Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

A comparison of score, rank and probability-based fusion methods for video shot retrieval

McDonald, Kieran and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2005) A comparison of score, rank and probability-based fusion methods for video shot retrieval. In: CIVR 2005 - International Conference on Image and Video Retrieval, 20-22 July 2005, Singapore. ISBN 978-3-540-27858-0

Abstract
It is now accepted that the most effective video shot retrieval is based on indexing and retrieving clips using multiple, parallel modalities such as text-matching, image-matching and feature matching and then combining or fusing these parallel retrieval streams in some way. In this paper we investigate a range of fusion methods for combining based on multiple visual features (colour, edge and texture), for combining based on multiple visual examples in the query and for combining multiple modalities (text and visual). Using three TRECVid collections and the TRECVid search task, we specifically compare fusion methods based on normalised score and rank that use either the average, weighted average or maximum of retrieval results from a discrete Jelinek-Mercer smoothed language model. We also compare these results with a simple probability-based combination of the language model results that assumes all features and visual examples are fully independent.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:The original publication is available at www.springerlink.com
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Published in: Image and Video Retrieval. Lecture Notes in Computer Science 3568. Springer Berlin / Heidelberg. ISBN 978-3-540-27858-0
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/11526346_10
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 03/IN.3/I361, Enterprise Ireland
ID Code:269
Deposited On:10 Mar 2008 by DORAS Administrator . Last Modified 08 Nov 2018 10:52
Documents

Full text available as:

[thumbnail of lncs_3568.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
164kB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record