Learning invariant region descriptor operators with genetic programming and the F-measure

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Cynthia B. Perez and Gustavo Olague",
  title =        "Learning invariant region descriptor operators with
                 genetic programming and the F-measure",
  booktitle =    "19th International Conference on Pattern Recognition
                 (ICPR 2008)",
  year =         "2008",
  pages =        "1--4",
  address =      "Tampa, Florida, USA",
  month =        dec # " 8-11",
  keywords =     "genetic algorithms, genetic programming, GPLAB",
  isbn13 =       "978-1-4244-2175-6",
  DOI =          "doi:10.1109/ICPR.2008.4761178",
  size =         "4 pages",
  abstract =     "Recognizing and localizing objects is a classical
                 problem in computer vision that is an important stage
                 for many automated systems. In order to perform object
                 recognition many researchers have focused on local
                 features as the basis of their proposed methodologies.
                 This work is devoted to the task of learning invariant
                 region descriptor operators with genetic programming.
                 The idea is to find a set of expressions that could be
                 equal or better than the weighted gradient magnitude
                 that is normally applied on the SIFT descriptor. This
                 magnitude corresponds to the operator that we would
                 like to improve through genetic programming (GP). The
                 key for a successful problem statement was achieved
                 with the F-measure. After a bibliographical study we
                 have found a criterion that is simple, reliable, and
                 useful in the estimation of such a metric. The measure
                 that we propose here is based on the harmonic mean
                 which is normally used by the information retrieval
                 community. Experimental results show that the evolved
                 descriptor's operator can enhance significantly the
                 overall performance of the SIFT descriptor and surpass
                 other state-of-the-art algorithms.",
  bibsource =    "DBLP, http://dblp.uni-trier.de",

Genetic Programming entries for Cynthia B Perez Gustavo Olague