Title: Fusing pyramid histogram of gradients and optical flow for hand gesture recognition

Authors: S.S. Suni; K. Gopakumar

Addresses: Department of Electronics and Communication, LBS Centre for Science and Technology, Thiruvananthapuram, Kerala, India ' Department of Electronics and Communication, TKM College of Engineering, Kollam, Kerala, India

Abstract: Human computer interaction systems based on hand gestures catch the eye of the research community for implementing natural communication between man and machines. However, different persons perform the same gestures differently in terms of velocity and motion scale. This poses a challenging issue in minimising the variations between different persons and maximises the coherence of the same gestures. In this paper, the original pyramid histogram of gradients in three orthogonal planes combining with the dense optical flow to create dynamic descriptor is explored in to discriminate features for recognition of hand gestures. The shape and motion features of images in a video sequence are captured to obtain the geometric and illumination invariant spatio-temporal feature descriptor for classification. A multiclass support vector machine classifier is used to recognise the hand gestures. The proposed method gives an excellent recognition rate and excels the existing approaches.

Keywords: human computer interaction; HCI; pyramid histogram of gradients; PHOG; optical flow; hand gesture recognition; multi-class support vector machine.

DOI: 10.1504/IJCVR.2020.109396

International Journal of Computational Vision and Robotics, 2020 Vol.10 No.5, pp.449 - 464

Accepted: 15 Jul 2019
Published online: 08 Sep 2020 *

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