Abstract
A new 3D model retrieval approach is proposed by using multi-instance to understand 3D models, while each object in a 3D model is called instance. For visually connected components are not geometrically connected, we present a two-stage multi-instance generation algorithm. The first stage is to compute connected components from a mesh model. The second stage is to merge connected components by testing intersections among their axis-aligned bounding boxes. And then shape descriptor is extracted for each instance and the similarity between 3D models is measured by means of instances' shape descriptors. Experimental results show that our method has better performance than the traditional 3D model retrieval approach.
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