The Maximal Self-dissimilarity Interest Point Detector

@article{Tombari2015TheMS,
  title={The Maximal Self-dissimilarity Interest Point Detector},
  author={Federico Tombari and Luigi di Stefano},
  journal={IPSJ Trans. Computer Vision and Applications},
  year={2015},
  volume={7},
  pages={175-188}
}
We propose a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of contextual self-dissimilarity reverses the key paradigm of recent successful techniques such as the Local Self… CONTINUE READING