@inproceedings{jantunen:12003:sign-lang:lrec,
  author    = {Jantunen, Tommi and Burger, Birgitta and De Weerdt, Danny and Seilola, Irja and Wainio, Tuija},
  title     = {Experiences collecting motion capture data on continuous signing},
  pages     = {75--82},
  editor    = {Crasborn, Onno and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Kristoffersen, Jette and Mesch, Johanna},
  booktitle = {Proceedings of the {LREC2012} 5th Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon},
  maintitle = {8th International Conference on Language Resources and Evaluation ({LREC} 2012)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Istanbul, Turkey},
  day       = {27},
  month     = may,
  year      = {2012},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/12003.html},
  abstract  = {This paper describes some of the experiences the authors have had collecting continuous motion capture data on Finnish Sign Language in the motion capture laboratory of the Department of Music at the University of Jyv{\"a}skyl{\"a}, Finland. Monologue and dialogue data have been recorded with an eight-camera optical motion capture system by tracking, at a frame rate of 120 Hz, the three-dimensional locations of small ball-shaped reflective markers attached to the signer's hands, arms, head, and torso. The main question from the point of view of data recording concerns marker placement, while the main themes discussed concerning data processing include gap-filling (i.e. the process of interpolating the information of missing frames on the basis of surrounding frames) and the importing of data into ELAN for subsequent segmentation (e.g. into signs and sentences). The paper will also demonstrate how the authors have analyzed the continuous motion capture data from the kinematic perspective.}
}

@inproceedings{karppa-etal-2012-comparing:lrec,
  author    = {Karppa, Matti and Jantunen, Tommi and Viitaniemi, Ville and Laaksonen, Jorma and Burger, Birgitta and De Weerdt, Danny},
  title     = {Comparing computer vision analysis of signed language video with motion capture recordings},
  pages     = {2421--2425},
  editor    = {Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Do{\u g}an, Mehmet U{\u g}ur and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
  booktitle = {8th International Conference on Language Resources and Evaluation ({LREC} 2012)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Istanbul, Turkey},
  day       = {21--27},
  month     = may,
  year      = {2012},
  isbn      = {978-2-9517408-7-7},
  language  = {english},
  url       = {https://aclanthology.org/L12-1152},
  abstract  = {We consider a non-intrusive computer-vision method for measuring the motion of a person performing natural signing in video recordings. The quality and usefulness of the method is compared to a traditional marker-based motion capture set-up. The accuracy of descriptors extracted from video footage is assessed qualitatively in the context of sign language analysis by examining if the shape of the curves produced by the different means resemble one another in sequences where the shape could be a source of valuable linguistic information. Then, quantitative comparison is performed first by correlating the computer-vision-based descriptors with the variables gathered with the motion capture equipment. Finally, multivariate linear and non-linar regression methods are applied for predicting the motion capture variables based on combinations of computer vision descriptors. The results show that even the simple computer vision method evaluated in this paper can produce promisingly good results for assisting researchers working on sign language analysis.}
}