• DocumentCode
    3035688
  • Title

    Investigating Human Performance in Hand-Drawn Symbol Autocompletion

  • Author

    Costagliola, Gennaro ; De Rosa, M. ; Fuccella, Vittorio

  • Author_Institution
    Dept. of Inf., Univ. of Salerno, Fisciano, Italy
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    279
  • Lastpage
    284
  • Abstract
    Auto completion has proven effective in various text-based applications. Conversely, no experiments have been carried out on the automatic completion of hand-drawn symbols and only a few systems have been presented in the literature for this purpose. Nevertheless, such a feature might be useful in different domains, e.g. for accelerating symbol retrieval and for launching complex gestural commands. In this paper we present a user study aimed at evaluating the human performance in hand-drawn symbol auto completion. In particular, using a set of more than 100 symbols belonging to the Military Course of Action domain, we evaluated the conditions under which the users are willing to exploit the auto completion functionality and those under which they can use it efficiently. As a result, we obtained that in a drawing task the auto completion functionality can be used in a profitable way, with a drawing time saving of about 18%.
  • Keywords
    gesture recognition; hand-drawn symbol autocompletion; human performance evaluation; military course of action domain; text-based applications; Accuracy; Atmospheric measurements; Complexity theory; Feature extraction; Interactive systems; Manuals; Particle measurements; Symbol recognition; interface; sketch; symbol autocompletion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.54
  • Filename
    6721807