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Local feature extraction and matching partial objects
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|Title: ||Local feature extraction and matching partial objects|
|Authors: ||Bespalov, Dmitriy|
Regli, William C.
|Keywords: ||Partial Matching;Shape Matching;Feature Extraction|
|Issue Date: ||7-Sep-2006|
|Publisher: ||Elsevier Science B.V.|
|Citation: ||Computer-Aided Design, 38(9): pp. 1020-1037.|
|Abstract: ||A primary shortcoming of existing techniques for 3D model matching is the reliance on global information
of model’s structure. Models are matched in their entirety, depending on overall topology and
geometry information. A current open challenge is how to perform partial matching. Partial matching
is important for finding similarities across part models with different global shape properties and for
segmentation and matching of data acquired from 3D scanners.
This paper presents a Scale-Space feature extraction technique based on recursive decomposition of
polyhedral surfaces into surface patches. The experimental results presented in this paper suggest that
this technique can potentially be used to perform matching based on local model structure. In our previous
work, Scale-Space decomposition has been successfully used to extract features from mechanical
artifacts. Scale-Space techniques can be parameterized to generate decompositions that correspond to
manufacturing, assembly or surface features relevant to mechanical design. One application of these
technique is to support matching and content-based retrieval of solid models.
This paper shows how a Scale-Space technique can extract features that are invariant with respect to
the global structure of the model as well as small perturbations that 3D laser scanning process introduce.
In order to accomplish this, we introduce a new distance function defined on triangles instead of points.
Believe this technique offers a new way to control the feature decomposition process, which results in
extraction of features that are more meaningful from an engineering view point.
The new technique is computationally practical for use in indexing large models. Examples are
provided that demonstrate effective feature extraction on 3D laser scanned models. In addition, a simple
sub-graph isomorphism algorithm was used to show that the feature adjacency graphs obtained through
feature extraction, are meaningful descriptors of 3D CAD objects.
All of the data used in the experiments for this work is freely available at:
|Appears in Collections:||Faculty Research and Publications (Comp Sci)|
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