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dc.contributor.authorZhao, Ruzhang
dc.contributor.authorFang, Yajun
dc.contributor.authorHOrn, Berthold K.P.
dc.date.accessioned2021-11-24T19:03:59Z
dc.date.available2021-11-05T18:21:20Z
dc.date.available2021-11-24T19:03:59Z
dc.date.issued2018
dc.identifier.urihttps://hdl.handle.net/1721.1/137561.2
dc.description.abstract© 2018 IEEE. For identification of change information in image sequences, most studies focus on change detection in one image sequence, while few studies have considered the change level comparison between two different image sequences. Moreover, most studies require the detection of image information in details, for example, object detection. Based on Uncertainty Coefficient(UC), this paper proposes an innovative method 'CCUC' for change comparison between two image sequences. The proposed method is computationally efficient and simple to implement. The change comparison stems from video monitoring system. The limited number of provided screens and a large number of monitoring cameras require the videos or image sequences ordered by change level. We demonstrate this new method by applying it on two publicly available image sequences. The results are able to show the method can distinguish the different change level for sequences.en_US
dc.language.isoen
dc.relation.isversionof10.1109/UV.2018.8642140en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleA Simple Change Comparison Method for Image Sequences Based on Uncertainty Coefficienten_US
dc.typeArticleen_US
dc.identifier.citationZhao, Ruzhang, Fang, Yajun and HOrn, Berthold K.P. 2018. "A Simple Change Comparison Method for Image Sequences Based on Uncertainty Coefficient."en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-05-31T12:43:45Z
dspace.date.submission2019-05-31T12:43:46Z
mit.metadata.statusPublication Information Neededen_US


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