Chereme-based recognition of isolated, dynamic gestures from South African sign language with Hidden Markov Models.
Much work has been done in building systems that can recognize gestures, e.g. as a component of sign language recognition systems. These systems typically use whole gestures as the smallest unit for recognition. Although high recognition rates have been reported, these systems do not scale well and are computationally intensive. The reason why these systems generally scale poorly is that they recognize gestures by building individual models for each separate gesture
School Location:South Africa
Source Type:Master's Thesis
Keywords:optical pattern recognition mathematical models image processing digital techniques markov processes
Date of Publication:01/01/2006