Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/3560
Title: MuLVAT: a video annotation tool based on XML-dictionaries and shot clustering
Authors: Tsapatsoulis, Nicolas 
Kounoudes, Anastasis 
Theodosiou, Zenonas 
metadata.dc.contributor.other: Κουνούδης, Αναστάσιος
Τσαπατσούλης, Νικόλας
Θεοδοσίου, Ζήνωνας
Major Field of Science: Social Sciences
Field Category: Media and Communications
Keywords: Computer science;Back propagation (Artificial intelligence);Computer graphics;Multimedia systems;Neural networks;Semantics;Video recording;XML (Document markup language)
Issue Date: 2009
Source: Artificial neural networks – ICANN 2009: 19th international conference, Limassol, Cyprus, September 14-17, 2009, Proceedings, Part II, Pages 913-922
Abstract: Recent advances in digital video technology have resulted in an explosion of digital video data which are available through the Web or in private repositories. Efficient searching in these repositories created the need of semantic labeling of video data at various levels of granularity, i.e., movie, scene, shot, keyframe, video object, etc. Through multilevel labeling video content is appropriately indexed, allowing access from various modalities and for a variety of applications. However, despite the huge efforts for automatic video annotation human intervention is the only way for reliable semantic video annotation. Manual video annotation is an extremely laborious process and efficient tools developed for this purpose can make, in many cases, the true difference. In this paper we present a video annotation tool, which uses structured knowledge, in the form of XML dictionaries, combined with a hierarchical classification scheme to attach semantic labels to video segments at various level of granularity. Video segmentation is supported through the use of an efficient shot detection algorithm; while shots are combined into scenes through clustering with the aid of a Genetic Algorithm scheme. Finally, XML dictionary creation and editing tools are available during annotation allowing the user to always use the semantic label she/he wishes instead of the automatically created ones
URI: https://hdl.handle.net/20.500.14279/3560
ISBN: 978-3-642-04276-8 (print)
ISSN: 978-3-642-04277-5 (online)
DOI: 10.1007/978-3-642-04277-5_92
Rights: © 2009 Springer Berlin Heidelberg
Type: Book Chapter
Affiliation : Cyprus University of Technology 
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

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