PerSign: Personalized Bangladeshi Sign Letters Synthesis
September 29, 2022 Β· Declared Dead Β· π ACM Symposium on User Interface Software and Technology
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Authors
Mohammad Imrul Jubair, Ali Ahnaf, Tashfiq Nahiyan Khan, Ullash Bhattacharjee, Tanjila Joti
arXiv ID
2209.14591
Category
cs.CV: Computer Vision
Cross-listed
cs.HC
Citations
0
Venue
ACM Symposium on User Interface Software and Technology
Last Checked
4 months ago
Abstract
Bangladeshi Sign Language (BdSL) - like other sign languages - is tough to learn for general people, especially when it comes to expressing letters. In this poster, we propose PerSign, a system that can reproduce a person's image by introducing sign gestures in it. We make this operation personalized, which means the generated image keeps the person's initial image profile - face, skin tone, attire, background - unchanged while altering the hand, palm, and finger positions appropriately. We use an image-to-image translation technique and build a corresponding unique dataset to accomplish the task. We believe the translated image can reduce the communication gap between signers (person who uses sign language) and non-signers without having prior knowledge of BdSL.
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