Scanned Three-Dimensional Model Matching and Comparison Algorithms for Manufacturing Applications

2006 ◽  
Vol 129 (1) ◽  
pp. 190-201 ◽  
Author(s):  
Vahram Avagyan ◽  
Armen Zakarian ◽  
Pravansu Mohanty

In recent years the increased use of 3D scanning hardware has introduced a new type of data to the design and manufacturing field. In many design and manufacturing applications (e.g., part refurbishing or remanufacturing) a scanned 3D model may be provided as an input to a shape matching system to search the database for related or identical models with the purpose of extracting useful information. The introduction of scanned 3D models restricts the use of the CAD-based 3D model search and comparison methods due to significant differences in model representations. The CAD models provide structured and high-level representation of the part features, whereas the scanned 3D models usually come in a polygonal mesh representation, which does not directly reveal engineering features of the part. These differences require new algorithms for comparing the shapes of scanned 3D models, ones that are robust against different scanning technologies and can be adjusted to work with different representations of the models. In this paper, a new approach and algorithms for scanned 3D shape matching and comparison are presented. Given the scanned 3D model as an input the approach first uses general-purpose shape matching methods to identify a small list of likely matches (i.e., candidate models) for more detailed shape comparison. To perform detailed comparison of the shapes each candidate model is geometrically adjusted (i.e., rotated and translated) with the input using one of two new viewpoint algorithms developed in this paper. Once the candidate models are adjusted they are compared to the input to identify the similarities and differences between their shapes. To accomplish this task a new 3D shape matching algorithm is developed. The relevance of the methodology developed in this paper is illustrated with the application of scanned 3D shape matching and comparison algorithms in rapid manufacturing of broken parts.

2011 ◽  
Vol 27 (11) ◽  
pp. 991-1004 ◽  
Author(s):  
M. Attene ◽  
S. Marini ◽  
M. Spagnuolo ◽  
B. Falcidieno

Author(s):  
Adrian Ion ◽  
Nicole M. Artner ◽  
Gabriel Peyre ◽  
Salvador B. Lopez Marmol ◽  
Walter G. Kropatsch ◽  
...  

Author(s):  
Manuele Bicego ◽  
Stefano Danese ◽  
Simone Melzi ◽  
Umberto Castellani

Author(s):  
Jiangping Wang ◽  
Kai Ma ◽  
Vivek Kumar Singh ◽  
Thomas Huang ◽  
Terrence Chen

Author(s):  
Jingsheng Zhang ◽  
Shana Smith

To achieve effective 3D shape retrieval, there is a crucial need for efficient shape matching methods. This paper introduces a new method for 3D shape matching, which uses a simplified octree representation of 3D mesh models. The simplified octree representation was developed to improve time and space efficiency over prior representations. The proposed method also stores octree information in extensible markup language format, rather than in a new proprietary data file type, to facilitate comparing models over the Internet.


2015 ◽  
Vol 37 (12) ◽  
pp. 2361-2373 ◽  
Author(s):  
Xiang Bai ◽  
Song Bai ◽  
Zhuotun Zhu ◽  
Longin Jan Latecki

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