Human Recognition based on Gait Features and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Dipak Sharma and Rahadian Yusuf and Ivan Tanev and 
                 Katsunori Shimohara",
  title =        "Human Recognition based on Gait Features and Genetic
  journal =      "Journal of Robotics, Networking and Artificial Life",
  year =         "2014",
  volume =       "1",
  number =       "3",
  pages =        "194--197",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, Human
                 Identification, Biometrics, Genetic Programming, Human
                 Gaits, Nature Inspired Computing",
  ISSN =         "2352-6386",
  URL =          "",
  DOI =          "doi:10.2991/jrnal.2014.1.3.5",
  size =         "4 pages",
  abstract =     "Human walking has always been the curious field of
                 research for different disciple of social and
                 information science. The study of human walk or human
                 gait in association with different behaviours and
                 emotions has not only fascinated social science
                 researchers, but its uniqueness has also attracted many
                 computer scientists to work in this arena for the quest
                 of uncovering reliable mechanisms of biometric
                 identification. In this research, we used a novel
                 method for human identification based on inferring the
                 relationship between the human gait features via
                 genetic programming. Moreover, we focus on generating
                 the unique numerical signature that is similar for
                 different locomotion gaits of a particular individual
                 but different across different individuals",
  notes =        "",

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