@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.html},
  abstract  = {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:04007:sign-lang:lrec,
  author    = {Costa, Ant{\^o}nio Carlos da Rocha and Dimuro, Gra{\c c}aliz Pereira and Baldez de Freitas, Juliano},
  title     = {A Sign Matching Technique to Support Searches in Sign Language Texts},
  pages     = {32--36},
  editor    = {Streiter, Oliver and Vettori, Chiara},
  booktitle = {Proceedings of the {LREC2004} Workshop on the Representation and Processing of Sign Languages: From {SignWriting} to Image Processing. Information techniques and their implications for teaching, documentation and communication},
  maintitle = {4th International Conference on Language Resources and Evaluation ({LREC} 2004)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Lisbon, Portugal},
  day       = {30},
  month     = may,
  year      = {2004},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/04007.html},
  abstract  = {This paper presents a technique for matching two signs written in the SignWriting system. We have defined such technique to support procedures for searching in sign language texts that were written in that writing system. Given the graphical nature of SignWriting, a graphical pattern matching method is needed, which can deal in controlled ways with the small graphical variations writers can introduce in the graphical forms of the signs, when they write them. The technique we present builds on a so-called degree of graphical similarity between signs, allowing for a sort of ``fuzzy'' graphical pattern matching procedure for written signs.}
}