This paper introduces a fuzzy rule-based method for the recognition of hand gestures acquired from a data glove, and a way to show the recognized hand gesture using the graphical symbols provided by the HamNoSys notation system. The method uses the set of angles of finger joints for the classification of hand configurations, and classifications of segments of hand gestures for recognizing gestures. The segmentation of gestures is based on the concept of "monotonic" gesture segment, i.e., sequences of hand configurations in which the variations of the angles of the finger joints have the same tendency (either non-increasing or non-decreasing), separated by reference hand configurations that mark the inflexion points in the sequence. Each gesture is characterized by its list of monotonic segments. The set of all lists of segments of a given set of gestures determine a set of finite automata that recognize such gestures. For each gesture, a sequence of HamNoSys symbols representing the reference hand configurations of the gesture is produced as an output.
@inproceedings{costa:06011:sign-lang:lrec,
author = {Costa, Ant{\^o}nio Carlos da Rocha and Dimuro, Gra{\c c}aliz Pereira and Bedregal, Benjamin C.},
title = {Recognizing Hand Gestures Using a Fuzzy Rule-Based Method and Representing them with {HamNoSys}},
pages = {55--58},
editor = {Vettori, Chiara},
booktitle = {Proceedings of the {LREC2006} 2nd Workshop on the Representation and Processing of Sign Languages: Lexicographic Matters and Didactic Scenarios},
maintitle = {5th International Conference on Language Resources and Evaluation ({LREC} 2006)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Genoa, Italy},
day = {28},
month = may,
year = {2006},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/06011.pdf}
}