A rule based technique for extraction of visual attention regions based on real-time clustering

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

44 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)766-784
Journal / PublicationIEEE Transactions on Multimedia
Volume9
Issue number4
Publication statusPublished - Jun 2007

Abstract

Recently, the detection of visual attention regions (VAR) is becoming more important due to its useful application in the area of multimedia. Although there exist a lot of approaches to detect visual attention regions, few of them consider the semantic gap between the visual attention regions and high-level semantics. In this paper, we propose a rule based technique for the extraction of visual attention regions at the object level based on real-time clustering, such that VAR detection can be performed in a very efficient way. The proposed technique consists of four stages: 1) a fast segmentation technique which is called the real time clustering algorithm (RTCA); 2) a refined specification of VAR which is known as the hierarchical visual attention regions (HVAR); 3) a new algorithm known as the rule based detection algorithm (RADA) to obtain the set of HVARs in real time, and 4) a new adaptive image display module and the corresponding adaptation operations using HVAR. We also define a new background measure which combines both feature contrast and the geometric property of the region to identify the background region, and a confidence factor which is used to extract the set of hierarchical visual attention regions. Compared with existing techniques, our approach has two advantages: 1) the approach detects the visual attention region at the object level, which bridges the gap between traditional visual attention regions and high-level semantics; 2) our approach is efficient and easy to implement. © 2007 IEEE.

Research Area(s)

  • Clustering, Knowledge extraction, Real time processing, Visual attention regions, Visualization