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Sign Language Recognition Systems: A Decade Systematic Literature Review

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Abstract

Despite the importance of sign language recognition systems, there is a lack of a Systematic Literature Review and a classification scheme for it. This is the first identifiable academic literature review of sign language recognition systems. It provides an academic database of literature between the duration of 2007–2017 and proposes a classification scheme to classify the research articles. Three hundred and ninety six research articles were identified and reviewed for their direct relevance to sign language recognition systems. One hundred and seventeen research articles were subsequently selected, reviewed and classified. Each of 117 selected papers was categorized on the basis of twenty five sign languages and were further compared on the basis of six dimensions (data acquisition techniques, static/dynamic signs, signing mode, single/double handed signs, classification technique and recognition rate). The Systematic Literature Review and classification process was verified independently. Literature findings of this paper indicate that the major research on sign language recognition has been performed on static, isolated and single handed signs using camera. Overall, it will be hoped that the study may provide readers and researchers a roadmap to guide future research and facilitate knowledge accumulation and creation into the field of sign language recognition.

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  1. Computer Science and Engineering Department, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Ankita Wadhawan & Parteek Kumar

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  1. Ankita Wadhawan
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Wadhawan, A., Kumar, P. Sign Language Recognition Systems: A Decade Systematic Literature Review. Arch Computat Methods Eng 28, 785–813 (2021). https://doi.org/10.1007/s11831-019-09384-2

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