Publication:
Review On Hand Gesture Recognition for Bengali Sign Language

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Abstract

Communication becomes difficult when interaction between the disabled and the general public are required. People with disabilities of various races communicate using various sign languages. For persons who are deaf or hard of hearing sign language is their primary mode of communication. However, the majority of our community does not understand sign language, taking them out in public is incredibly challenging. In order to make sign language understandable to the general public, computer vision-based methods are now widely used. Recognition of hand gesture is one of the computer vision based technologies for recognizing sign language, and it is attracting a lot of attention from analysis. For a long time, it has been a popular research area. In the area of hand gesture recognition in computer vision, some recent research has achieved outstanding improvements by employing deep learning techniques. In this paper we have discussed the previous research methods, technologies, datasets and models used in Bengal sign language gestures that are interconnected in terms of achieving a successful result. Therefore, this review article tried to reveal the independent techniques which are used to overcome the challenges in research.

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Hand Gesture, Recognition, Bengali, Sign Language, Review On

Citation

D. Perera, B. Kanchana, R. Peiris, K. Madushan and D. Kasthurirathna, "Review On Hand Gesture Recognition for Bengali Sign Language," 2022 2nd International Conference on Advanced Research in Computing (ICARC), 2022, pp. 194-199, doi: 10.1109/ICARC54489.2022.9753791.

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