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    Action Recognition Using Discriminative Structured Trajectory Groups

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    Name:
    Action Recognition using Discriminative Structured Trajectory Groups.pdf
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    5.701Mb
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    Description:
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    Type
    Conference Paper
    Authors
    Atmosukarto, Indriyati
    Ahuja, Narendra
    Ghanem, Bernard cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Image and Video Understanding Lab
    VCC Analytics Research Group
    Visual Computing Center (VCC)
    Date
    2015-02-24
    Online Publication Date
    2015-02-24
    Print Publication Date
    2015-01
    Permanent link to this record
    http://hdl.handle.net/10754/556158
    
    Metadata
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    Abstract
    In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.
    Citation
    Indriyati Atmosukarto, Narendra Ahuja, Bernard Ghanem "Action Recognition using Discriminative Structured Trajectory Groups" Winter Conference on Applications of Computer Vision (WACV 2015)​​​
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2015 IEEE Winter Conference on Applications of Computer Vision
    Conference/Event name
    2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015
    DOI
    10.1109/WACV.2015.124
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7045978
    http://vcc.kaust.edu.sa/Documents/B.%20Ghanem/papers/action_recognition_wacv2015.pdf
    ae974a485f413a2113503eed53cd6c53
    10.1109/WACV.2015.124
    Scopus Count
    Collections
    Conference Papers; Electrical and Computer Engineering Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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