Comparison and combination of textual and visual features for interactive cross-language image retrieval

Pei Cheng Cheng; Jen Yuan Yeh; Hao Ren Ke; Been Chian Chien; Wei Pang Yang

doi:10.1007/11519645_77

Comparison and combination of textual and visual features for interactive cross-language image retrieval

Pei Cheng Cheng^*, Jen Yuan Yeh, Hao Ren Ke, Been Chian Chien, Wei Pang Yang

^*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

This paper concentrates on the user-centered search task at Image-CLEF 2004. In this work, we combine both textual and visual features for cross-language image retrieval, and propose two interactive retrieval systems -T_ICLEF and VCT_ICLEF. The first one incorporates a relevance feedback mechanism based on textual information while the second one combines textual and image information to help users find a target image. The experimental results show that VCT_ICLEF had a better performance in almost all cases. Overall, it helped users find the topic image within a fewer iterations with a maximum of 2 iterations saved. Our user survey also reported that a combination of textual and visual information is helpful to indicate to the system what a user really wanted in mind.

Original language	English
Pages (from-to)	793-804
Number of pages	12
Journal	Lecture Notes in Computer Science
Volume	3491
DOIs	https://doi.org/10.1007/11519645_77
Publication status	Published - 2005
Externally published	Yes
Event	5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images - Bath, United Kingdom Duration: 2004 Sept 15 → 2004 Sept 17

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/11519645_77

Cite this

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title = "Comparison and combination of textual and visual features for interactive cross-language image retrieval",

abstract = "This paper concentrates on the user-centered search task at Image-CLEF 2004. In this work, we combine both textual and visual features for cross-language image retrieval, and propose two interactive retrieval systems -T_ICLEF and VCT_ICLEF. The first one incorporates a relevance feedback mechanism based on textual information while the second one combines textual and image information to help users find a target image. The experimental results show that VCT_ICLEF had a better performance in almost all cases. Overall, it helped users find the topic image within a fewer iterations with a maximum of 2 iterations saved. Our user survey also reported that a combination of textual and visual information is helpful to indicate to the system what a user really wanted in mind.",

author = "Cheng, {Pei Cheng} and Yeh, {Jen Yuan} and Ke, {Hao Ren} and Chien, {Been Chian} and Yang, {Wei Pang}",

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journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

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note = "5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images ; Conference date: 15-09-2004 Through 17-09-2004",

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TY - JOUR

T1 - Comparison and combination of textual and visual features for interactive cross-language image retrieval

AU - Cheng, Pei Cheng

AU - Yeh, Jen Yuan

AU - Ke, Hao Ren

AU - Chien, Been Chian

AU - Yang, Wei Pang

PY - 2005

Y1 - 2005

N2 - This paper concentrates on the user-centered search task at Image-CLEF 2004. In this work, we combine both textual and visual features for cross-language image retrieval, and propose two interactive retrieval systems -T_ICLEF and VCT_ICLEF. The first one incorporates a relevance feedback mechanism based on textual information while the second one combines textual and image information to help users find a target image. The experimental results show that VCT_ICLEF had a better performance in almost all cases. Overall, it helped users find the topic image within a fewer iterations with a maximum of 2 iterations saved. Our user survey also reported that a combination of textual and visual information is helpful to indicate to the system what a user really wanted in mind.

AB - This paper concentrates on the user-centered search task at Image-CLEF 2004. In this work, we combine both textual and visual features for cross-language image retrieval, and propose two interactive retrieval systems -T_ICLEF and VCT_ICLEF. The first one incorporates a relevance feedback mechanism based on textual information while the second one combines textual and image information to help users find a target image. The experimental results show that VCT_ICLEF had a better performance in almost all cases. Overall, it helped users find the topic image within a fewer iterations with a maximum of 2 iterations saved. Our user survey also reported that a combination of textual and visual information is helpful to indicate to the system what a user really wanted in mind.

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DO - 10.1007/11519645_77

M3 - Conference article

AN - SCOPUS:24944564719

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EP - 804

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JF - Lecture Notes in Computer Science

T2 - 5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004: Multilingual Information Access for Text, Speech and Images

Y2 - 15 September 2004 through 17 September 2004

ER -

Comparison and combination of textual and visual features for interactive cross-language image retrieval

Abstract

ASJC Scopus subject areas

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