@InProceedings{LENC-CVWW14,
  IS = { zkontrolovano 29 May 2014 },
  UPDATE  = { 2014-03-13 },
  booktitle = { CVWW2014: Proceedings of the 19th Computer Vision Winter Workshop},
  editor    = { Zuzana K{\' u}kelov{\' a} and Jan Heller },
  publisher = { Czech Society for Cybernetics and Informatics },
  address   = { Prague, Czech Republic },
  isbn      = { 978-80-260-5641-6 },
  book_pages = { 127 },
  title     = { A Few Things One Should Know About Feature Extraction, Description and Matching },
  author    = { Lenc, Karel and Matas, Ji{\v r}{\'\i} and Mishkin, Dmytro },
  pages     = { 67--74 },
  year      = { 2014 },
  month     = { February },
  day       = { 3--5 },
  venue     = { K{\v r}tiny, Czech Republic },
Keywords    = {feature detectors; image matching, feature descriptors},
 annote = {We explore the computational bottlenecks of the affine feature extraction process and sho
w how this process can be speeded up by 2-3 times with no or very modest loss of performance. With o
ur improvements the speed of the Hessian-Affine and MSER detector is comparable with similarity-inva
riant SURF and DoG-SIFT detectors. The improvements presented include a faster anisotropic patch ext
raction algorithm which does not depend on the feature scale, a speed up of a feature dominant orien
tation estimation and SIFT descriptor computation using a look-up table.
In the second part of the paper we explore performance of the recently proposed first geometrically 
inconsistent nearest neighbour criterion and domination orientation generation process.},
  project =     {FP7-ICT-270138 DARWIN, TACR TE01020415 V3C},
}