Superpixel convolution for segmentation

Teppei Suzuki, Shuichi Akizuki, Naoki Kato, Yoshimitsu Aoki

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, we propose a novel segmentation algorithm based on convolutional neural networks (CNNs) on superpix-else CNNs are powerful methods for several computer vision tasks, but spatial information disappears through the pooling process. Moreover, since pooling compresses different types of pixels into a single value, pooling sometimes negatively affects the results of inference in segmentation task. We use superpixel pooling instead of general pooling to resolve this problem. However, general CNNs can't use superpixel images in which the adjacency relationships between pixels are broken. Therefore, we define CNNs and Dilated Convolution on superpixels. Finally, we show the effectiveness of proposed method on an HKU-IS dataset.

    Original languageEnglish
    Title of host publication2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
    PublisherIEEE Computer Society
    Pages3249-3253
    Number of pages5
    ISBN (Electronic)9781479970612
    DOIs
    Publication statusPublished - 2018 Aug 29
    Event25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece
    Duration: 2018 Oct 72018 Oct 10

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    ISSN (Print)1522-4880

    Conference

    Conference25th IEEE International Conference on Image Processing, ICIP 2018
    CountryGreece
    CityAthens
    Period18/10/718/10/10

    Keywords

    • Convolutional Neural Networks
    • Saliency Object Detection
    • Segmentation
    • Super-pixel

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

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  • Cite this

    Suzuki, T., Akizuki, S., Kato, N., & Aoki, Y. (2018). Superpixel convolution for segmentation. In 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings (pp. 3249-3253). [8451721] (Proceedings - International Conference on Image Processing, ICIP). IEEE Computer Society. https://doi.org/10.1109/ICIP.2018.8451721