View-based techniques for 3D model retrieval

• Main Author: Li, Bo
• Other Authors: Henry Johan
• Format: Theses and Dissertations
• Language: English
• Published: 2012
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
• Online Access: https://hdl.handle.net/10356/50686
• Institution: Nanyang Technological University

With the increase in the number of available 3D models, the ability to accurately and efficiently search for 3D models is crucial in many applications such as Computer-Aided Design (CAD), on-line 3D model shopping and 3D game, movie and animation production. As a result, 3D model retrieval has become an important research area. In recent years, several typical algorithms that extract different types of 3D model features have been proposed. However, 3D model feature supporting multi-modal queries such as 3D models and 2D sketches is an important research direction which has little related work. In addition, 3D normalization is an important process in 3D model retrieval to extract rotation-dependent features and currently there still exists much room in terms of alignment accuracy and consistency. In this work, we propose several algorithms to contribute solutions for the above issues. Motivated by the mechanism of human perception and multi-view vision, together with the retrieval performance comparison of previous retrieval work as well as the verifications of our proposed algorithms, we adopt a view-based approach which extracts features based on the rendered views of a 3D model. The first part of our work is dealing with 3D pose normalization. A novel Minimum Projection Area-based (MPA) alignment method is proposed for pose normalization based on the idea of successively finding two perpendicular principal axes with minimum projection area. Next, we propose a view-based 3D model feature named view context to support both Query-by-Model and Query-by-Sketch retrieval. The view context of a particular view captures the distribution of visual information differences between this view and a set of arranged views. Finally, to improve the retrieval performance on a classified 3Dmodel database, we propose a 3D model retrieval algorithm based on a hybrid 3D shape descriptor and a class-based approach utilizing the existing class information of the database. In conclusion, we have conducted substantial research in several aspects of 3D model retrieval techniques and proposed our solutions by mainly adopting a view-based framework.