Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/138679
Title: FOREGROUND-CENTRIC ACTION RECOGNITION
Authors: TRAN LAM AN
ORCID iD:   orcid.org/0000-0003-4355-812X
Keywords: foreground-centric, action recognition, video classification, video prediction
Issue Date: 16-Aug-2017
Citation: TRAN LAM AN (2017-08-16). FOREGROUND-CENTRIC ACTION RECOGNITION. ScholarBank@NUS Repository.
Abstract: Video is highly unstructured and high dimensional data. While action recognition has been an active research topic, modeling structures in video is often a challenging problem. Modeling structures would reduce search spaces of learning problems in high dimensional video data and produce competitive performances. Inspired by these prospects, in this thesis, we attempt to develop structural action models based on a robust and prominent cue in video, figure-ground separation. Going through a paradigm shift in computer vision community, we also develop structural models powered by both shallow and deep predictive machinery.
URI: http://scholarbank.nus.edu.sg/handle/10635/138679
Appears in Collections:Ph.D Theses (Open)

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