Literature DB >> 17218743

Pose-oblivious shape signature.

Ran Gal1, Ariel Shamir, Daniel Cohen-Or.   

Abstract

A 3D shape signature is a compact representation for some essence of a shape. Shape signatures are commonly utilized as a fast indexing mechanism for shape retrieval. Effective shape signatures capture some global geometric properties which are scale, translation, and rotation invariant. In this paper, we introduce an effective shape signature which is also pose-oblivious. This means that the signature is also insensitive to transformations which change the pose of a 3D shape such as skeletal articulations. Although some topology-based matching methods can be considered pose-oblivious as well, our new signature retains the simplicity and speed of signature indexing. Moreover, contrary to topology-based methods, the new signature is also insensitive to the topology change of the shape, allowing us to match similar shapes with different genus. Our shape signature is a 2D histogram which is a combination of the distribution of two scalar functions defined on the boundary surface of the 3D shape. The first is a definition of a novel function called the local-diameter function. This function measures the diameter of the 3D shape in the neighborhood of each vertex. The histogram of this function is an informative measure of the shape which is insensitive to pose changes. The second is the centricity function that measures the average geodesic distance from one vertex to all other vertices on the mesh. We evaluate and compare a number of methods for measuring the similarity between two signatures, and demonstrate the effectiveness of our pose-oblivious shape signature within a 3D search engine application for different databases containing hundreds of models.

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Year:  2007        PMID: 17218743     DOI: 10.1109/TVCG.2007.45

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  5 in total

1.  Robust principal axes determination for point-based shapes using least median of squares.

Authors:  Yu-Shen Liu; Karthik Ramani
Journal:  Comput Aided Des       Date:  2009-04-01       Impact factor: 3.027

2.  IDSS: deformation invariant signatures for molecular shape comparison.

Authors:  Yu-Shen Liu; Yi Fang; Karthik Ramani
Journal:  BMC Bioinformatics       Date:  2009-05-22       Impact factor: 3.169

3.  Fast and robust shape diameter function.

Authors:  Shuangmin Chen; Taijun Liu; Zhenyu Shu; Shiqing Xin; Ying He; Changhe Tu
Journal:  PLoS One       Date:  2018-01-26       Impact factor: 3.240

4.  Using diffusion distances for flexible molecular shape comparison.

Authors:  Yu-Shen Liu; Qi Li; Guo-Qin Zheng; Karthik Ramani; William Benjamin
Journal:  BMC Bioinformatics       Date:  2010-09-24       Impact factor: 3.169

5.  Three dimensional shape comparison of flexible proteins using the local-diameter descriptor.

Authors:  Yi Fang; Yu-Shen Liu; Karthik Ramani
Journal:  BMC Struct Biol       Date:  2009-05-12
  5 in total

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