Five Challenges for Intelligent Cinematography and Editing

dc.contributor.author	Ronfard, Rémi	en_US
dc.contributor.editor	William Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfard	en_US
dc.date.accessioned	2017-04-22T17:13:03Z
dc.date.available	2017-04-22T17:13:03Z
dc.date.issued	2017
dc.identifier.isbn	978-3-03868-031-4
dc.identifier.issn	2411-9733
dc.identifier.uri	http://dx.doi.org/10.2312/wiced.20171069
dc.identifier.uri	https://diglib.eg.org:443/handle/10.2312/wiced20171069
dc.description.abstract	In this position paper, we propose five challenges for advancing the state of the art in intelligent cinematography and editing by taking advantage of the huge quantity of cinematographic data (movies) and metadata (movie scripts) available in digital formats. This suggests a data-driven approach to intelligent cinematography and editing, with at least five scientific bottlenecks that need to be carefully analyzed and resolved.we briefly describe them and suggest some possible avenues for future research in each of those new directions.	en_US
dc.publisher	The Eurographics Association	en_US
dc.subject	I.2.10 [Vision and Scene Understanding]
dc.subject
dc.subject	I.3.3 [Computer Graphics]
dc.title	Five Challenges for Intelligent Cinematography and Editing	en_US
dc.description.seriesinformation	Eurographics Workshop on Intelligent Cinematography and Editing
dc.description.sectionheaders	Styles and Challenges
dc.identifier.doi	10.2312/wiced.20171069
dc.identifier.pages	37-41