A Spatiotemporal Oriented Energy Network for Dynamic Texture Recognition

@article{Hadji2017ASO,
  title={A Spatiotemporal Oriented Energy Network for Dynamic Texture Recognition},
  author={Isma Hadji and Richard P. Wildes},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={3085-3093}
}
This paper presents a novel hierarchical spatiotemporal orientation representation for spacetime image analysis. It is designed to combine the benefits of the multilayer architecture of ConvNets and a more controlled approach to spacetime analysis. A distinguishing aspect of the approach is that unlike most contemporary convolutional networks no learning is involved; rather, all design decisions are specified analytically with theoretical motivations. This approach makes it possible to… CONTINUE READING
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