From Text to Image: Generating Visual Query for Image Retrieval
Resource
Multilingual Information Access for Text, Speech and Images: 5th Workshop of the Cross-Language Evaluation Forum, CLEF 2004, Bath, UK, September 15-17, 2004, Carol Peters, Paul Clough, Julio Gonzalo (Eds), Lecture Notes in Computer Science, 3491, 664-675
Journal
Multilingual Information Access for Text Speech and Images (Lecture Notes in Computer Science)
Pages
664-675
Date Issued
2005
Date
2005
Author(s)
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Dough
Vardi, Moshe Y.
Weikum, Gerhard
Abstract
This paper explores the uses of visual features for cross-language access to an image collection. An approach which transforms textual queries into visual representations is proposed. The relationships between text and images are mined. We employ the mined relationships to construct visual queries from textual ones. The retrieval results using textual and visual queries are combined to generate the final ranked list. We conducted English monolingual and Chinese-English cross-language retrieval experiments. The performances are quite good. The average precision of English monolingual textual run is 0.6304. The performance of cross-lingual retrieval is about 70% of monolingual retrieval. Comparatively, the gain of the generated visual query is not significant. If only appropriate query terms are selected to generate visual query, retrieval performance could be increased. © Springer-Verlag Berlin Heidelberg 2005.
SDGs
Other Subjects
Approximation theory; Image retrieval; Information retrieval; Linguistics; Mathematical transformations; Text processing; Cross-lingual retrieval; Retrieval performance; Visual query; Visual representations; Query languages
Type
conference paper
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