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dc.contributor.authorZhang, L
dc.contributor.authorHan Lau, AC
dc.contributor.authorTjondronegoro, D
dc.contributor.authorChandran, V
dc.date.accessioned2020-01-14T23:27:46Z
dc.date.available2020-01-14T23:27:46Z
dc.date.issued2014
dc.identifier.isbn9781479958962
dc.identifier.doi10.1109/MMSP.2014.6958799
dc.identifier.urihttp://hdl.handle.net/10072/390272
dc.description.abstractThe proliferation of news reports published in online websites and news information sharing among social media users necessitates effective techniques for analysing the image, text and video data related to news topics. This paper presents the first study to classify affective facial images on emerging news topics. The proposed system dynamically monitors and selects the current hot (of great interest) news topics with strong affective interestingness using textual keywords in news articles and social media discussions. Images from the selected hot topics are extracted and classified into three categorized emotions, positive, neutral and negative, based on facial expressions of subjects in the images. Performance evaluations on two facial image datasets collected from realworld resources demonstrate the applicability and effectiveness of the proposed system in affective classification of facial images in news reports. Facial expression shows high consistency with the affective textual content in news reports for positive emotion, while only low correlation has been observed for neutral and negative. The system can be directly used for applications, such as assisting editors in choosing photos with a proper affective semantic for a certain topic during news report preparation.
dc.publisherIEEE
dc.relation.ispartofconferencename2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)
dc.relation.ispartofconferencetitle2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP)
dc.relation.ispartofdatefrom2014-09-22
dc.relation.ispartofdateto2014-09-24
dc.subject.fieldofresearchArtificial Intelligence and Image Processing
dc.subject.fieldofresearchcode0801
dc.titleA pilot study on affective classification of facial images for emerging news topics
dc.typeConference output
dc.type.descriptionE2 - Conferences (Non Refereed)
dcterms.bibliographicCitationZhang, L; Han Lau, AC; Tjondronegoro, D; Chandran, V, A pilot study on affective classification of facial images for emerging news topics, 2014 IEEE 16th International Workshop on Multimedia Signal Processing (MMSP), 2014
dc.date.updated2020-01-14T23:23:53Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorTjondronegoro, Dian W.


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