Title: Real time vision-based hand gesture recognition using depth sensor and a stochastic context free grammar

Authors: Jayesh Gangrade; Jyoti Bharti

Addresses: Maulana Azad National Institute of Technology, Bhopal, 462003, India; IES IPS Academy, Indore, 452012, India ' Maulana Azad National Institute of Technology, Bhopal, 462003, India

Abstract: This paper presents a new algorithm in computer vision for the recognition of hand gestures. In the proposed system, Kinect sensor is used to track and segment hand in the clutter background and feature extracted by finger and an angle between them. Classify the hand posture using multi-class support vector machine. The hand gesture is recognised by stochastic context free grammar (SCFG). Stochastic context free grammar uses syntactic structure analysis and by this method, recognises hand gestures by set of production rules which consists of a combination of hand postures. The proposed algorithm is able to recognise various hand postures in real time with more than 97% accuracy.

Keywords: hand gesture; stochastic context free grammar; SCFG; multi-class support vector machine; Kinect sensor.

DOI: 10.1504/IJCVR.2019.099438

International Journal of Computational Vision and Robotics, 2019 Vol.9 No.3, pp.260 - 271

Received: 20 Sep 2017
Accepted: 03 May 2018
Published online: 02 May 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article