Papers by Thibaut Le Naour
A Low-Cost Motion Capture Corpus in French Sign Language for Interpreting Iconicity and Spatial Referencing Mechanisms (2022.lrec-1)
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| Challenge: | Existing tools for automatic translation of sign language videos into transcribed texts are limited. |
| Approach: | They propose to use deep learning methods to circumvent the use of models in spatial referencing recognition by a 3D skeleton and a software program to capture and post-process the LSF-SHELVES corpus. |
| Outcome: | The proposed system targets iconicity and spatial referencing in french sign language . it is light-weight and low-cost to collect data from a large panel of signers . |