Authors:
Fattah Alizadeh
and
Alistair Sutherland
Affiliation:
Dublin City University, Ireland
Keyword(s):
3D Model Retrieval, Charge Density Distribution, Shape Descriptor, Non-rigid Objects.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
Abstract:
Defining a robust shape descriptor is an enormous challenge in the 3D model retrieval domain. Therefore, great deals of research have been conducted to propose new shape descriptors which meet the retrieving criteria. This paper proposes a new shape descriptor based on the distribution of electrical charge which holds valuable characteristics such as insensitivity to translation, sale and rotation, robustness to noise as well as simplification operation. After extracting the canonical form representation of the models, they are treated as surfaces placed in a free space and charge Q is distributed over them. Following to calculating the amount of charge on each face of the model, a set of concentric spheres enclose the model and the total amount of distributed charge between the adjacent spheres on the model’s surface generates the Charge Distribution Descriptor (CDD). A beneficial two-phase description using the number of Charged-Dense Patches for each model is utilized to boost th
e discrimination power of the system. The strength of our approach is verified using experiments on the McGill dataset. The results demonstrate higher ability of our system compared to other well-known approaches.
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