{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:13:01Z","timestamp":1776085981385,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T00:00:00Z","timestamp":1560902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1605254"],"award-info":[{"award-number":["U1605254"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61728206"],"award-info":[{"award-number":["61728206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Maintaining the high visual recognizability of traffic signs for traffic safety is a key matter for road network management. Mobile Laser Scanning (MLS) systems provide efficient way of 3D measurement over large-scale traffic environment. This paper presents a quantitative visual recognizability evaluation method for traffic signs in large-scale traffic environment based on traffic recognition theory and MLS 3D point clouds. We first propose the Visibility Evaluation Model (VEM) to quantitatively describe the visibility of traffic sign from any given viewpoint, then we proposed the concept of visual recognizability field and Traffic Sign Visual Recognizability Evaluation Model (TSVREM) to measure the visual recognizability of a traffic sign. Finally, we present an automatic TSVREM calculation algorithm for MLS 3D point clouds. Experimental results on real MLS 3D point clouds show that the proposed method is feasible and efficient.<\/jats:p>","DOI":"10.3390\/rs11121453","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T10:43:32Z","timestamp":1560941012000},"page":"1453","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Automated Visual Recognizability Evaluation of Traffic Sign Based on 3D LiDAR Point Clouds"],"prefix":"10.3390","volume":"11","author":[{"given":"Shanxin","family":"Zhang","sequence":"first","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China"},{"name":"Xizang Key Laboratory of Optical Information Processing and Visualization Technology, Information Engineering College, Xizang Minzu University, Xianyang 712000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6075-796X","authenticated-orcid":false,"given":"Cheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lili","family":"Lin","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenglu","family":"Wen","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenhui","family":"Yang","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhemin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Geography and Environmental Management University of Waterloo, Waterloo, ON N2L 3G1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.neulet.2010.08.059","article-title":"Cognitive processing of traffic signs in immersive virtual reality environment: An ERP study","volume":"485","author":"Liu","year":"2010","journal-title":"Neurosci. 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