Analysis of Genetic Programming in Gait Recognition

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Dipak Gaire Sharma and Ivan Tanev and 
                 Katsunori Shimohara",
  title =        "Analysis of Genetic Programming in Gait Recognition",
  booktitle =    "Proceedings of 2015 IEEE Congress on Evolutionary
                 Computation (CEC 2015)",
  year =         "2015",
  editor =       "Yadahiko Murata",
  pages =        "1418--1423",
  address =      "Sendai, Japan",
  month =        "25-28 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2015.7257054",
  abstract =     "Analysis of human motion is one of the most curious
                 fields among different disciplines of socio-psychology,
                 neuro biology and computer science. A person's walk is
                 so crucial because it is associated with lots of other
                 aspects which yield very important information related
                 to emotions, personality, and neurological disorder.
                 The morphological and psychological information induced
                 from both the physiology and neurology involved in
                 motion is one of the key research fields that could one
                 day resolve the various challenges existing in today's
                 intelligent systems inspired from nature. The most
                 interesting among all these is, those wealth of data
                 can be artificially trained using the complex systems
                 in response to generate evidences for identifying the
                 particular person [1]. This paper is the extension of
                 human gait recognition which presents the analysis of
                 efficiency of genetic programming in different cases
                 involved in feature extraction and gait recognition.",
  notes =        "1315 hrs 15350 CEC2015",

Genetic Programming entries for Dipak Gaire Sharma Ivan T Tanev Katsunori Shimohara