维普中文期刊产品整合服务

Data-driven approach to learning salience models of indoor landmarks by using genetic programming

查看全文 作　　者：Xuke [1]Hu;Lei [2,3]Ding;Jianga [2,3]Shang;Hongchao [4]Fan;Tessio [1]Novack;Alexey [1]Noskov;Alexander [1]Zipfa 高影响力作者 机构地区：[1]GIScience Research Group,Institute of Geography,Heidelberg University,Heidelberg,Germany;[2]School of Geography and Information Engineering,China University of Geosciences,Wuhan,People’s Republic of China;[3]National Engineering Research Center for Geographic Information System,Wuhan,People’s Republic of China;[4]Department of Civil and Environmental Engineering,Norwegian University of Science and Technology,Trondheim,Norway高影响力机构 出　　处：《International Journal of Digital Earth》索引2020年第13卷第11期,共28页高影响力期刊 基　　金：the National Key R&D Program of China(No.2016YFB0502203);the National Natural Science Foundation of China(Grant No.41271440);the China Scholarship Council. 摘　　要：In landmark-based way-finding,determining the most salient landmark from several candidates at decision points is challenging.To overcome this problem,current approaches usually rely on a linear model to measure the salience of landmarks.However,linear models are not always able to establish an accurate quantitative relationship between the attributes of a landmark and its perceived salience.Furthermore,the numbers of evaluated scenes and of volunteers participating in the testing of these models are often limited.With the aim of overcoming these gaps,we propose learning a non-linear salience model by means of genetic programming.We compared our proposed approach with conventional algorithms by using photographs of two hundred test scenes collected from two shopping malls.Two hundred volunteers who were not in these environments were asked to answer questionnaires about the collected photographs.The results from this experiment showed that in 76%of the cases,the most salient landmark(according to the volunteers’perception)was correctly predicted by our proposed approach.This accuracy rate is considerably higher than the ones achieved by conventional linear models. 关 键 词：Indoor navigation landmarks salience model genetic programming
相关文献

参考文献(30)

引证文献(5)

网站首页 | 关于我们 | 联系我们 | 产品服务 | 客服中心 | 广告服务 | 版权声明 | 网站联盟 | 友情链接 | 售卡网点

版权所有© 渝B2-20050021-1　渝公网安备 50019002500403号　违法和不良信息举报中心

互联网出版许可证 新出网证(渝)字10号 全国400电话 - 免长途话费