Abstract

3D shape retrieval is a problem of current interest in different fields, especially in the mechanical engineering domain. According to our knowledge, multifeature based techniques achieve the best performance at present. However, the practicability of those methods is badly limited due to the high computational cost. To improve the retrieval efficiency of 3D CAD model, we propose a novel 3D CAD model retrieval algorithm called VSC_WCO which consists of a new 3D shape descriptor named VSC and Weights Combination Optimization scheme WCO. VSC represents a 3D model with three distance distribution histograms based on vertices classification. The weighted sum of L1 norm distances between corresponding distance histograms of two VSC descriptors is regarded as dissimilarity of two models. For higher retrieval accuracy on a classified 3D model database, WCO is proposed based on Particle Swarm Optimization and existing class information. Experimental results on ESB, PSB, and NTU databases show that the discriminative power of VSC is already comparable to or better than several typical shape descriptors. After WCO is employed, the performance of VSC_WCO is similar to the leading methods by all performance metrics and is much better by computational efficiency.

Highlights

  • The development of computer graphics technology gives a birth to the explosion in the number of 3D models which are widely used in many diverse applications

  • To improve the retrieval efficiency of 3D CAD model, we propose a novel 3D CAD model retrieval algorithm called VSC Weights combinations optimization (WCO) which consists of a new 3D shape descriptor named VSC and Weights Combination Optimization scheme WCO

  • To improve the retrieval efficiency for 3D CAD models in a classified 3D model database, we have proposed a 3D model retrieval method called VSC WCO which is based on the proposed 3D shape descriptor VSC and Weights Combination Optimization scheme WCO

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Summary

Introduction

The development of computer graphics technology gives a birth to the explosion in the number of 3D models which are widely used in many diverse applications. More and more 3D model databases are available on the web, such as Princeton Shape Benchmark (PSB) [1], National Taiwan University Shape Benchmark (NTU) [2], and Engineering Shape Benchmark (ESB) [3]. It is very necessary to develop efficient tools for 3D CAD model retrieval. The so-called content-based 3D model retrieval, using the characteristics of 3D model itself, has attracted a lot of research interests [6,7,8,9,10,11,12,13]. The content-based approaches are broadly classified into three categories: shape-based, viewbased, and multifeature based approaches

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