Comparison and Combination of Textual and Visual Features for Interactive Cross-Language Image Retrieval View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

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

ABSTRACT

This paper concentrates on the user-centered search task at ImageCLEF 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. More... »

PAGES

793-804

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11519645_77

DOI

http://dx.doi.org/10.1007/11519645_77

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018953368


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