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dc.contributor.authorAsawa, Krishna
dc.contributor.authorManchanda, Priyanka
dc.date2014-09
dc.date.accessioned2020-02-05T13:43:01Z
dc.date.available2020-02-05T13:43:01Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/9803
dc.description.abstractMulti-sensor information fusion is a rapidly developing research area which forms the backbone of numerous essential technologies such as intelligent robotic control, sensor networks, video and image processing and many more. In this paper, we have developed a novel technique to analyze and correlate human emotions expressed in voice tone & facial expression. Audio and video streams captured to populate audio and video bimodal data sets to sense the expressed emotions in voice tone and facial expression respectively. An energy based mapping is being done to overcome the inherent heterogeneity of the recorded bi-modal signal. The fusion process uses sampled and mapped energy signal of both modalities’s data stream and further recognize the overall emotional component using Support Vector Machine (SVM) classifier with the accuracy 93.06%.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 02, nº 07
dc.relation.urihttps://www.ijimai.org/journal/node/671es_ES
dc.rightsopenAccesses_ES
dc.subjectbimodal fusiones_ES
dc.subjectemotion recognitiones_ES
dc.subjectintelligent systemses_ES
dc.subjectmachine learninges_ES
dc.subjectenergy mappinges_ES
dc.subjectIJIMAIes_ES
dc.titleRecognition of Emotions using Energy Based Bimodal Information Fusion and Correlationes_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttp://dx.doi.org/10.9781/ijimai.2014.272


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