{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T19:56:04Z","timestamp":1722369364966},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Streamlines are commonly used in scientific visualization.\nThey are the most used geometric items in\nprimitive-based visualization algorithms. In this paper, a\nmodified version of the farthest point seeding strategy\nstreamline placement is presented. The main advantage\ncompared to the original method is the use of a simple easy\nto implement underlying data structure. The Delaunay triangulation\nused in the original algorithm is heavy and susceptible\nto the calculation robustness errors. The distances\nbetween lines and the localization of the biggest void in\nthe domain are approximated using the Delaunay triangulation.\nThis paper presents an adaptive distance grid\nto model the visualization domain and incorporate anywhere\nthe local distance to all the other streamlines and\nthe boundaries exactly without any approximation. The\nstreamlines are started at the farthest point from all the existing\nones and the domain boundaries. The localization\nof the seed point position is directly accessible via the distance\nadaptive grid. The grid update is direct too, and is\ndone by a greedy algorithm avoiding any additional cost.\nThe obtained results are sufficient, and the extension to\nmulti-resolution is straight and simple.<\/jats:p>","DOI":"10.1515\/comp-2016-0007","type":"journal-article","created":{"date-parts":[[2016,7,27]],"date-time":"2016-07-27T09:54:00Z","timestamp":1469613240000},"page":"91-99","source":"Crossref","is-referenced-by-count":1,"title":["Adaptive Distance Grid Based Algorithm for\nFarthest Point Seeding Streamline Placement"],"prefix":"10.1515","volume":"6","author":[{"given":"Abdelkrim","family":"Mebarki","sequence":"first","affiliation":[{"name":"D\u00e9partement d\u2019Informatique \u2013 Facult\u00e9 des Math\u00e9matiques et Informtique , Universit\u00e9 des Sciences et de la Technologie d\u2019Oran \u2013 Mohamed Boudiaf Oran , 31015 El M\u2019Naouer , Algeria"}]}],"member":"374","published-online":{"date-parts":[[2016,7,11]]},"container-title":["Open Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/view\/journals\/comp\/6\/1\/article-p91.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2016-0007\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2016-0007\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T08:57:13Z","timestamp":1651049833000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2016-0007\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,2,22]]},"published-print":{"date-parts":[[2016,1,1]]}},"alternative-id":["10.1515\/comp-2016-0007"],"URL":"https:\/\/doi.org\/10.1515\/comp-2016-0007","relation":{},"ISSN":["2299-1093"],"issn-type":[{"value":"2299-1093","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,1]]}}}