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Sign language images dataset from Mexican sign language
Josué Espejel1, Laura D Jalili1, Jair Cervantes1
1UAEMEX (Autonomous University of Mexico State), Texcoco 56259, Mexico.
Data in Brief
|July 1, 2024
Summary
This study addresses the lack of formal datasets for Mexican Sign Language (MSL) by creating a structured dataset of 249 MSL words. The dataset includes 31,442 images captured using specific visual enhancements for better recognition.
Area of Science:
- Linguistics
- Computer Science
- Human-Computer Interaction
Background:
- Sign languages are complete linguistic systems with unique grammar.
- Variations across countries highlight the need for country-specific documentation.
- A formal dataset for Mexican Sign Language (MSL) is currently lacking.
Purpose of the Study:
- To address the deficit of formal datasets for Mexican Sign Language (MSL).
- To structure and create a comprehensive dataset for MSL research and development.
Main Methods:
- A dataset of 249 MSL words was structured into 17 subsets.
- Videos were recorded using black backgrounds and clothing to enhance focus on hands and face.
- An average of 11 individuals per word, with 15 frames per video sequence, yielded 31,442 JPG images.
Main Results:
- A novel dataset of 31,442 images for 249 Mexican Sign Language words was successfully created.
- The dataset employs visual enhancements (black background/clothing) to improve feature extraction.
- Data was collected from multiple individuals to capture sign variations.
Conclusions:
- The developed dataset provides a foundational resource for advancing Mexican Sign Language research.
- This structured dataset can facilitate the development of MSL recognition technologies.
- The dataset's methodology offers a model for documenting other sign languages.
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