Attention-driven image interpretation with application to image retrieval

Hong FU, Zheru CHI, Dagan FENG

Research output: Contribution to journalArticlespeer-review

74 Citations (Scopus)

Abstract

Visual attention, a selective procedure of human's early vision, plays a very important role for humans to understand a scene by intuitively emphasizing some focused regions/objects. Being aware of this, we propose an attention-driven image interpretation method that pops out visual attentive objects from an image iteratively by maximizing a global attention function. In this method, an image can be interpreted as containing several perceptually attended objects as well as a background, where each object has an attention value. The attention values of attentive objectives are then mapped to importance factors so as to facilitate the subsequent image retrieval. An attention-driven matching algorithm is proposed in this paper based on a retrieval strategy emphasizing attended objects. Experiments on 7376 Hemera color images annotated by keywords show that the retrieval results from our attention-driven approach compare favorably with conventional methods, especially when the important objects are seriously concealed by the irrelevant background. Copyright © 2006 Pattern Recognition Society. Published by Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)1604-1621
JournalPattern Recognition
Volume39
Issue number9
Early online date24 Mar 2006
DOIs
Publication statusPublished - Sep 2006

Citation

Fu, H., Chi, Z., & Feng, D. (2006). Attention-driven image interpretation with application to image retrieval. Pattern Recognition, 39(9), 1604-1621. doi: 10.1016/j.patcog.2005.12.015

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