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dc.contributor.authorGrundmann, Matthias
dc.contributor.authorKwatra, Vivek
dc.contributor.authorHan, Mei
dc.contributor.authorEssa, Irfan
dc.date.accessioned2011-03-24T22:07:48Z
dc.date.available2011-03-24T22:07:48Z
dc.date.issued2010-06
dc.identifier.citationGrundmann, M., Kwatra, V., Han, M., & Essa, I. (2010). "Discontinuous Seam-Carving for Video Retargeting". Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), 13-18 June 2010, 569-576.en_US
dc.identifier.issn1063-6919
dc.identifier.urihttp://hdl.handle.net/1853/38275
dc.description©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.en_US
dc.descriptionPresented at the 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 13-18 June 2010, San Francisco, CA.
dc.descriptionDOI: 10.1109/CVPR.2010.5540165
dc.description.abstractWe introduce a new algorithm for video retargeting that uses discontinuous seam-carving in both space and time for resizing videos. Our algorithm relies on a novel appearance-based temporal coherence formulation that allows for frame-by-frame processing and results in temporally discontinuous seams, as opposed to geometrically smooth and continuous seams. This formulation optimizes the difference in appearance of the resultant retargeted frame to the optimal temporally coherent one, and allows for carving around fast moving salient regions. Additionally, we generalize the idea of appearance-based coherence to the spatial domain by introducing piece-wise spatial seams. Our spatial coherence measure minimizes the change in gradients during retargeting, which preserves spatial detail better than minimization of color difference alone. We also show that per-frame saliency (gradient-based or feature-based) does not always produce desirable retargeting results and propose a novel automatically computed measure of spatio-temporal saliency. As needed, a user may also augment the saliency by interactive region-brushing. Our retargeting algorithm processes the video sequentially, making it conducive for streaming applications.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectImagesen_US
dc.subjectVideo resizingen_US
dc.subjectVideo streamingen_US
dc.titleDiscontinuous Seam-Carving for Video Retargetingen_US
dc.typePost-printen_US
dc.typeProceedings
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computing
dc.contributor.corporatenameGoogle Research
dc.publisher.originalInstitute of Electrical and Electronics Engineers


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