Shape Description and Retrieval for 3D Model Search Engine.

摘要

The large number of 3D models on the Internet encourages us to develop 3D model search engines. In this dissertation, we present a 3D model retrieval system using both the 3D model query and the sketch query.;For 3D model query based retrieval system, we propose two new 3D model descriptors, named the Sphere Image and the Bag-of-View-Words (BoVW) descriptor. The Sphere Image is defined as a collection of view features. A viewpoint of a 3D model is regarded as a "pixel": (1) The position of the viewpoint is denoted as the coordinate of the "pixel". (2) The feature descriptor of the projected view is denoted as the value of the "pixel". We also propose a probabilistic graphical model for 3D model matching, and develop a 3D model retrieval system to test our approach. The BoVW descriptor describes a 3D model by measuring the occurrences of its projected views. An adaptive clustering method is applied to reduce the redundancy of the projected views of each 3D model. A 3D model is represented by a multi-resolution histogram, which is combined by several BoVW descriptors at different levels. The codebook is obtained by unsupervised learning. We also propose a new pyramid matching method for 3D model comparison. We have conducted experiments based on the SHape REtrieval Contest (SHREC) 2012 Generic 3D model benchmark and the Princeton Shape Benchmark (PSB). Experimental results indicate that our system outperforms some state-of-the-art 3D model retrieval systems with respect to the retrieval precision and the computational cost.;For sketch query based retrieval system, we propose a Bigger Exposure Opportunity Views (BEOV) descriptor and a Shape-Ring descriptor, for representing the 3D model candidates and the sketch query, respectively. The BEOV descriptor represents a 3D model by several characteristic views, which have more chances to be exposed to people. The Shape-Ring descriptor preserves the features of the contour and the inside detail of the sketch query and the BEOV. Experiments have been conducted based on the SHape REtrieval Contest (SHREC) 2012 and SHREC 2013 sketch track data sets. Our approach outperforms the existing 3D model retrieval methods in terms of the retrieval precision and the computational cost.