A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
The major challenges that sign language recognition (SLR) now faces are developing methods that solve largevocabulary continuous sign problems. In this paper, transitionmovement models (TMMs) are proposed to handle transition parts between two adjacent signs in large-vocabulary continuous SLR. For tackling mass transition movements arisen from a large vocabulary size, a temporal clustering algorithm improved from k-means by using dynamic time warping as its distance measure is proposed todoi:10.1109/tsmca.2006.886347 fatcat:2riou3fzonetdlnigj6asvv6o4