This work presents a meta study covering around 300 published sign language recognition
papers with over 400 experimental results. It includes most papers between the start of the …

In contrast to speech recognition, whose speech features have been extensively explored in
the research literature, feature extraction in Sign Language Recognition (SLR) is still a very …

This chapter covers the key aspects of sign-language recognition (SLR), starting with a brief
introduction to the motivations and requirements, followed by a précis of sign linguistics and …

This paper proposes a novel multi-layered gesture recognition method with Kinect. We
explore the essential linguistic characters of gestures: the components concurrent character …

This paper presents an approach to large lexicon sign recognition that does not require
tracking. This overcomes the issues of how to accurately track the hands through self …

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 of …

In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language
recognition system is built on the SIGNUM database. The system is trained on appearance …

Present work deals with the incorporation of non-manual cues in automatic sign language
recognition. More specifically eye gaze, head pose and facial expressions are discussed in …

In this paper, we study one-shot learning gesture recognition on RGB-D data recorded from
Microsoft's Kinect. To this end, we propose a novel bag of manifold words (BoMW)-based …

2017 marked the release of a new version of SignStream® software, designed to facilitate
linguistic analysis of ASL video. SignStream® provides an intuitive interface for labeling and …