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Automatic summarization of soccer highlights using audio-visual descriptors
dc.contributor.author | Raventós Mayoral, Arnau |
dc.contributor.author | Quijada Ferrero, Raúl |
dc.contributor.author | Torres Urgell, Lluís |
dc.contributor.author | Tarrés Ruiz, Francisco |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2016-01-19T15:11:00Z |
dc.date.available | 2016-01-19T15:11:00Z |
dc.date.issued | 2015-06-30 |
dc.identifier.citation | Raventos, A., Quijada, R., Torres, L., Tarres, F. Automatic summarization of soccer highlights using audio-visual descriptors. "SpringerPlus", 30 Juny 2015, vol. 4, p. 1-19. |
dc.identifier.issn | 2193-1801 |
dc.identifier.uri | http://hdl.handle.net/2117/81686 |
dc.description.abstract | Automatic summarization generation of sports video content has been object of great interest for many years. Although semantic descriptions techniques have been proposed, many of the approaches still rely on low-level video descriptors that render quite limited results due to the complexity of the problem and to the low capability of the descriptors to represent semantic content. In this paper, a new approach for automatic highlights summarization generation of soccer videos using audio-visual descriptors is presented. The approach is based on the segmentation of the video sequence into shots that will be further analyzed to determine its relevance and interest. Of special interest in the approach is the use of the audio information that provides additional robustness to the overall performance of the summarization system. For every video shot a set of low and mid level audio-visual descriptors are computed and lately adequately combined in order to obtain different relevance measures based on empirical knowledge rules. The final summary is generated by selecting those shots with highest interest according to the specifications of the user and the results of relevance measures. A variety of results are presented with real soccer video sequences that prove the validity of the approach. |
dc.format.extent | 19 p. |
dc.language.iso | eng |
dc.publisher | Springer |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo |
dc.subject.lcsh | Video description |
dc.subject.lcsh | Semantic computing |
dc.subject.lcsh | Soccer |
dc.subject.other | Video summarization |
dc.subject.other | Content analysis |
dc.subject.other | Audiovisual descriptors |
dc.subject.other | Multimedia feature extraction |
dc.subject.other | Semantic detection |
dc.subject.other | Multimodal processing and fusion |
dc.subject.other | Shot-boundary detection |
dc.subject.other | Of-the-art |
dc.subject.other | Video |
dc.subject.other | Retrieval |
dc.subject.other | System |
dc.title | Automatic summarization of soccer highlights using audio-visual descriptors |
dc.type | Article |
dc.subject.lemac | Vídeo |
dc.subject.lemac | Semàntica computacional |
dc.subject.lemac | Futbol |
dc.contributor.group | Universitat Politècnica de Catalunya. DMAG - Grup d'Aplicacions Multimèdia Distribuïdes |
dc.identifier.doi | 10.1186/s40064-015-1065-9 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.springerplus.com/content/pdf/s40064-015-1065-9.pdf |
dc.rights.access | Open Access |
local.identifier.drac | 16870379 |
dc.description.version | Postprint (published version) |
local.citation.author | Raventos, A.; Quijada, R.; Torres, L.; Tarres, F. |
local.citation.publicationName | SpringerPlus |
local.citation.volume | 4 |
local.citation.startingPage | 1 |
local.citation.endingPage | 19 |
dc.identifier.pmid | 26155440 |
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