Back close

A Stroke Based Representation of Indian Sign Language Signs Incorporating Global and Local Motion Information

Publication Type : Conference Paper

Publisher : Second International Conference on Advanced Computing, Networking and Security

Source : Second International Conference on Advanced Computing, Networking and Security, 2013.

Url : http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6714139(link is external)

Keywords : Dynamic Signs, Global motion, Indian sign language, Key Frames, Key Maximum Curvature points(KMCPs), Local motion, Stroke sequence

Campus : Amritapuri

School : School of Engineering

Center : Center for Computational Engineering and Networking

Department : Computer Science

Verified : Yes

Year : 2013

Abstract : Sign Language is a visual gesture language used by speech impaired people to convey their thoughts and ideas with the help of hand gestures and facial expressions. This paper presents a stroke based representation of dynamic gestures of Indian Sign Language Signs incorporating both local as well as global motion information. This compact representation of a gesture is analogous to phonemic representation of speech signals. To incorporate the local motion of the hand, each stroke contains the features corresponding to the hand shape as well. The dynamic gesture trajectories are segmented based on Maximum Curvature Points(MCPs). MCPs are selected based on the direction change of trajectories. The frames corresponding to the MCP points of the trajectory are considered as the key frames. Local information features are taken as the hand shape of the Key frames. The existing methods of Sign Language Recognition has scalability problems apart from high complexity and the need for extensive training data. In contrast, our proposed method of stroke based representation has less expensive training phase since it only requires the training of stroke features and stroke sequences of each word. Our algorithms also address the issue of scalability. We have tested our approach in the context of Indian Sign Language recognition and we present the results from this study

Cite this Research Publication :
M. Geetha, Aswathi, P. V., and Dr. Kaimal, M. R., “A Stroke Based Representation of Indian Sign Language Signs Incorporating Global and Local Motion Information”, in Second International Conference on Advanced Computing, Networking and Security, 2013.

Admissions Apply Now