{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:00:55Z","timestamp":1762506055309,"version":"3.38.0"},"reference-count":34,"publisher":"SAGE Publications","issue":"3-4","license":[{"start":{"date-parts":[[2013,2,25]],"date-time":"2013-02-25T00:00:00Z","timestamp":1361750400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Information Visualization"],"published-print":{"date-parts":[[2013,7]]},"abstract":"<jats:p> Automatic viewpoint selection algorithms try to optimize the view of a data set to best show its features. They are often based on information theoretic frameworks. Although many algorithms have shown useful results, they often take several seconds to produce a result because they render the scene from a variety of viewpoints and analyze the result. In this article, we propose a new algorithm for volume data sets that dramatically reduces the running time. Our entire algorithm takes less than a second, which allows it to be integrated into real-time volume-rendering applications. The interactive performance is achieved by solving a maximization problem with a small sample of the data set, instead of rendering it from a variety of directions. We compare performance results of our algorithm to state-of-the-art approaches and show that our algorithm achieves comparable results for the resulting viewpoints. Furthermore, we apply our algorithm to multichannel volume data sets. <\/jats:p>","DOI":"10.1177\/1473871612467631","type":"journal-article","created":{"date-parts":[[2013,2,27]],"date-time":"2013-02-27T01:59:30Z","timestamp":1361930370000},"page":"240-256","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["A new approach to interactive viewpoint selection for volume data sets"],"prefix":"10.1177","volume":"12","author":[{"given":"Han Suk","family":"Kim","sequence":"first","affiliation":[{"name":"University of California San Diego, La Jolla, CA, USA"}]},{"given":"Didem","family":"Unat","sequence":"additional","affiliation":[{"name":"Lawrence Berkeley Laboratory, Berkeley, CA, USA"}]},{"given":"Scott B","family":"Baden","sequence":"additional","affiliation":[{"name":"University of California San Diego, La Jolla, CA, USA"}]},{"given":"J\u00fcrgen P","family":"Schulze","sequence":"additional","affiliation":[{"name":"University of California San Diego, La Jolla, CA, USA"}]}],"member":"179","published-online":{"date-parts":[[2013,2,25]]},"reference":[{"first-page":"273","volume-title":"Proceedings of the vision modeling and visualization conference 2001, VMV \u201901","author":"V\u00e1zquez P-P","key":"bibr1-1473871612467631"},{"key":"bibr2-1473871612467631","doi-asserted-by":"publisher","DOI":"10.1109\/VISUAL.2005.1532833"},{"first-page":"185","volume-title":"Eurographics workshop on computational aesthetics in graphics, visualization and imaging","author":"Sbert M","key":"bibr3-1473871612467631"},{"key":"bibr4-1473871612467631","first-page":"495","author":"Takahashi S","year":"2005","journal-title":"Visual Conf IEEE"},{"key":"bibr5-1473871612467631","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2006.137"},{"first-page":"193","volume-title":"IEEE Pacific 2009, visualization symposium","author":"Tao Y","key":"bibr6-1473871612467631"},{"key":"bibr7-1473871612467631","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44842-X_31"},{"key":"bibr8-1473871612467631","doi-asserted-by":"publisher","DOI":"10.1145\/1186822.1073244"},{"key":"bibr9-1473871612467631","unstructured":"Harris C, Stephens M. 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