Glass object localization by joint inference of boundary and depth

Tao Wang*, Xuming He, Nick Barnes

*Corresponding author for this work

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

    21 Citations (Scopus)

    Abstract

    We address the problem of localizing glass objects with a multimodal RGB-D camera. Our method integrates the intensity and depth information from a single view point, and builds a Markov Random Field that predicts glass boundary and region jointly. Based on the localization, we also reconstruct the depth of the scene and fill in the missing depth values. The efficacy of our algorithm is validated on a new RGB-D Glass dataset of 43 distinct glass objects.

    Original languageEnglish
    Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
    Pages3783-3786
    Number of pages4
    Publication statusPublished - 2012
    Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
    Duration: 11 Nov 201215 Nov 2012

    Publication series

    NameProceedings - International Conference on Pattern Recognition
    ISSN (Print)1051-4651

    Conference

    Conference21st International Conference on Pattern Recognition, ICPR 2012
    Country/TerritoryJapan
    CityTsukuba
    Period11/11/1215/11/12

    Fingerprint

    Dive into the research topics of 'Glass object localization by joint inference of boundary and depth'. Together they form a unique fingerprint.

    Cite this