Summary of 3d-lex V1.0: 3d Lexicons For American Sign Language and Sign Language Of the Netherlands, by Oline Ranum and Gomer Otterspeer and Jari I. Andersen and Robert G. Belleman and Floris Roelofsen
3D-LEX v1.0: 3D Lexicons for American Sign Language and Sign Language of the Netherlands
by Oline Ranum, Gomer Otterspeer, Jari I. Andersen, Robert G. Belleman, Floris Roelofsen
First submitted to arxiv on: 3 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents an efficient method for capturing American Sign Language (ASL) and the Sign Language of the Netherlands (SLN) in 3D. The approach integrates three motion capture techniques: high-resolution 3D poses, 3D handshapes, and depth-aware facial features. The dataset, called 3D-LEX v1.0, contains 2,000 signs with an average sampling rate of one sign every 10 seconds. The paper also proposes a semi-automatic method for annotating phonetic properties and showcases the utility of the dataset by generating handshape annotations from 3D-LEX. The results demonstrate that handshape labels enhance gloss recognition accuracy by 5% over using no handshape annotations, and by 1% over expert annotations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about a new way to capture sign language in three dimensions (3D). It helps researchers study sign language better by creating a big dataset of signs from American Sign Language and the Sign Language of the Netherlands. The dataset has lots of signs, taken at different times, and it’s very useful for recognizing handshapes and understanding what people are signing. |
