Inspired by the Defense Advanced Research Projects Agency's (DARPA) recent successes in speech recognition, we introduce a new task for sign language recognition research: a ...
R. Martin McGuire, Jose L. Hernandez-Rebollar, Tha...
To collect data for sign language recognition is not a trivial task. The lack of training data has become a bottleneck in the research of singer independence and large vocabulary r...
Sign language recognition (SLR) plays an important role in human-computer interaction (HCI), especially for the convenient communication between deaf and hearing society. How to e...
Sign language recognition constitutes a challenging field of research in computer vision. Common problems like overlap, ambiguities, and minimal pairs occur frequently and require...
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...
Hitherto, one major challenge to sign language recognition is how to develop approaches that scale well with increasing vocabulary size. In large vocabulary speech recognition real...
In Sign Language recognition, one of the problems is to collect enough data. Data collection for both training and testing is a laborious but necessary step. Almost all of the stat...
CopyCat is an American Sign Language (ASL) game, which uses gesture recognition technology to help young deaf children practice ASL skills. We describe a brief history of the game...
Helene Brashear, Valerie L. Henderson, Kwang-Hyun ...
This paper presents a unified system for segmentation and tracking of face and hands in a sign language recognition using a single camera. Unlike much related work that uses colou...
We address multistream sign language recognition and focus on efficient multistream integration schemes. Alternative approaches are investigated and the application of Product-HM...