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Coupling ground-level panoramas and aerial imagery for change detection

Coupling ground-level panoramas and aerial imagery for change detection

作     者:Nehla Ghouaiel Sébastien Lefèvre 

作者机构:Institute of Research in Computer Science and Random SystemsUniversitéde Bretagne-SudUMR 6074 IRISAVannesFrance 

出 版 物:《Geo-Spatial Information Science》 (地球空间信息科学学报(英文))

年 卷 期:2016年第19卷第3期

页      面:222-232页

核心收录:

学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

主  题:Image analysis remote sensing change detection crowdsourcing mobile mapping panoramic photos 

摘      要:Geographic landscapes in all over the world may be subject to rapid changes induced,for instance,by urban,forest,and agricultural *** such kind of changes is usually achieved through remote ***,obtaining regular and up-to-date aerial or satellite images is found to be a high costly process,thus preventing regular updating of land cover ***,in this paper,we propose a low-cost solution based on the use of groundlevel geo-located landscape panoramic photos providing high spatial resolution information of the *** photos can be acquired from various sources:digital cameras,smartphone,or even web ***,since the acquisition is performed at the ground level,the users’immediate surroundings,as sensed by a camera device,can provide information at a very high level of precision,enabling to update the land cover type of the geographic *** the described herein method,we propose to use inverse perspective mapping(inverse warping)to transform the geo-tagged ground-level 360◦photo onto a top-down view as if it had been acquired from a nadiral aerial *** re-projected,the warped photo is compared to a previously acquired remotely sensed image using standard techniques such as *** differences in orientation,resolution,and geographical extent between the top-down view and the aerial image are addressed through specific processing steps(***).Experiments on publicly available data-sets made of both ground-level photos and aerial images show promising results for updating land cover maps with mobile ***,the proposed approach contributes to the crowdsourcing efforts in geo-information processing and mapping,providing hints on the evolution of a landscape.

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