and Multimedia Signal Processing, 2009. IIH-MSP '09. Fifth International Conference on
Source: DBLP

ABSTRACT In recent years, advanced techniques on digitization and visualization of 3D models have made 3D models as plentiful as images and video. The rapid generation of 3D models has made the development of efficient 3D model retrieval systems become urgently. In this paper, we will propose a feature integration approach in which a weighted distance method is developed to combine the distance evaluated by each individual one of the descriptors. The weight associated with each feature descriptor can be automatically determined according to the retrieval result using each individual feature descriptor. Experiments conducted on the Princeton Shape Benchmark (PSB) database have shown that the proposed feature integration approach provides a promising retrieval result.

0 Bookmarks
 · 
68 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a novel methodology for content-based search and retrieval of 3D objects. After proper positioning of the 3D objects using translation and scaling, a set of functionals is applied to the 3D model producing a new domain of concentric spheres. In this new domain, a new set of functionals is applied, resulting in a descriptor vector which is completely rotation invariant and thus suitable for 3D model matching. Further, weights are assigned to each descriptor, so as to significantly improve the retrieval results. Experiments on two different databases of 3D objects are performed so as to evaluate the proposed method in comparison with those most commonly cited in the literature. The experimental results show that the proposed method is superior in terms of precision versus recall and can be used for 3D model search and retrieval in a highly efficient manner.
    Journal on Advances in Signal Processing 01/2007; DOI:10.1155/2007/23912 · 0.81 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Three dimensional models play an important role in many applications; the problem is how to select the appropriate models from a 3D database rapidly and accurately. In recent years, a variety of shape representations, statistical methods, and geometric algorithms have been proposed for matching 3D shapes or models. In this paper, we propose a 3D shape representation scheme based on a combination of principal plane analysis and dynamic programming. The proposed 3D shape representation scheme consists of three steps. First, a 3D model is transformed into a 2D image by projecting the vertices of the model onto its principal plane. Second, the convex hall of the 2D shape of the model is further segmented into multiple disjoint triangles using dynamic programming. Finally, for each triangle, a projection score histogram and moments are extracted as the feature vectors for similarity searching. Experimental results showed the robustness of the proposed scheme, which resists translation, rotation, scaling, noise, and destructive attacks. The proposed 3D model retrieval method performs fairly well in retrieving models having similar characteristics from a database of 3D models.
    Pattern Recognition 02/2007; DOI:10.1016/j.patcog.2006.06.006 · 2.58 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Classification is one of the basic tasks of data mining in modern database applications including molecular biology, astronomy, mechanical engineering, medical imaging or meteorology. The underlying models have to consider spatial properties such as shape or extension as well as thematic attributes. We introduce 3D shape histograms as an intuitive and powerful similarity model for 3D objects. Particular flexibility is provided by using quadratic form distance functions in order to account for errors of measurement, sampling, and numerical rounding that all may result in small displacements and rotations of shapes. For query processing, a general filter-refinement architecture is employed that efficiently supports similarity search based on quadratic forms. An experimental evaluation in the context of molecular biology demonstrates both, the high classification accuracy of more than 90% and the good performance of the approach.

Full-text (2 Sources)

Download
6 Downloads
Available from
Aug 15, 2014