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PerSign: Personalized Bangladeshi Sign Letters Synthesis

arXiv 2209.14591 ↗First posted 29 Sep 2022cs.CV cs.HCcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 18 references that are in the map. First posted on arXiv 29 Sep 2022.

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5 of 18 references.

References · 5

  1. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  2. 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,161
  3. 2018GestureGAN for Hand Gesture-to-Gesture Translation in the Wildcited by 27
  4. 2021BdSL36: A Dataset for Bangladeshi Sign Letters Recognitioncited by 7
  5. 2018Real Time Bangladeshi Sign Language Detection using Faster R-CNNcited by 6

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