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A framework for 3D model reconstruction in reverse engineering
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AI
DOI：10.1016/j.cie.2012.07.009.png)
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Abstract
En 中文
We present a framework for 3D model reconstruction, which has potential applications to a spectrum of engineering problems with impacts on rapid design and prototyping, shape analysis, and virtual reality. The framework, composed of four main components, provides a systematic solution to reconstruct geometric model from the surface mesh of an existing object. First, the input mesh is pre-processed to filter out noise. Second, the mesh is partitioned into segments to obtain individual geometric feature patches. Then, two integrated solutions, namely solid feature based strategy and surface feature based strategy, are exploited to reconstruct primitive features from the segmented feature patches. Finally, the modeling operations, such as solid boolean and surface trimming operations, are performed to assemble the primitive features into the final model. The concepts of feature, constraint and modeling history are introduced into the entire reconstruction process so that the design intents are retrieved and exhibited in the final model with geometrical accuracy, topological consistency and flexible editability. A variety of industrial parts have been tested to illustrate the effectiveness and robustness of our framework. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Model reconstruction
Mesh denoising
Mesh segmentation
Feature reconstruction
Reverse engineering
Journal
IF:
6.5
Papers:
1.0W
Citations:
3.8W
