Name
Abstract | ||
|---|---|---|
This study proposes a method to recognize facades from large-scale urban scenes based on multi-level image features utilizing a recently developed oblique aerial photogrammetry technique. The method involves the use of multi-level image features, a bottom-up feature extraction procedure to produce regions of interest through monoscopic analysis, and then a coarse-to-fine feature matching strategy to characterise and match the regions in a stereoscopic model. Feature extraction from typical urban Manhattan scenes is based on line segments. Windows are re-organised based on the spatial constraints of line segments and the homogeneous structure of the spectrum. Facades as regions of interest are successfully constructed with a remarkable single edge and evidence from windows to get rid of occlusion. Feature matching is hierarchically performed beginning from distinctive facades and regularly distributed windows to the sub-pixel point primitives. The proposed strategy can effectively solve ambiguity and multi-solution problems in the complex urban scene matching process, particularly repetitive and poor-texture facades in oblique view. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3390/rs70810562 | REMOTE SENSING |
Keywords | Field | DocType |
spatial relationship | Oblique projection,Computer vision,Line segment,Photogrammetry,Oblique case,Stereoscopy,Feature (computer vision),Feature extraction,Artificial intelligence,Facade,Geology | Journal |
Volume | Issue | Citations |
7 | 8 | 2 |
PageRank | References | Authors |
0.38 | 11 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiucheng Yang | 1 | 32 | 7.04 |
| Xuebin Qin | 2 | 32 | 7.95 |
| Jun Wang | 3 | 13 | 5.63 |
| Xin Ye | 4 | 25 | 8.36 |
| Qi-ming Qin | 5 | 158 | 49.12 |