Title :
Shape-based 3D model retrieval
Author :
Song, Jeong-Jun ; Golshani, Forouzan
Author_Institution :
Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA
Abstract :
Two feature extraction methods for shape similarity based retrieval of 3D object models are presented. The proposed methods, which result in more effective and robust techniques for searching 3D models by similarity, support two essential query modes, namely, query by 3D model and query by 2D image. Our feature extraction scheme is inspired by observation of human behavior in recognizing 3D objects in practice. The process of extracting spatial arrangement from a 3D object surface and 2D shape features from projection images are achieved by adopting curvature distribution of the model surfaces and Fourier descriptors of the projection images.
Keywords :
Fourier transforms; feature extraction; image retrieval; solid modelling; visual databases; 2D shape features; 3D object model; 3D object surface; Fourier descriptors; curvature distribution; feature extraction; model surfaces; projection images; query processing; shape similarity based retrieval; shape-based 3D model retrieval; spatial arrangement extraction; Computer graphics; Data mining; Feature extraction; Information retrieval; Multimedia systems; Object recognition; Robustness; Shape; Solid modeling; Spatial databases;
Conference_Titel :
Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
Print_ISBN :
0-7695-2038-3
DOI :
10.1109/TAI.2003.1250251