Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89162
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dc.contributor.authorHou, Junhuien
dc.contributor.authorChau, Lap-Puien
dc.contributor.authorMagnenat-Thalmann, Nadiaen
dc.contributor.authorHe, Yingen
dc.date.accessioned2018-05-18T07:42:23Zen
dc.date.accessioned2019-12-06T17:19:15Z-
dc.date.available2018-05-18T07:42:23Zen
dc.date.available2019-12-06T17:19:15Z-
dc.date.issued2015en
dc.identifier.citationHou, J., Chau, L.-P., Magnenat-Thalmann, N., & He, Y. (2015). Human Motion Capture Data Tailored Transform Coding. IEEE Transactions on Visualization and Computer Graphics, 21(7), 848-859.en
dc.identifier.issn1077-2626en
dc.identifier.urihttps://hdl.handle.net/10356/89162-
dc.description.abstractHuman motion capture (mocap) is a widely used technique for digitalizing human movements. With growing usage, compressing mocap data has received increasing attention, since compact data size enables efficient storage and transmission. Our analysis shows that mocap data have some unique characteristics that distinguish themselves from images and videos. Therefore, directly borrowing image or video compression techniques, such as discrete cosine transform, does not work well. In this paper, we propose a novel mocap-tailored transform coding algorithm that takes advantage of these features. Our algorithm segments the input mocap sequences into clips, which are represented in 2D matrices. Then it computes a set of data-dependent orthogonal bases to transform the matrices to frequency domain, in which the transform coefficients have significantly less dependency. Finally, the compression is obtained by entropy coding of the quantized coefficients and the bases. Our method has low computational cost and can be easily extended to compress mocap databases. It also requires neither training nor complicated parameter setting. Experimental results demonstrate that the proposed scheme significantly outperforms state-of-the-art algorithms in terms of compression performance and speed.en
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en
dc.description.sponsorshipMOE (Min. of Education, S’pore)en
dc.format.extent20 p.en
dc.language.isoenen
dc.relation.ispartofseriesIEEE Transactions on Visualization and Computer Graphicsen
dc.rights© 2015 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. The published version is available at: [http://dx.doi.org/10.1109/TVCG.2015.2403328].en
dc.subjectTransform Codingen
dc.subjectMotion Captureen
dc.titleHuman Motion Capture Data Tailored Transform Codingen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.contributor.researchInstitute for Media Innovationen
dc.identifier.doi10.1109/TVCG.2015.2403328en
dc.description.versionAccepted versionen
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Appears in Collections:EEE Journal Articles
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