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Acoustic event detection based on feature-level fusion of audio and video modalities
dc.contributor.author | Butko, Taras |
dc.contributor.author | Canton Ferrer, Cristian |
dc.contributor.author | Segura Perales, Carlos |
dc.contributor.author | Giró Nieto, Xavier |
dc.contributor.author | Nadeu Camprubí, Climent |
dc.contributor.author | Hernando Pericás, Francisco Javier |
dc.contributor.author | Casas Pla, Josep Ramon |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2011-10-23T09:26:48Z |
dc.date.available | 2011-10-23T09:26:48Z |
dc.date.created | 2011-03-15 |
dc.date.issued | 2011-03-15 |
dc.identifier.citation | Butko, T. [et al.]. Acoustic event detection based on feature-level fusion of audio and video modalities. "Eurasip journal on advances in signal processing", 15 Març 2011, vol. 2011, p. 1-11. |
dc.identifier.issn | 1687-6172 |
dc.identifier.uri | http://hdl.handle.net/2117/13630 |
dc.description | Research article |
dc.description.abstract | Acoustic event detection (AED) aims at determining the identity of sounds and their temporal position in audio signals. When applied to spontaneously generated acoustic events, AED based only on audio information shows a large amount of errors, which are mostly due to temporal overlaps. Actually, temporal overlaps accounted for more than 70% of errors in the realworld interactive seminar recordings used in CLEAR 2007 evaluations. In this paper, we improve the recognition rate of acoustic events using information from both audio and video modalities. First, the acoustic data are processed to obtain both a set of spectrotemporal features and the 3D localization coordinates of the sound source. Second, a number of features are extracted from video recordings by means of object detection, motion analysis, and multicamera person tracking to represent the visual counterpart of several acoustic events. A feature-level fusion strategy is used, and a parallel structure of binary HMM-based detectors is employed in our work. The experimental results show that information from both the microphone array and video cameras is useful to improve the detection rate of isolated as well as spontaneously generated acoustic events. |
dc.format.extent | 11 p. |
dc.language.iso | eng |
dc.publisher | HINDAWI |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic |
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 | Acoustic event detection |
dc.title | Acoustic event detection based on feature-level fusion of audio and video modalities |
dc.type | Article |
dc.subject.lemac | Senyal acústic -- Detecció |
dc.contributor.group | Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla |
dc.contributor.group | Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
dc.identifier.doi | 10.1155/2011/485738 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.hindawi.com/journals/asp/2011/485738/ |
dc.rights.access | Open Access |
local.identifier.drac | 5391480 |
dc.description.version | Postprint (published version) |
local.citation.author | Butko, T.; Canton-Ferrer, C.; Segura, C.; Giro, X.; Nadeu, C.; Hernando, J.; Casas, J. |
local.citation.publicationName | Eurasip journal on advances in signal processing |
local.citation.volume | 2011 |
local.citation.startingPage | 1 |
local.citation.endingPage | 11 |
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