Video Indexing using Motion Estimation

SV Porter, M Mirmehdi, BT Thomas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


Summarising video data is essential to enable content-based video indexing and retrieval. A novel graph theoretic approach is presented to extract representative key frames corresponding to the shortest path of the graph for each shot. We distinguish further amongst paths of similar weight by examining the standard deviation of their constituent edge weights which improves the distribution of the selected key frames. The perceived camera motions contained within each shot are also annotated to introduce a further level of indexing and searching video content.
Translated title of the contributionVideo Indexing using Motion Estimation
Original languageEnglish
Title of host publicationUnknown
PublisherBMVA Press
Pages659 - 668
Number of pages9
ISBN (Print)1901725235
Publication statusPublished - Sept 2003

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 14th Bristish Machine Vision Conference


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