Abstract. A sign language recognition system based on Hidden Markov Models(HMMs) and Auto-regressive Hidden Markov Models(ARHMMs) has been proposed in this paper. ARHMMs fully cons...
Xiaolin Yang, Feng Jiang, Han Liu, Hongxun Yao, We...
As one of the important research areas of multimodal interaction, sign language recognition (SLR) has attracted increasing interest. In SLR, especially on medium or large vocabula...
In this paper, we employ a zero-order local deformation model to model the visual variability of video streams of American sign language (ASL) words. We discuss two possible ways o...
Morteza Zahedi, Daniel Keysers, Thomas Deselaers, ...
Handshape is a key linguistic component of signs, and thus, handshape recognition is essential to algorithms for sign language recognition and retrieval. In this work, linguistic ...
Ashwin Thangali, Stan Sclaroff, Carol Neidle, Joan...
Abstract. This paper presents a novel approach to sign language recognition that provides extremely high classification rates on minimal training data. Key to this approach is a 2 ...
Richard Bowden, David Windridge, Timor Kadir, Andr...