TY - GEN
T1 - Capturing Distalization
AU - Stamp, Rose
AU - Khatib, Lilyana
AU - Hel-Or, Hagit
N1 - Publisher Copyright: © European Language Resources Association (ELRA), licensed under CC-BY-NC 4.0.
PY - 2022
Y1 - 2022
N2 - Coding and analyzing large amounts of video data is a challenge for sign language researchers, who traditionally code 2D video data manually. In recent years, the implementation of 3D motion capture technology as a means of automatically tracking movement in sign language data has been an important step forward. Several studies show that motion capture technologies can measure sign language movement parameters - such as volume, speed, variance - with high accuracy and objectivity. In this paper, using motion capture technology and machine learning, we attempt to automatically measure a more complex feature in sign language known as distalization. In general, distalized signs use the joints further from the torso (such as the wrist), however, the measure is relative and therefore distalization is not straightforward to measure. The development of a reliable and automatic measure of distalization using motion tracking technology is of special interest in many fields of sign language research.
AB - Coding and analyzing large amounts of video data is a challenge for sign language researchers, who traditionally code 2D video data manually. In recent years, the implementation of 3D motion capture technology as a means of automatically tracking movement in sign language data has been an important step forward. Several studies show that motion capture technologies can measure sign language movement parameters - such as volume, speed, variance - with high accuracy and objectivity. In this paper, using motion capture technology and machine learning, we attempt to automatically measure a more complex feature in sign language known as distalization. In general, distalized signs use the joints further from the torso (such as the wrist), however, the measure is relative and therefore distalization is not straightforward to measure. The development of a reliable and automatic measure of distalization using motion tracking technology is of special interest in many fields of sign language research.
KW - Israeli Sign Language
KW - Kinect Azure
KW - distalization
KW - motion capture
KW - proximalization
UR - http://www.scopus.com/inward/record.url?scp=85146255727&partnerID=8YFLogxK
M3 - منشور من مؤتمر
T3 - 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, sign-lang 2022 - held in conjunction with the International Conference on Language Resources and Evaluation, LREC 2022 - Proceedings
SP - 187
EP - 191
BT - 10th Workshop on the Representation and Processing of Sign Languages
A2 - Efthimiou, Eleni
A2 - Fotinea, Stavroula-Evita
A2 - Hanke, Thomas
A2 - Hochgesang, Julie A.
A2 - Kristoffersen, Jette
A2 - Mesch, Johanna
A2 - Schulder, Marc
T2 - 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, sign-lang 2022
Y2 - 20 June 2022 through 25 June 2022
ER -