Hand shape estimation for South African sign language

• Main Author: Li, Pei
• Other Authors: Connan, James
• Language: en
• Published: University of the Western Cape 2015
• Subjects: Sign language; Sign language recognition; Hand shape recognition; Hand tracking
• Online Access: http://hdl.handle.net/11394/4374

>Magister Scientiae - MSc === Hand shape recognition is a pivotal part of any system that attempts to implement Sign Language recognition. This thesis presents a novel system which recognises hand shapes from a single camera view in 2D. By mapping the recognised hand shape from 2D to 3D,it is possible to obtain 3D co-ordinates for each of the joints within the hand using the kinematics embedded in a 3D hand avatar and smooth the transformation in 3D space between any given hand shapes. The novelty in this system is that it does not require a hand pose to be recognised at every frame, but rather that hand shapes be detected at a given step size. This architecture allows for a more efficient system with better accuracy than other related systems. Moreover, a real-time hand tracking strategy was developed that works efficiently for any skin tone and a complex background.