HOSO: Histogram of Surface Orientation for RGB-D Salient Object Detection

David Feng, Nick Barnes, Shaodi You

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Citations (Scopus)

    Abstract

    Salient object detection using RGB-D data is an emerging field in computer vision. Salient regions are often characterized by an unusual surface orientation profile with respect to the surroundings. To capture such profile, we introduce the histogram of surface orientation (HOSO) feature to measure surface orientation distribution contrast for RGB-D saliency. We propose a new unified model that integrates surface orientation distribution contrast with depth and color contrast across multiple scales. This model is implemented in a multi-stage saliency computation approach that performs contrast estimation using a kernel density estimator (KDE), estimates object positions from the low-level saliency map, and finally refines the estimated object positions with a graph cut based approach. Our method is evaluated on two RGB-D salient object detection databases, achieving superior performance to previous state-of-the-art methods.

    Original languageEnglish
    Title of host publicationDICTA 2017 - 2017 International Conference on Digital Image Computing
    Subtitle of host publicationTechniques and Applications
    EditorsYi Guo, Manzur Murshed, Zhiyong Wang, David Dagan Feng, Hongdong Li, Weidong Tom Cai, Junbin Gao
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-8
    Number of pages8
    ISBN (Electronic)9781538628393
    DOIs
    Publication statusPublished - 19 Dec 2017
    Event2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017 - Sydney, Australia
    Duration: 29 Nov 20171 Dec 2017

    Publication series

    NameDICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications
    Volume2017-December

    Conference

    Conference2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017
    Country/TerritoryAustralia
    CitySydney
    Period29/11/171/12/17

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