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 …

This work presents a statistical recognition approach performing large vocabulary
continuous sign language recognition across different signers. Automatic sign language …

This work presents a new approach to learning a frame-based classifier on weakly labelled
sequence data by embedding a CNN within an iterative EM algorithm. This allows the CNN …

Gesture recognition pertains to recognizing meaningful expressions of motion by a human,
involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an …

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 …

Within the context of hand gesture recognition, spatiotemporal gesture segmentation is the
task of determining, in a video sequence, where the gesturing hand is located and when the …

Sign language spotting is the task of detecting and recognizing signs in a signed utterance,
in a set vocabulary. The difficulty of sign language spotting is that instances of signs vary in …

The widespread adoption of personal service robots will likely depend on how well they
interact with users. This chapter was motivated by a desire to facilitate the design of usable …

The proposed work is part of a project that aims for the control of a videogame based on
hand gesture recognition. This goal implies the restriction of real-time response and …

We investigate the problem of recognizing words from video, fingerspelled using the British
Sign Language (BSL) fingerspelling alphabet. This is a challenging task since the BSL …