Abdullah Alfarrarjeh, Xiao Yang, A. A. Jabal, S. H. Kim, C. Shahabi
{"title":"Exploring the Spatial-Visual Locality of Geo-tagged Urban Street Images","authors":"Abdullah Alfarrarjeh, Xiao Yang, A. A. Jabal, S. H. Kim, C. Shahabi","doi":"10.1109/MIPR51284.2021.00023","DOIUrl":null,"url":null,"abstract":"Urban street images have a unique property as they capture visual scenes that are distinctive to their geo-graphical regions. Such images are similar to their neighboring ones while dissimilar to faraway images. We refer to this characteristic of images as the spatial visual locality or the spatial locality of similar visual features. This study focuses on geo-tagged urban street images and hypothesizes that those images demonstrate a local similarity in a certain region but a dissimilarity across different regions, and provides different analysis methods to validate the hypothesis. The paper also evaluates the correctness of the hypothesis using three real geo-tagged street images collected from the Google Street View. Our experimental results demonstrate a high locality of similar visual features among urban street images.","PeriodicalId":139543,"journal":{"name":"2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIPR51284.2021.00023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Urban street images have a unique property as they capture visual scenes that are distinctive to their geo-graphical regions. Such images are similar to their neighboring ones while dissimilar to faraway images. We refer to this characteristic of images as the spatial visual locality or the spatial locality of similar visual features. This study focuses on geo-tagged urban street images and hypothesizes that those images demonstrate a local similarity in a certain region but a dissimilarity across different regions, and provides different analysis methods to validate the hypothesis. The paper also evaluates the correctness of the hypothesis using three real geo-tagged street images collected from the Google Street View. Our experimental results demonstrate a high locality of similar visual features among urban street images.