Camera Motion and Surrounding Scene Appearance as Context for Action Recognition

Fabian Caba Heilbron Ali Thabet Juan Carlos Niebles Bernard Ghanem
KAUST, Universidad del Norte

ACCV 2014

Summary

This work introduces a framework for recognizing human actions in videos by incorporating a new set of visual cues that represent the context of the action. We develop a weak foreground-background segmentation approach in order to robustly extract not only foreground features that are focused on the actors, but also global camera motion and contextual scene information. Using dense point trajectories, our approach separates and describes the foreground motion from the background, represents the appearance of the extracted static background, and encodes the global camera motion that interestingly is shown to be discriminative for certain action classes. Below we show an example of our foreground-background segmentation:


Resources:

  • Download our ACCV 2014 Paper.
  • Check out our Poster presentation!
  • Code can be cloned from Here!

    • Acknowledgment

    Research reported in this publication was supported by competitive research funding from King Abdullah University of Science and Technology (KAUST). F.C.H. was also supported by a COLCIENCIAS Young Scientist and Innovator Fellowship. J.C.N. is supported by a Microsoft Research Faculty Fellowship.

    References

    1. H. Wang and C. Schmid. Action Recognition with Improved Trajectories. In ICCV, 2013.
      2.

    If you use any of this work material in your research, please cite our ACCV 2014 paper:

    F.C. Heilbron, A. Thabet, J.C. Niebles and B. Ghanem. Camera Motion and Surrounding Scene Appearance as Context for Action Recognition. In ACCV, 2014.

    @article{caba2014cues,
      title={{Camera Motion and Surrounding Scene Appearance as Context for Action Recognition}},
      author={Heilbron, F.C. and Thabet, A. and Niebles, J.C. and Ghanem, B.},
      journal={ACCV},
      year={2014}
    }