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A Computational Pixelization Model Based on Selective Attention for Artificial Visual Prosthesis

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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Abstract

Inspired by the ongoing research on artificial visual prosthesis, a novel pixelization visual model based on the selection of local attention-drawing features is proposed, and a subjective scoring experiment as a cognitive assessment is designed to evaluate the performance of the model. The results of the experiment reveal that the model can accentuate the areas with prominent features in the original image, so as to give observers a subjective perception of rich visual information. Thus, the model will provide a new approach for future research.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering, Tsinghua University, Beijing, China

    Ruonan Li & Xudong Zhang

  2. Department of Biomedical Engineering, Tsinghua University, Beijing, China

    Guangshu Hu

Authors
  1. Ruonan Li
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  2. Xudong Zhang
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  3. Guangshu Hu
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, R., Zhang, X., Hu, G. (2005). A Computational Pixelization Model Based on Selective Attention for Artificial Visual Prosthesis. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_80

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  • DOI: https://doi.org/10.1007/11539902_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28320-1

  • Online ISBN: 978-3-540-31863-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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