Abstract
With the development of graphic accelerated hardware and 3D modeling tools, 3D models will be as prevalent as other multimedia data in the future. Thus, effective content-based 3D model retrieval systems are required for emerging needs. Many 3D model retrieval methods have been proposed in recent years. Shape distributions showed superiority over others due to rotation invariance and ease of computation, but the discriminative accuracy is limited for any loss in information. Fuzzy Shape Distributions (FSD) is proposed to improve the retrieval performance of distribution-based methods. First, two improved shape distributions are presented by using the concentric partition and symmetrical partition for 3D models. Second, the two enhanced descriptors are combined with a fuzzy weighted procedure. Experimental results show that the proposed FSD can achieve better retrieval performance. Key words: 3D model retrieval, fuzzy weighted, shape distribution, sequential quadratic programming, content-based.
Highlights
With the development of computer graphics and virtual reality, 3D models are projected to be as prevalent as other multimedia data in the future. 3D models play an important role in several domains such as computeraided design and protein classification
Effective content-based 3D model retrieval systems are required for emerging needs
Experimental results show that the proposed Fuzzy Shape Distributions (FSD) can achieve better retrieval performance
Summary
With the development of computer graphics and virtual reality, 3D models are projected to be as prevalent as other multimedia data in the future. 3D models play an important role in several domains such as computeraided design and protein classification. With the development of computer graphics and virtual reality, 3D models are projected to be as prevalent as other multimedia data in the future. There is an urgent need for an effective content based 3D model retrieval system. The key challenge to a content-based 3D model retrieval system is the extraction of the most representative features of 3D models (Tangelder and Veltkamp, 2004). Bustos et al (2007) surveyed techniques for searching for similar content in 3D object databases and a comparative study of different 3D model retrieval methods was published (Bustos et al, 2004). Iyer et al (2005) classified and compared various 3D shape searching techniques based on shape representations and indicated directions for further research. The performance of the existing algorithms is mainly limited due to two major issues: the degeneracy of
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