Range-Sample Depth Feature for Action Recognition

@article{Lu2014RangeSampleDF,
  title={Range-Sample Depth Feature for Action Recognition},
  author={Cewu Lu and Jiaya Jia and Chi-Keung Tang},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2014},
  pages={772-779}
}
We propose binary range-sample feature in depth. It is based on τ tests and achieves reasonable invariance with respect to possible change in scale, viewpoint, and background. It is robust to occlusion and data corruption as well. The descriptor works in a high speed thanks to its binary property. Working together with standard learning algorithms, the proposed descriptor achieves state-of-the-art results on benchmark datasets in our experiments. Impressively short running time is also yielded. 
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