摘要
精细化的城市建筑风格地图已成为古建筑保护、城市规划、旅游资源开发的重要参考依据。但城市建筑众多,信息采集困难,仅靠人工难以实现成图,因此提出了面向街景影像建筑区域匹配的建筑风格地图生成方法。首先,在提取特征建筑风格影像的基础上,结合球形全景影像的空间几何约束和图像特征,通过匹配同名建筑区域构建双像建筑区域点位映射;然后,利用街景采集点到建筑俯视轮廓的方位范围,提出单像建筑区域方位映射,建立街景建筑区域与单体建筑俯视轮廓的空间匹配关系;最后,综合判定各单体建筑的风格属性,生成精细尺度的建筑风格地图。实验结果表明,基于单、双像位置映射的建筑区域匹配正确率分别达80.3%和85.1%,且19类建筑风格地图的分类精确率为55.1%,召回率为76.4%,在一定程度上能反映大范围的城市建筑风格的地理分布特征。
Objectives: Each region has specific characteristics of architectural styles, and a detailed investigation of the geographical distribution of architectural styles is conducive to the protection of historic buildings, the development of special tourism resources and the scientific planning of urban architectural areas.However, the number of urban buildings is large, manual collection and investigation cannot meet the needs of large-scale operations. In recent years, Google and other Internet companies have launched street view images. Street view images are high resolution, containing a full range of urban street views as well as precise location and posture information, which provide a possibility to explore the geographic distribution of urban architectural styles. Therefore, we use deep learning to identify and match the styles of street view building areas, and establish a mapping relationship between the building area images and building outlines,so as to construct the generation method of a large-scale urban architectural style map in detail.Methods:The style identification and map matching of architectural areas in street view images are the key and difficulty in generating urban architectural style maps. Firstly, we extract the building area images of various styles through Faster R-CNN. In order to establish the mapping relationship between building area images and single building outlines, we construct a building location mapping method by matching the same name building area in two adjacent street view images, then the building can be located by forward intersection.Secondly, for the single building image without a same-name area, we also propose a building azimuth mapping method, which combines the spatial azimuth relationship between the street view building area and building outlines in a digital map. The intersection of union(Io U) of the single building image azimuth range and the building outline azimuth range can help match the building area in a street view image and building outlines in a digi
作者
徐虹
王禄斌
方志祥
何明辉
侯学成
左亮
管昉立
熊策
龚毅宇
庞晴霖
张涵
孙树藤
娜迪热·艾麦尔
XU Hong;WANG Lubin;FANG Zhixiang;HE Minghui;HOU Xuecheng;ZUO Liang;GUAN Fangli;XIONG Ce;GONG Yiyu;PANG Qinglin;ZHANG Han;SUN Shuteng;NADIRE Aimaier(School of Urban Construction,Wuhan University of Science and Technology,Wuhan 430065,China;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China)
出处
《武汉大学学报（信息科学版）》
EI
CAS
CSCD
北大核心
2021年第5期659-671,共13页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(41771473)。
关键词
街景影像
建筑风格分类
深度学习
街景影像匹配
建筑视觉定位
street view images
architectural style classification
deep learning
street view image matching
building visual localization
