Decomposing spontaneous sign language into elementary movements: A principal component analysis-based approach.

ABSTRACT: Sign Language (SL) is a continuous and complex stream of multiple body movement features. That raises the challenging issue of providing efficient computational models for the description and analysis of these movements. In the present paper, we used Principal Component Analysis (PCA) to decompose SL motion into elementary movements called principal movements (PMs). PCA was applied to the upper-body motion capture data of six different signers freely producing discourses in French Sign Language. Common PMs were extracted from the whole dataset containing all signers, while individual PMs were extracted separately from the data of individual signers. This study provides three main findings: (1) although the data were not synchronized in time across signers and discourses, the first eight co

SUBMITTER: Bigand F 

PROVIDER: S-EPMC8555838 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature