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Multistage Multiscale Inference Network with Visibility Attention for Occluded Person Re-Identification

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dc.contributor.advisorWildes, Richard
dc.contributor.authorKim, Yoon Tae
dc.date.accessioned2021-07-06T12:42:02Z
dc.date.available2021-07-06T12:42:02Z
dc.date.copyright2021-02
dc.date.issued2021-07-06
dc.date.updated2021-07-06T12:42:02Z
dc.degree.disciplineComputer Science
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractFor occluded person re-identification this thesis presents the Multistage Multiscale Inference Network (MMI-Net) that leverages an inference framework based on multiscale representations with visibility guidance. MMI-Net consists of three sub-networks, i) global, ii) part-based and iii) integrated, to infer person re-identification. The global inference sub-network provides an overall holistic analysis of input images. The part-based sub-network captures more localized information. Both the global and part-based models make use of multiscale representation across multiple processing stages to capture a variety of complementary discriminative image structure. The integrated sub-network aggregates the global and part-based representations to obtain the final fusion of all extracted information. Pose guided attentional processing is used to provide robustness to occlusion. MMI-Net is unique in its integrated multistage inference architecture that accounts for local and global appearance with attentional processing. In empirical evaluation, MMI-Net outperforms current existing methods on multiple occluded person re-identification datasets.
dc.identifier.urihttp://hdl.handle.net/10315/38432
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer science
dc.subject.keywordsComputer Vision
dc.subject.keywordsPerson Re-Identification
dc.subject.keywordsTracking
dc.subject.keywordsDeep Learning
dc.subject.keywordsMachine Learning
dc.titleMultistage Multiscale Inference Network with Visibility Attention for Occluded Person Re-Identification
dc.typeElectronic Thesis or Dissertation

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