| 引用本文: | 何楚,杨芳,石博,徐新,廖明生.基于足迹图模型的立体路网提取[J].哈尔滨工业大学学报,2013,45(10):111.DOI:10.11918/j.issn.0367-6234.2013.10.020 |
| HE Chu,YANG Fang,SHI Bo,XU Xin,LIAO Mingsheng.Stereoscopic road network extraction based on footprint graph model[J].Journal of Harbin Institute of Technology,2013,45(10):111.DOI:10.11918/j.issn.0367-6234.2013.10.020 |
|
| 摘要: |
| 为了改善足迹跟踪算法在夹角较小的交叉路口容易出现将两足尖合并和不易检测波谷的问题,提出了一种新的立体路网提取算法．算法分为3个步骤:首先用足迹跟踪算法提取道路基元,然后在足迹图结构上建立道路模型,最后通过立体反演层次推理实现道路分层．结果表明:该算法通过对波峰合并的角度选择和波谷检测的偏差校正提高了道路基元提取的准确性,并结合立体反演推理算法实现了道路连接、高度设置和分层．最后在Google Earth提供的真实数据上进行实验验证了该算法能有效地体现立体交叉路口的层次,并能保证提取出来的道路的正确性、完整性． |
| 关键词: 足迹跟踪 立体路网 交叉路口 道路提取 层次推理 |
| DOI：10.11918/j.issn.0367-6234.2013.10.020 |
| 分类号: |
| 基金项目:国家重点基础研究发展计划项目(2013CB733404);国家自然科学基金资助项目(2,6);中国博士后科学基金资助(2011118); 中国博士后科学基金特别资助(2012T50671). |
|
| Stereoscopic road network extraction based on footprint graph model |
|
HE Chu1,2, YANG Fang1, SHI Bo1, XU Xin1, LIAO Mingsheng2
|
|
(1. Electronic Information School, Wuhan University, 430072 Wuhan,China; 2. The State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, 430072 Wuhan,China)
|
| Abstract: |
| A new three-step method called stereoscopic intersection extraction based on footprint graph model is proposed in this paper. Firstly, the primitives are extracted by footprint, then the road model is built based on the graph of primitives, finally, the road lamination is realized by referring and reasoning. Though the footprint algorithm presented by Hu can be used to extract road primitives, there exist two problems, one is that two toes which are adjacent can be easily considered as one toe, and the other is that troughs are not likely to be detected, we solved these two problems by making some improvements. Then we use stereoscopic inferring algorithm to link the roads, set the heights of the roads and realize lamination. At last, we experiment on the dataset of Google earth, as a result, this algorithm can reflect the levels of the roads effectively, what’s more, the correctness being guaranteed, this algorithm still has strong robustness. |
| Key words: footprint stereoscopic road network intersection road extraction level inference |
