Shape based 3D model retrieval without query
Proceedings of the 6th ACM international conference on Image and video retrieval
Stratified helix information of medial-axis-points matching for 3D model retrieval
Proceedings of the international workshop on Workshop on multimedia information retrieval
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
Shape google: Geometric words and expressions for invariant shape retrieval
ACM Transactions on Graphics (TOG)
On volume distribution features based 3d model retrieval
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
Efficient object categorization with the surface-approximation polynomials descriptor
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
Hi-index | 0.00 |
In this paper, we present an approach based on 2D slices for measuring similarity between 3D models. The key idea is to represent the 3D model by a series of slices along certain directions so that the shape-matching problem between 3D models is transformed into similarity measuring between 2D slices. Here, we have to deal with the following problems: selection of cutting directions, cutting methods, and similarity measuring. To solve these problems, some strategies and rules are proposed. Firstly, a maximum normal distribution method is presented to get three ortho-axes that coincide better with human visual perception mechanism. Secondly, a cutting method is given which can be used to get a series of slices composed of a set of closed polygons. Thirdly, on the basis of 3D shape distribution method presented by Robert et al., we develop a 2D shape distribution method to measure the similarity between the 2D slices. Some experiments are given in this paper to show the validity of this method for 3D model retrieval.