Hand gesture recognition serves as a key for overcoming many difficulties and providing
convenience for human life. The ability of machines to understand human activities and their …

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 …

Human body trajectories are a salient cue to identify actions in video. Such body trajectories
are mainly conveyed by hands and face across consecutive frames in sign language …

Abstract Vision-based Continuous Sign Language Recognition (CSLR) aims to recognize
unsegmented signs from image streams. Overfitting is one of the most critical problems in …

In the recent past, research in the field of automatic sign language recognition using
machine learning methods have demonstrated remarkable success and made momentous …

Hand gesture recognition is viewed as a significant field of exploration in computer vision
with assorted applications in the human–computer communication (HCI) community. The …

The co-occurrence signals (eg, hand shape, facial expression, and lip pattern) play a critical
role in Continuous Sign Language Recognition (CSLR). Compared to RGB data, skeleton …

Sign language relies on visual gestures of human body parts to convey meaning and plays
a vital role in modern society to communicate and interact with people having hearing …

Sign language translation (SLT) is a challenging weakly supervised task without word-level
annotations. An effective method of SLT is to leverage multimodal complementarity and to …

It usually takes a fusion of image processing and machine learning algorithms in order to
build a fully-functioning computer vision system for hand gesture recognition. Fortunately …