Bag-of-visual-words and spatial extensions for land-use classification

@inproceedings{Yang2010BagofvisualwordsAS,
  title={Bag-of-visual-words and spatial extensions for land-use classification},
  author={Yi Yang and Shawn D. Newsam},
  booktitle={GIS},
  year={2010}
}
We investigate bag-of-visual-words (BOVW) approaches to land-use classification in high-resolution overhead imagery. We consider a standard non-spatial representation in which the frequencies but not the locations of quantized image features are used to discriminate between classes analogous to how words are used for text document classification without regard to their order of occurrence. We also consider two spatial extensions, the established spatial pyramid match kernel which considers the… CONTINUE READING
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References

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Showing 1-3 of 3 references

Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision • 2004
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Object Recognition from Local Scale-Invariant Features

ICCV • 1999
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Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 • 2005
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