Video Indexing using Motion Estimation

SV Porter; M Mirmehdi; BT Thomas

Video Indexing using Motion Estimation

SV Porter
, M Mirmehdi
, BT Thomas

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

Abstract

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 contribution	Video Indexing using Motion Estimation
Original language	English
Title of host publication	Unknown
Publisher	BMVA Press
Pages	659 - 668
Number of pages	9
ISBN (Print)	1901725235
Publication status	Published - Sept 2003

Bibliographical note

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

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@inproceedings{57d2c97286ec415698c8a94bfe442dbd,

title = "Video Indexing using Motion Estimation",

abstract = "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. ",

author = "SV Porter and M Mirmehdi and BT Thomas",

note = "Conference Proceedings/Title of Journal: Proceedings of the 14th Bristish Machine Vision Conference",

year = "2003",

month = sep,

language = "English",

isbn = "1901725235",

pages = "659 -- 668",

booktitle = "Unknown",

publisher = "BMVA Press",

}

TY - GEN

T1 - Video Indexing using Motion Estimation

AU - Porter, SV

AU - Mirmehdi, M

AU - Thomas, BT

N1 - Conference Proceedings/Title of Journal: Proceedings of the 14th Bristish Machine Vision Conference

PY - 2003/9

Y1 - 2003/9

N2 - 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.

AB - 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.

M3 - Conference Contribution (Conference Proceeding)

SN - 1901725235

SP - 659

EP - 668

BT - Unknown

PB - BMVA Press

ER -

Video Indexing using Motion Estimation

Abstract

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