Please use this identifier to cite or link to this item: https://doi.org/10.1006/cviu.2000.0858
DC FieldValue
dc.titleScene-based shot change detection and comparative evaluation
dc.contributor.authorCheong, L.-F.
dc.date.accessioned2014-10-07T03:05:03Z
dc.date.available2014-10-07T03:05:03Z
dc.date.issued2000-08
dc.identifier.citationCheong, L.-F. (2000-08). Scene-based shot change detection and comparative evaluation. Computer Vision and Image Understanding 79 (2) : 224-235. ScholarBank@NUS Repository. https://doi.org/10.1006/cviu.2000.0858
dc.identifier.issn10773142
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/81136
dc.description.abstractA key step for managing a large video database is to partition the video sequences into shots. Past approaches to this problem tend to confuse gradual shot changes with changes caused by smooth camera motions. This is in part due to the fact that camera motion has not been dealt with in a more fundamental way. We propose an approach that is based on a physical constraint used in optical flow analysis, namely, the total brightness of a scene point across two frames should remain constant if the change across two frames is a result of smooth camera motion. Since the brightness constraint would be violated across a shot change, the detection can be based on detecting the violation of this constraint. It is robust because it uses only the qualitative aspect of the brightness constraint - detecting a scene change rather than estimating the scene itself. Moreover, by tapping on the significant know-how in using this constraint, the algorithm's robustness is further enhanced. Experimental results are presented to demonstrate the performance of various algorithms. It is shown that our algorithm is less likely to interpret gradual camera motions as shot changes, resulting in a better precision performance than most other algorithms. However, its performance deteriorates under large camera or object motions. A twin-threshold scheme is proposed to improve its robustness.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1006/cviu.2000.0858
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1006/cviu.2000.0858
dc.description.sourcetitleComputer Vision and Image Understanding
dc.description.volume79
dc.description.issue2
dc.description.page224-235
dc.description.codenCVIUF
dc.identifier.isiut000088615800002
Appears in Collections:Staff Publications

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