Improved rank pooling strategy for complex action recognition

@article{Mohammadi2017ImprovedRP,
  title={Improved rank pooling strategy for complex action recognition},
  author={Eman Mohammadi and Q. M. Jonathan Wu and Mehrdad Saif},
  journal={2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
  year={2017},
  pages={1351-1356}
}
Feature ranking from video-wide temporal evolution brings reliable information for complex action recognition. However, a video may contain similar features in the sequence of frames which deliver unnecessary information to the ranking function. This paper proposes a method to improve the rank-pooling strategy which captures the optimized latent structure of the video sequence data. The optimization is followed by removing the redundant features from the sequence data. The cosine and… CONTINUE READING

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