Action Recognition Using Subtensor Constraint

  • Qiguang Liu
  • Xiaochun Cao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7574)


Human action recognition from videos draws tremendous interest in the past many years. In this work, we first find that the trifocal tensor resides in a twelve dimensional subspace of the original space if the first two views are already matched and the fundamental matrix between them is known, which we refer to as subtensor. Then we use the subtensor to perform the task of action recognition under three views. We find that treating the two template views separately or not considering the correspondence relation already known between the first two views omits a lot of useful information. Experiments and datasets are designed to demonstrate the effectiveness and improved performance of the proposed approach.


Action Recognition Dynamic Time Warping Fundamental Matrix Testing Video Testing Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Qiguang Liu
    • 1
  • Xiaochun Cao
    • 1
  1. 1.School of Computer Science and TechnologyTianjin UniversityTianjinChina

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