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http://dx.doi.org/10.3745/KIPSTA.2003.10A.4.357

Evaluation of shape similarity for 3D models  

Kim, Jeong-Sik (세종대학교 대학원 컴퓨터공학과)
Choi, Soo-Mi (세종대학교 소프트웨어공학과)
Publication Information
The KIPS Transactions:PartA / v.10A, no.4, 2003 , pp. 357-368 More about this Journal
Abstract
Evaluation of shape similarity for 3D models is essential in many areas - medicine, mechanical engineering, molecular biology, etc. Moreover, as 3D models are commonly used on the Web, many researches have been made on the classification and retrieval of 3D models. In this paper, we describe methods for 3D shape representation and major concepts of similarity evaluation, and analyze the key features of recent researches for shape comparison after classifying them into four categories including multi-resolution, topology, 2D image, and statistics based methods. In addition, we evaluated the performance of the reviewed methods by the selected criteria such as uniqueness, robustness, invariance, multi-resolution, efficiency, and comparison scope. Multi-resolution based methods have resulted in decreased computation time for comparison and increased preprocessing time. The methods using geometric and topological information were able to compare more various types of models and were robust to partial shape comparison. 2D image based methods incurred overheads in time and space complexity. Statistics based methods allowed for shape comparison without pose-normalization and showed robustness against affine transformations and noise.
Keywords
3D Model Retrieval; Similarity Measures; Shape Matching;
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