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Machine Learning of Motion Statistics Reveals the Kinematic Signature of the Identity of a Person in Sign Language
- Source :
- Frontiers in Bioengineering and Biotechnology, Frontiers in Bioengineering and Biotechnology, Frontiers, 2021, 9, ⟨10.3389/fbioe.2021.710132⟩, Frontiers in Bioengineering and Biotechnology, 2021, 9, ⟨10.3389/fbioe.2021.710132⟩, Frontiers in Bioengineering and Biotechnology, Vol 9 (2021)
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- International audience; Sign language (SL) motion contains information about the identity of a signer, as does voice for a speaker or gait for a walker. However, how such information is encoded in the movements of a person remains unclear. In the present study, a machine learning model was trained to extract the motion features allowing for the automatic identification of signers. A motion capture (mocap) system recorded six signers during the spontaneous production of French Sign Language (LSF) discourses. A principal component analysis (PCA) was applied to time-averaged statistics of the mocap data. A linear classifier then managed to identify the signers from a reduced set of principal components (PCs). The performance of the model was not affected when information about the size and shape of the signers were normalized. Posture normalization decreased the performance of the model, which nevertheless remained over five times superior to chance level. These findings demonstrate that the identity of a signer can be characterized by specific statistics of kinematic features, beyond information related to size, shape, and posture. This is a first step toward determining the motion descriptors necessary to account for the human ability to identify signers.
- Subjects :
- Normalization (statistics)
Histology
Computer science
Feature extraction
Biomedical Engineering
Bioengineering
Linear classifier
French Sign Language
Sign language
Machine learning
computer.software_genre
Motion capture
Identity (music)
Motion (physics)
03 medical and health sciences
[SCCO]Cognitive science
0302 clinical medicine
Statistics
motion capture
sign language
[INFO]Computer Science [cs]
030304 developmental biology
Original Research
0303 health sciences
person identification
human movements
business.industry
feature extraction
Bioengineering and Biotechnology
language.human_language
machine learning
statistics
language
Artificial intelligence
business
computer
TP248.13-248.65
030217 neurology & neurosurgery
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 22964185
- Database :
- OpenAIRE
- Journal :
- Frontiers in Bioengineering and Biotechnology, Frontiers in Bioengineering and Biotechnology, Frontiers, 2021, 9, ⟨10.3389/fbioe.2021.710132⟩, Frontiers in Bioengineering and Biotechnology, 2021, 9, ⟨10.3389/fbioe.2021.710132⟩, Frontiers in Bioengineering and Biotechnology, Vol 9 (2021)
- Accession number :
- edsair.doi.dedup.....555c51c46229a11d54adf2912dd99799