Name
Abstract | ||
|---|---|---|
3D object recognition has attracted considerable research in computer vision and computer graphics. In this paper, we draw attentions from neurophysiological research that line drawings trigger a neural response similar to natural color images, and propose a line-drawing-based 3D object recognition method. The contribution of the proposed method includes a feature defined for line drawings and a similarity metric for object recognition. Experimental results on McGill 3D shape benchmark show that the proposed method has the best performance when compared to five classic 3D object recognition methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-34263-9_19 | CVM |
Keywords | DocType | Citations |
object recognition,benchmark show,considerable research,computer vision,object recognition method,best performance,computer graphics,line drawing,neurophysiological research,proposed method | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong-Jin Liu | 1 | 837 | 72.83 |
| qiufang fu | 2 | 35 | 1.98 |
| Ye Liu | 3 | 66 | 3.38 |
| Xiaolan Fu | 4 | 786 | 60.72 |