tailieunhanh - Báo cáo hóa học: " Manifold-Ranking-Based Keyword Propagation for Image Retrieval"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Manifold-Ranking-Based Keyword Propagation for Image Retrieval | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article iD 79412 Pages 1-10 DOI ASP 2006 79412 Manifold-Ranking-Based Keyword Propagation for Image Retrieval Hanghang Tong 1 Jingrui He 1 Mingjing Li 2 Wei-Ying Ma 2 Hong-Jiang Zhang 2 and Changshui Zhang1 1 Department of Automation Tsinghua University Beijing 100084 China 2 Microsoft Research Asia 49 Zhichun Road Beijing 100080 China Received 30 August 2004 Revised 29 January 2005 Accepted 5 April 2005 A novel keyword propagation method is proposed for image retrieval based on a recently developed manifold-ranking algorithm. In contrast to existing methods which train a binary classifier for each keyword our keyword model is constructed in a straightforward manner by exploring the relationship among all images in the feature space in the learning stage. In relevance feedback the feedback information can be naturally incorporated to refine the retrieval result by additional propagation processes. In order to speed up the convergence of the query concept we adopt two active learning schemes to select images during relevance feedback. Furthermore by means of keyword model update the system can be self-improved constantly. The updating procedure can be performed online during relevance feedback without extra offline training. Systematic experiments on a general-purpose image database consisting of 5 000 Corel images validate the effectiveness of the proposed method. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION The initial image retrieval methods are based on keyword annotation and can be traced back to the 1970 s 1 2 . In such approaches images are first annotated manually with keywords and then retrieved by their annotations. As long as the annotation is accurate and complete keywords can accurately represent the semantics of images. However it suffers from several main difficulties for example the large amount of manual labor .