People with hearing impairments are found worldwide; therefore, the development of
effective local level sign language recognition (SLR) tools is essential. We conducted a …

This paper presents a literature review on the use of depth for hand tracking and gesture
recognition. The survey examines 37 papers describing depth-based gesture recognition …

Vision-based sign language recognition aims at hel** the hearing-impaired people to
communicate with others. However, most existing sign language datasets are limited to a …

Develo** successful sign language recognition, generation, and translation systems
requires expertise in a wide range of fields, including computer vision, computer graphics …

Sign language recognition is challenged by problems, such as accurate tracking of hand
gestures, occlusion of hands, and high computational cost. Recently, it has benefited from …

Sign language recognition is a challenging problem where signs are identified by
simultaneous local and global articulations of multiple sources, ie hand shape and …

We propose SignFi to recognize sign language gestures using WiFi. SignFi uses Channel
State Information (CSI) measured by WiFi packets as the input and a Convolutional Neural …

Sign language recognition is a challenging and often underestimated problem comprising
multi-modal articulators (handshape, orientation, movement, upper body and face) that …

Sign language facilitates communication between hearing impaired peoples and the rest of
the society. A number of sign language recognition (SLR) systems have been developed by …

Three-dimensional hand gesture recognition has attracted increasing research interests in
computer vision, pattern recognition, and human-computer interaction. The emerging depth …