Non-sequential multiscale content-based video decomposition

Doulamis, N; Doulamis, A

dc.contributor.author	Doulamis, N	en
dc.contributor.author	Doulamis, A	en
dc.date.accessioned	2014-03-01T01:22:50Z
dc.date.available	2014-03-01T01:22:50Z
dc.date.issued	2005	en
dc.identifier.issn	0165-1684	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16674
dc.subject	Hierarchical summarization	en
dc.subject	MPEG-7	en
dc.subject	Video decomposition	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Algorithms	en
dc.subject.other	Computational complexity	en
dc.subject.other	Graph theory	en
dc.subject.other	Image quality	en
dc.subject.other	Optical resolving power	en
dc.subject.other	Stochastic programming	en
dc.subject.other	Hierarchical summarization	en
dc.subject.other	MPEG-7	en
dc.subject.other	Video decomposition	en
dc.subject.other	Video files	en
dc.subject.other	Content based retrieval	en
dc.title	Non-sequential multiscale content-based video decomposition	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.sigpro.2004.10.004	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.sigpro.2004.10.004	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	In this paper, a multiscale content-based video decomposition scheme is presented for efficient non-linear (non-sequential) organization of the video visual content. In particular, each video file is analyzed in a multiscale structure of different ""content resolution levels"", creating a hierarchy from the lowest (coarse) to the highest (fine) resolution. The scheme resembles the progressive transmission of still images, where instead of transmitting the image sequentially at a full resolution, by scanning it line by line, a lower image resolution is first delivered and then, the image quality gradually enhances so that the user is able at any time to see a preview of the image content. The proposed video decomposition is represented as a graph structure, each level of which corresponds to a particular content resolution, while the graph-nodes the respective regions that the content is analyzed at this level. Transitions among nodes of the same level are also permitted. The number of nodes at a given level expresses the degree of detail that the content at this level is analyzed. This number is estimated by minimizing the average transmitted information, required for localizing a video segment of interest and also takes into account the content complexity. Quality criteria are introduced to evaluate the efficiency of the proposed scheme. The efficiency of the organization is maximized if multiscale content decomposition is performed using content representatives and constructing content classes. Content representatives are estimated in our approach as the ones of the maximum dissimilarity, expressed by a distance metric. The optimization is conducted by incorporating a stochastic algorithm of logarithmically reduced searching area (stochastic logarithmic). Experimental results on real-life video sequences show that the proposed multiscale video organization enables users to detect content of interest much faster, compared to the conventional sequential video scanning or other video decomposition/summarization methods, resulting in a better organization efficiency as measured by the quality criteria. © 2004 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Signal Processing	en
dc.identifier.doi	10.1016/j.sigpro.2004.10.004	en
dc.identifier.isi	ISI:000226430700007	en
dc.identifier.volume	85	en
dc.identifier.issue	2	en
dc.identifier.spage	325	en
dc.identifier.epage	356	en