Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40251
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dc.titleDetection and removal of lighting & shaking artifacts in home videos
dc.contributor.authorYan, W.-Q.
dc.contributor.authorKankanhalli, M.S.
dc.date.accessioned2013-07-04T08:00:03Z
dc.date.available2013-07-04T08:00:03Z
dc.date.issued2002
dc.identifier.citationYan, W.-Q.,Kankanhalli, M.S. (2002). Detection and removal of lighting & shaking artifacts in home videos. Proceedings of the ACM International Multimedia Conference and Exhibition : 107-116. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40251
dc.description.abstractMany amateur videographers, like home video enthusiasts, may capture videos that are not of a professional quality. Many minor but visually annoying distortions like lighting imbalance and shaking artifacts could be introduced by the unskilled operations of the video camcorder. Since home videos constitute footage of great sentimental value, such videos cannot be summarily discarded. Unlike movies and sitcoms, shot re-takes of important events, such as wedding ceremonies are just not possible. Therefore, such distortions need to be corrected. In this paper, we present a novel method to detect segments of videos that have lighting and shaking artifacts. These segments can then be subjected to a restoration process that can remove these artifacts. We present techniques to correct lighting artifacts by appropriately adjusting the luminance. In order to remove the shaking artifact, image mosaicing is first employed to build a mosaic frame for the segment with the aid of edge blending techniques. Subsequently a Bezier-curve based blending of motion trajectory is employed to perform motion-compensated filtering of the snaking artifact. The restored video is then created by appropriately cropping the mosaic frame based on the compensated motion trajectory. We have implemented the developed techniques and the experimental results on home videos demonstrate the effectiveness of our approach. Detection and removal of artifacts are significant in other videos as well as those obtained from autonomous vehicles, robots and remote sensing.
dc.sourceScopus
dc.subjectArtifacts removal
dc.subjectLighting artifacts
dc.subjectVideo mosaic
dc.subjectVideo shaking
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings of the ACM International Multimedia Conference and Exhibition
dc.description.page107-116
dc.identifier.isiutNOT_IN_WOS
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