English

PerSign: Personalized Bangladeshi Sign Letters Synthesis

Computer Vision and Pattern Recognition 2022-09-30 v1 Human-Computer Interaction

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.

Keywords

Cite

@article{arxiv.2209.14591,
  title  = {PerSign: Personalized Bangladeshi Sign Letters Synthesis},
  author = {Mohammad Imrul Jubair and Ali Ahnaf and Tashfiq Nahiyan Khan and Ullash Bhattacharjee and Tanjila Joti},
  journal= {arXiv preprint arXiv:2209.14591},
  year   = {2022}
}

Comments

Accepted at ACM UIST 2022 (poster)