Viewpoint-Aware Representation for Sketch-Based 3D Model Retrieval

• Published in: IEEE signal processing letters Vol. 21; no. 8; pp. 966 - 970
• Main Authors: Zou, Changqing, Wang, Changhu, Wen, Yafei, Zhang, Lei, Liu, Jianzhuang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D model retrieval; Benchmarking; Context; Feature extraction; junction-based local feature; Junctions; Mathematical models; Measurement; Query processing; query-to-model distance; Representations; Retrieval; Shape; Signal processing; Sketches; Solid modeling; Three dimensional models; Three-dimensional displays; viewpoint-aware representation
• ISSN: 1070-9908; 1558-2361
• DOI: 10.1109/LSP.2014.2321764

We study the problem of sketch-based 3D model retrieval, and propose a solution powered by a new query-to-model distance metric and a powerful feature descriptor based on the bag-of-features framework. The main idea of the proposed query-to-model distance metric is to represent a query sketch using a compact set of sample views (called basic views) of each model, and to rank the models in ascending order of the representation errors. To better differentiate between relevant and irrelevant models, the representation is constrained to be essentially a combination of basic views with similar viewpoints. In another aspect, we propose a mid-level descriptor (called BOF-JESC) which robustly characterizes the edge information within junction-centered patches, to extract the salient shape features from sketches or model views. The combination of the query-to-model distance metric and the BOF-JESC descriptor achieves effective results on two latest benchmark datasets.