Download:
|
by Universite De Geneve, David Mcg Squire
http://cui.unige.ch/~vision/Publications/postscript/2000/VGTR00.03_MuellerHMuellerWSquirePecenovicMarchandPun.ps.gz
Add To MetaCart
Abstract:
This article describes a framework for distributed multimedia retrieval which permits the connection of compliant user interfaces with a variety of multimedia retrieval engines via an open communication protocol, MRML (Multi Media Retrieval Markup Language). It allows the choice of image collection, feature set and query algorithm during run{time, permitting multiple users to query a system adapted to their needs, using the query paradigm adapted to their problem such as query by example (QBE), browsing queries, or query by annotation. User interaction is implemented over several levels and in diverse ways. Relevance feedback is implemented using positive and negative example images that can be used for a best{match QBE query. In contrast, browsing methods try to approach the searched image by giving overviews of the entire collection and by successive renement. In addition to these query methods, Long term o line learning is implemented. It allows feature preferences per user, user domain or over all users to be learned automatically. We present the Viper multimedia retrieval system as the core of the framework and an example of an MRML{compliant search engine. Viper uses techniques adapted from traditional
Citations
|
881
|
Term-weighting approaches in automatic text retrieval
– Salton, Buckley
- 1998
|
|
681
|
W.: Query by Image and Video Content: The QBIC System
– Flickner, Sawhney, et al.
- 1997
|
|
559
|
Relevance feedback in information retrieval, The
– Rocchio
- 1971
|
|
93
|
Region-based image querying
– Carson, Belongie, et al.
- 1997
|
|
75
|
Content–based query of image databases: inspirations from text retrieval
– Squire, Müller, et al.
|
|
38
|
MetaSEEk: A content-based meta-search engine for images
– Beigi, Benitez, et al.
- 1997
|
|
38
|
Information Embedding Based on User’s Relevance Feedback for Image Retrieval
– Lee, Ma, et al.
- 1998
|
|
37
|
Target testing and the PicHunter Bayesian multimedia retrieval system
– Cox, Miller, et al.
|
|
35
|
Performance evaluation in content-based image retrieval: Overview and proposals
– Muller, Muller, et al.
- 2001
|
|
22
|
A comparison of human and machine assessments of image similarity for the organization of image databases
– Squire, Pun
- 1997
|
|
20
|
Relevance Feedback and Term Weighting Schemes for Content-Based Image Retrieval
– Squire, Müller, et al.
- 1999
|
|
18
|
Strategies for positive and negative relevance feedback in image retrieval
– Müller, Müller, et al.
- 2000
|
|
17
|
Efficient access methods for content-based image retrieval with inverted files
– Muller, Squire, et al.
- 1999
|
|
16
|
Hunting moving targets: an extension to Bayesian methods in multimedia databases
– Muller, Squire, et al.
- 1999
|
|
8
|
Query taxonomy of multimedia databases
– Chang, Bergmann, et al.
- 1999
|
|
8
|
MRML: Towards an extensible standard for multimedia querying and benchmarking { Draft proposal
– Muller, Pecenovic, et al.
- 1999
|
|
7
|
MPEG-7: Context and objectives (version 10
– Group
- 1998
|
|
7
|
Overview of the seventh text retrieval conference (TREC-7
– Vorhees, Harmann
- 1998
|
|
3
|
Long term learning in content-based image retrieval
– Muller, Muller, et al.
- 2000
|
|
3
|
IBM's Query By Image Content. web page: http://wwwqbic.almaden.ibm.com/~qbic
– TM
- 1998
|
