Using an Image-text parallel corpus and the web for query expansion in cross-language image retrieval
Journal
Lecture Notes in Computer Science
Journal Volume
5152 LNCS
Pages
504-511
ISBN
3540857591; 9783540857594
Date Issued
2008
Author(s)
Chang Y.-C.
Abstract
ImageCLEF2007 photo task is different from those of the previous years in two aspects. The caption field in the image annotations and the narrative field in the text queries are removed, and the example images in the visual queries are also removed from the image collection. In the new definition, the information that can be employed is less than before. Thus matching query words and annotations directly is not feasible. This paper explores the web to expand queries and documents. The experiments show that query expansion improves the performance 16.11%, however, document expansion brings in too much noise and the performance decreases 28.24%. The media mapping method based on an image-text parallel corpus is regarded as query expansion. The results of the formal runs show this method performs the best. Compared with the performance of the models without expansion, the MAP improves about 86.69%?143.12%. Integration of the external and the internal resources gains no benefits in the further experiments. ? 2008 Springer-Verlag Berlin Heidelberg.
Type
conference paper