2D-3D fusion for layer decomposition of urban facades
文献类型：会议论文
| 作者 | Li, Yangyan; Zheng, Qian; Sharf, Andrei; Cohen-Or, Daniel; Chen, Baoquan; Mitra, Niloy J. |
| 出版日期 | 2011 |
| 会议名称 | 2011 IEEE International Conference on Computer Vision |
| 会议地点 | Barcelona, SPAIN |
| 英文摘要 | We present a method for fusing two acquisition modes, 2D photographs and 3D LiDAR scans, for depth-layer decomposition of urban facades. The two modes have complementary characteristics: point cloud scans are coherent and inherently 3D, but are often sparse, noisy, and incomplete; photographs, on the other hand, are of high resolution, easy to acquire, and dense, but view-dependent and inherently 2D, lacking critical depth information. In this paper we use photographs to enhance the acquired LiDAR data. Our key observation is that with an initial registration of the 2D and 3D datasets we can decompose the input photographs into rectified depth layers. We decompose the input photographs into rectangular planar fragments and diffuse depth information from the corresponding 3D scan onto the fragments by solving a multi-label assignment problem. Our layer decomposition enables accurate repetition detection in each planar layer, using which we propagate geometry, remove outliers and enhance the 3D scan. Finally, the algorithm produces an enhanced, layered, textured model. We evaluate our algorithm on complex multi-planar building facades, where direct autocorrelation methods for repetition detection fail. We demonstrate how 2D photographs help improve the 3D scans by exploiting data redundancy, and transferring high level structural information to (plausibly) complete large missing regions. © 2011 IEEE.(24 refs) |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3595]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2011 |
| 推荐引用方式 GB/T 7714 | Li, Yangyan,Zheng, Qian,Sharf, Andrei,et al. 2D-3D fusion for layer decomposition of urban facades[C]. 见:2011 IEEE International Conference on Computer Vision. Barcelona, SPAIN. |
入库方式： OAI收割
来源：深圳先进技术研究院
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