Speeding up relevance feedback in image retrieval with triangle-inequality based algorithms

Ziyou Xiong; Xiang Zhou; William M. Pottenger; Thomas S. Huang

doi:10.1109/icassp.2002.5745377

Speeding up relevance feedback in image retrieval with triangle-inequality based algorithms

Ziyou Xiong, Xiang Zhou, William M. Pottenger, Thomas S. Huang

Research output: Contribution to journal › Conference article › peer-review

Abstract

A content-based image retrieval (CBIR) system has been constructed to integrate relevance feedback with triangle-inequality based algorithms. The system offers typically 20 to 30 times faster retrieving speed with minimum sacrifice of retrieval performance on Corel database consisting of more than 17,000 images. The theoretic framework is built by using triangle-inequality based algorithms at sub-feature level and using relevance feedback techniques at feature level. Results show retrieval performance is clearly improved over the approach with only triangle-inequality based algorithms. A new high level weight updating method for the hierarchical distance model for relevance feedback is proposed.

Original language	English (US)
Pages (from-to)	IV/3373-IV/3376
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	4
DOIs	https://doi.org/10.1109/icassp.2002.5745377
State	Published - 2002
Externally published	Yes
Event	2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States Duration: May 13 2002 → May 17 2002

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Online availability

10.1109/icassp.2002.5745377

Library availability

Discover UIUC Full Text

Cite this

@article{e3b1d40b2a084969ba7f358ac8f5342f,

title = "Speeding up relevance feedback in image retrieval with triangle-inequality based algorithms",

abstract = "A content-based image retrieval (CBIR) system has been constructed to integrate relevance feedback with triangle-inequality based algorithms. The system offers typically 20 to 30 times faster retrieving speed with minimum sacrifice of retrieval performance on Corel database consisting of more than 17,000 images. The theoretic framework is built by using triangle-inequality based algorithms at sub-feature level and using relevance feedback techniques at feature level. Results show retrieval performance is clearly improved over the approach with only triangle-inequality based algorithms. A new high level weight updating method for the hierarchical distance model for relevance feedback is proposed.",

author = "Ziyou Xiong and Xiang Zhou and Pottenger, {William M.} and Huang, {Thomas S.}",

year = "2002",

doi = "10.1109/icassp.2002.5745377",

language = "English (US)",

volume = "4",

pages = "IV/3373--IV/3376",

journal = "Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing",

issn = "0736-7791",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2002 IEEE International Conference on Acoustic, Speech, and Signal Processing ; Conference date: 13-05-2002 Through 17-05-2002",

}

TY - JOUR

T1 - Speeding up relevance feedback in image retrieval with triangle-inequality based algorithms

AU - Xiong, Ziyou

AU - Zhou, Xiang

AU - Pottenger, William M.

AU - Huang, Thomas S.

PY - 2002

Y1 - 2002

N2 - A content-based image retrieval (CBIR) system has been constructed to integrate relevance feedback with triangle-inequality based algorithms. The system offers typically 20 to 30 times faster retrieving speed with minimum sacrifice of retrieval performance on Corel database consisting of more than 17,000 images. The theoretic framework is built by using triangle-inequality based algorithms at sub-feature level and using relevance feedback techniques at feature level. Results show retrieval performance is clearly improved over the approach with only triangle-inequality based algorithms. A new high level weight updating method for the hierarchical distance model for relevance feedback is proposed.

AB - A content-based image retrieval (CBIR) system has been constructed to integrate relevance feedback with triangle-inequality based algorithms. The system offers typically 20 to 30 times faster retrieving speed with minimum sacrifice of retrieval performance on Corel database consisting of more than 17,000 images. The theoretic framework is built by using triangle-inequality based algorithms at sub-feature level and using relevance feedback techniques at feature level. Results show retrieval performance is clearly improved over the approach with only triangle-inequality based algorithms. A new high level weight updating method for the hierarchical distance model for relevance feedback is proposed.

UR - http://www.scopus.com/inward/record.url?scp=0036288370&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036288370&partnerID=8YFLogxK

U2 - 10.1109/icassp.2002.5745377

DO - 10.1109/icassp.2002.5745377

M3 - Conference article

AN - SCOPUS:0036288370

SN - 0736-7791

VL - 4

SP - IV/3373-IV/3376

JO - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

JF - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

T2 - 2002 IEEE International Conference on Acoustic, Speech, and Signal Processing

Y2 - 13 May 2002 through 17 May 2002

ER -

Speeding up relevance feedback in image retrieval with triangle-inequality based algorithms

Abstract

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Cite this