@InProceedings{Mikulik-ACCV14,
  IS = { zkontrolovano 26 Jun 2015 },
  UPDATE  = { 2015-05-19 },
	author={Mikul{\'\i}k, Andrej and Radenovi{\'c}, Filip and
                  Chum, Ond{\v{r}}ej and Matas, Ji{\v{r}}{\'\i}},
	title={Efficient Image Detail Mining},
	affiliation={13133-13133-13133-13133},
	year={2015},
	pages={118-132},
	booktitle={{ACCV} 2014: Proceedings of the 12th Asian
                  Conference on Computer Vision, Part {II}},
	editor={Cremers, Daniel and Reid, Ian and Saito, Hideo and Yang, Ming-Hsuan},
	publisher={Springer},
	series={Lecture Notes in Computer Science},
	volume={9004},
	address={Gewerbestrasse 11, Cham, Switzerland},
	issn={0302-9743},
	isbn={978-3-319-16807-4},
	book_pages={709},
	year_of_conference={2014},
    month={November},
    day={1--5},
    venue={Singapore,Singapore},
    prestige={international},
    annote = {Two novel problems straddling the boundary between image
                  retrieval and data min ing are formulated: for every
                  pixel in the query image, (i) find the database
                  image with the maximum resolution depicting the
                  pixel and (ii) find the frequency with which it is
                  photograp hed in detail. An efficient and reliable
                  solution for both problems is proposed based on two
                  novel techniques, the hierarchical query expansion
                  that exploits the document at a time (DAAT )
                  inverted file and a geometric consistency
                  verification sufficiently robust to prevent topic
                  drift within a zooming search. Experiments show that
                  the proposed method finds surprisingly fine details
                  on landmarks, even those that are hardly noticeable
                  for humans.},
    keywords =   {image retrieval, details retrieval, hierarchical
                  query expansion, geometric consistency verification},
    psurl={http://cmp.felk.cvut.cz/~radenfil/publications/Mikulik-ACCV14.pdf},
    project =    {ERC-CZ LL1303, GACR P103/12/G084, SGS13/142/OHK3/2T/13},
    authorship = {25-25-25-25},
}