Name
Abstract | ||
|---|---|---|
With the rapid growth of available 3D models in various areas, effective methods to search 3D models are becoming increasingly important. In this paper, we propose a new method for sketch-based 3D model retrieval. Different from current methods that make use of either global or local features, the proposed method uses composite features combining global and local features extracted from representative 2D views of 3D models. The global features, shape strings, represent exterior boundary shape of the views and the local features, improved Pyramid of Histograms of Orientation Gradients (iPHOG), represent their interior details. Specifically, a global feature based filtering step is adopted to select more relevant candidate models to the query sketch and a local feature based process is used to refine chosen candidates. To evaluate the performance of the proposed method with that of other previous ones, we conducted a series of experiments on public standard 3D model databases. Experimental results are presented and indicate the effectiveness of the new approach for sketch-based 3D model retrieval. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11042-017-4446-y | Multimedia Tools Appl. |
Keywords | Field | DocType |
3D model retrieval, Composite feature, Filter, Global feature, Local feature | Histogram,Data mining,Computer vision,Pattern recognition,Computer science,Filter (signal processing),Artificial intelligence,Pyramid,Feature based,Sketch | Journal |
Volume | Issue | ISSN |
77 | 2 | 1573-7721 |
Citations | PageRank | References |
3 | 0.37 | 28 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhua Li | 1 | 19 | 8.06 |
| Hao-Peng Lei | 2 | 4 | 2.41 |
| Shujin Lin | 3 | 77 | 7.74 |
| Guoliang Luo | 4 | 14 | 2.88 |