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dc.contributor.authorHimawan, Ivan
dc.contributor.authorSong, Wei
dc.contributor.authorTjondronegoro, Dian
dc.date.accessioned2020-01-15T05:03:27Z
dc.date.available2020-01-15T05:03:27Z
dc.date.issued2013
dc.identifier.isbn978-1-4673-5052-5en_US
dc.identifier.issn1550-5790en_US
dc.identifier.doi10.1109/WACV.2013.6475002en_US
dc.identifier.urihttp://hdl.handle.net/10072/390284
dc.description.abstractThe increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.en_US
dc.languageEnglishen_US
dc.publisherIEEEen_US
dc.relation.ispartofconferencename2013 IEEE Workshop on Applications of Computer Vision (WACV)en_US
dc.relation.ispartofconferencetitle2013 IEEE Workshop on Applications of Computer Vision (WACV)en_US
dc.relation.ispartofdatefrom2013-01-15
dc.relation.ispartofdateto2013-01-17
dc.relation.ispartoflocationClearwater, FLen_US
dc.relation.ispartofpagefrom76en_US
dc.relation.ispartofpageto82en_US
dc.subject.keywordsScience & Technologyen_US
dc.subject.keywordsComputer Science, Artificial Intelligenceen_US
dc.subject.keywordsComputer Science, Theory & Methodsen_US
dc.subject.keywordsEngineering, Electrical & Electronicen_US
dc.titleAutomatic Region-of-Interest Detection and Prioritisation for Visually Optimised Coding of Low Bit Rate Videosen_US
dc.typeConference outputen_US
dcterms.bibliographicCitationHimawan, I; Song, W; Tjondronegoro, D, Automatic Region-of-Interest Detection and Prioritisation for Visually Optimised Coding of Low Bit Rate Videos, 2013 IEEE Workshop on Applications of Computer Vision (WACV), 2013, pp. 76-82en_US
dc.date.updated2020-01-15T04:53:08Z
dc.description.versionAccepted Manuscript (AM)en_US
gro.rights.copyright© 2013 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.en_US
gro.hasfulltextFull Text
gro.griffith.authorTjondronegoro, Dian W.


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