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However, automatic evaluation of video material is not reliable enough, especially when it comes to semantic abstraction from the video signal. In this article, we describe the video visual analytics method that combines the complementary strengths of human recognition and machine processing. After inspecting the challenges of scalable video analysis, we derive the main components of visual analytics for video data. Based on these components, we present our video visual analytics system that has its origins in our IEEE VAST Challenge 2009 participation. <\/jats:p>","DOI":"10.1177\/1473871613488571","type":"journal-article","created":{"date-parts":[[2013,6,6]],"date-time":"2013-06-06T03:30:51Z","timestamp":1370489451000},"page":"10-26","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":15,"title":["Scalable video visual analytics"],"prefix":"10.1177","volume":"14","author":[{"given":"Benjamin","family":"H\u00f6ferlin","sequence":"first","affiliation":[{"name":"Universit\u00e4t Osnabr\u00fcck, Osnabr\u00fcck, Germany"}]},{"given":"Markus","family":"H\u00f6ferlin","sequence":"additional","affiliation":[{"name":"Universit\u00e4t Stuttgart, Stuttgart, Germany"}]},{"given":"Gunther","family":"Heidemann","sequence":"additional","affiliation":[{"name":"Universit\u00e4t Osnabr\u00fcck, Osnabr\u00fcck, Germany"}]},{"given":"Daniel","family":"Weiskopf","sequence":"additional","affiliation":[{"name":"Universit\u00e4t Stuttgart, Stuttgart, Germany"}]}],"member":"179","published-online":{"date-parts":[[2013,6,5]]},"reference":[{"key":"bibr1-1473871613488571","unstructured":"Cisco. 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