Authors: Shujjat Khan; Donald G. Bailey; Gourab Sen Gupta
Addresses: School of Engineering and Advanced Technology (SEAT), Massey University, Palmerston North, New Zealand ' School of Engineering and Advanced Technology (SEAT), Massey University, Palmerston North, New Zealand ' School of Engineering and Advanced Technology (SEAT), Massey University, Palmerston North, New Zealand
Abstract: Sign language segmentation breaks a continuous sentence into its basic lexical units by detecting word boundaries. For robust recognition, the majority of direct segmentation approaches exploit these inter-sign pauses in a stream of hand gestures to demarcate word boundaries. Recent attempts to segment a continuous discourse exploit the constancy or directional variations of sign parameters (mainly spatial parameters). The delayed absolute difference (DAD) signature of hand positions provides means for analysing the segmentation features like pauses, repetitions and directional variations in a unique tool. In this paper, a DAD-based pause detection algorithm has been described. The performance of this deterministic algorithm is compared with three segmentation approaches. All the experiments and comparisons are done using the subjective annotation by 15 native New Zealand Sign Language (NZSL) signers. The proposed algorithm correctly and consistently detected the various lengths of pauses as compared to the existing segmentation approaches.
Keywords: pause detection; continuous sign language; sign language segmentation; word localisation; word recognition; delayed absolute difference; DAD signature; hand positions; hand gestures; pause lengths; pauses.
International Journal of Computer Applications in Technology, 2014 Vol.50 No.1/2, pp.75 - 83
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 25 Jul 2014 *