Title: A survey on manual and non-manual sign language recognition for isolated and continuous sign

Authors: Subhash Chand Agrawal; Anand Singh Jalal; Rajesh Kumar Tripathi

Addresses: GLA University, Mathura-281406, India ' GLA University, Mathura-281406, India ' GLA University, Mathura-281406, India

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.

Keywords: hand segmentation; feature extraction; classification; hand gestures; hand tracking; isolated signs; continuous signs; dataset; evaluation measures; manual signals; non-manual signals; sign language recognition; human-computer interaction; HCI; Indian sign language; vocabulary size.

DOI: 10.1504/IJAPR.2016.079048

International Journal of Applied Pattern Recognition, 2016 Vol.3 No.2, pp.99 - 134

Received: 11 Jan 2016
Accepted: 21 Feb 2016
Published online: 10 Sep 2016 *

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