Title :
Learning gestures for interacting with low-fidelity prototypes
Author :
De Souza Alcantara, Tulio ; Denzinger, Jörg ; Ferreira, Jennifer ; Maurer, Frank
Author_Institution :
Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada
Abstract :
This paper presents an approach to help designers create their own application-specific gestures and evaluate them in user-studies based on low fidelity prototypes of the application they are designing. In order to learn custom gestures, we developed a machine learning tool that uses an anti-unification algorithm to learn based on samples of the gesture provided by the designer.
Keywords :
gesture recognition; human computer interaction; learning (artificial intelligence); antiunification algorithm; application-specific gestures; custom gestures; learning gesture; low-fidelity prototype; machine learning tool; user-studies; Context; Educational institutions; Fingers; Gesture recognition; Hidden Markov models; Prototypes; Training; anti-unification; custom gestures; low-fidelity prototyping;
Conference_Titel :
Realizing Artificial Intelligence Synergies in Software Engineering (RAISE), 2012 First International Workshop on
Conference_Location :
Zurich
Print_ISBN :
978-1-4673-1752-8
DOI :
10.1109/RAISE.2012.6227967
