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
Link To Document