Review on Sign Language Detection Using Action Detection

Abstract

The development of sign language as a means of communication for those with hearing loss has been a significant step. Sign language is always needed for communication as not everyone understands how to translate signs. Without an interpreter, it is challenging to communicate. The hand shape, motion profile, and positioning of the hand, face, and other body components vary amongst signs in a particular sign language. Therefore, visual sign language detection is a difficult area of computer vision research. To overcome this, we need a flexible and long-lasting solution. For barrier-free communication, sign language must be translated so that it may be utilised by the broader population. The two primary methods for detecting sign language are image-based and sensor-based strategies. An image-based solution employs one or more cameras to record a series of images of the signer making the sign, which are then processed by image recognition software to identify the sign. The sensor-based approach tracks the hand articulations using instrumental gloves that have sensors built in. This project's primary goal is to break down barriers that separate the deaf and dumb from the rest of society