A survey on manual and non-manual sign language recognition for isolated and continuous sign Online publication date: Sat, 10-Sep-2016
by Subhash Chand Agrawal; Anand Singh Jalal; Rajesh Kumar Tripathi
International Journal of Applied Pattern Recognition (IJAPR), Vol. 3, No. 2, 2016
Abstract: Sign language recognition is an important area of human computer interaction (HCI). The last decade witnessed a good number of publications in this field. Furthermore, several surveys can be found in the literature but none of them addresses an overall review in this field. In this paper, we have specifically highlighted the Indian sign language (ISL). The works under the complex and moving background, integration of non-manual signals, large vocabulary and signer independent have got a very little attention in the past. In this paper, we have discussed hand segmentation and tracking, feature extraction and classification methods exist in the literature. Within these methods, we examine the various issues such as signer dependence/independence, manual/non-manual, glove/device-based, vocabulary size, constraints in hand segmentation, and isolated/continuous sign. The purpose of this paper is to provide a complete progress in the field of SLR, specifically in ISL.
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