Visual attention plays a vital role for humans to understand a scene by intuitively emphasizing some focused objects, and recent work in the computational model of visual attention has demonstrated that a purely bottom-up approach to identify salient regions within an image can be successfully applied to diverse and practical problems. Being aware of this, we propose a new approach of extracting objects of interest (OOIs) using attention-driven model. In this approach, images are coarsely segmented into regions using EM (Expectation-Maximization) algorithm, and then we use the modified Itti-Koch model (M-Itti-Koch) of visual attention to find salient peaks, if these peaks overlap with regions generated by EM algorithm, we proceed to extract attentive object around those points. Experiment results demonstrate that the proposed approach gives good performance, as compared with the current peer method in the literature.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Novel Objects of Interest Extraction Approach Using Attention-Driven Model for Content-Based Image Retrieval


    Beteiligte:
    Lu, Yinghua (Autor:in) / Zhang, Xiaohua (Autor:in) / Kong, Jun (Autor:in) / Wang, Xuefeng (Autor:in) / Zhang, Jinbo (Autor:in)


    Erscheinungsdatum :

    01.05.2008


    Format / Umfang :

    558433 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Attention-based Global Feature Extraction Method For Image Retrieval

    He, Xiangyun / Ma, Lin / Zhao, Weiqiang et al. | IEEE | 2024


    Combining Interest Points and Edges for Content-based Image Retrieval

    Wang, J. / Zha, H. / Cipolla, R. | British Library Conference Proceedings | 2005


    Combining interest points and edges for content-based image retrieval

    Junqiu Wang, / Hongbin Zha, / Cipolla, R. | IEEE | 2005


    Content based Image Retrieval through Object Extraction and Querying

    Kam, A. / Ng, T. / Kingsbury, N. et al. | British Library Conference Proceedings | 2000