Presentation	2005-06-16 Matching Words and Image Segments for Semantic Retrieval Andrea KUTICS,
PDF Download Page	PDF download Page Link
Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	This paper presents a new method for retrieving images. A user's similarity interpretation is subjective and a similarity model's interpretation is objective. This method combines textual and object-based visual features to decrease this difference. It uses a novel multi-scale segmentation framework to detect prominent objects in an image. These objects are grouped depending on their visual features and mapped to related words obtained from psychophysical studies. Then, a hierarchy of words expressing higher-level meaning is determined on the basis of natural language processing and user evaluation. Experiments were carried out on 15,000 natural images. These showed higher retrieval precision in terms of estimating user retrieval semantics obtained via this two-layer association.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	Image Retrieval / Semantics / Multi-modal / Segmentation
Paper #	DE2005-12,PRMU2005-33
Date of Issue

Conference Information
Committee	PRMU
Conference Date	2005/6/9(1days)
Place (in Japanese)	(See Japanese page)
Place (in English)
Topics (in Japanese)	(See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To	Pattern Recognition and Media Understanding (PRMU)
Language	ENG
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Matching Words and Image Segments for Semantic Retrieval
Sub Title (in English)
Keyword(1)	Image Retrieval
Keyword(2)	Semantics
Keyword(3)	Multi-modal
Keyword(4)	Segmentation
1st Author's Name	Andrea KUTICS
1st Author's Affiliation	School of Media Science, Tokyo University of Technology()
Date	2005-06-16
Paper #	DE2005-12,PRMU2005-33
Volume (vol)	vol.105
Number (no)	118
Page	pp.pp.-
#Pages	2
Date of Issue