Indian Sign Language Recognition: A Survey

Indian Sign Language Recognition: A Survey

Utkarsh Jagtap1, Vinayak Nangnurkar2, Suhas Chalwadi3, Neelam Jadhav4

Department of Computer Engineering

Genba Sopanrao Moze College of Engineering, Balewadi, Pune 45

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Abstract - This paper discusses the literature review of sign language recognition systems, which is an important research area in the field of computer vision and machine learning. The focus of the review is on Indian Sign Language (ISL) recognition systems, which have been developed by various practitioners with varying scopes. The reviewed literature includes five papers that use different approaches for feature extraction and recognition, such as clustering and deep learning algorithms. The data sets used in the reviewed literature have distinct qualities from one another in terms of input modality, sample size, and words or signs included in the dataset. The paper provides a detailed analysis of the data presented in the reviewed literature. Overall, this review aims to provide a comprehensive understanding of the current state of research in ISL recognition systems and to highlight the areas that require further research.

Key Words:  Mediapipe , CNN, Indian sign language , Deep learning, Clustering