Two viewpoints based real‐time recognition for hand gestures. Issue 17 (4th March 2021)

• Record Type: Journal Article
• Authors: Krishan Kumar, Amit; Kaushal Kumar, Abhishek; Guo, Shuli
• Is Part Of: IET image processing. Volume 14:Issue 17(2020)
• Page Start: 4606
• Page End: 4613
• Publication Date: 2021-03-04
• Subjects: image classification -- feature extraction -- learning (artificial intelligence) -- cameras -- geometry -- gesture recognition -- decision trees; computation time -- hand gesture recognition -- single viewpoint set‐up -- image processing -- feature extraction -- three‐dimensional view -- single camera system -- geometrical features -- 3D view estimation -- classification accuracy -- recognition rate -- single‐camera system -- real‐time recognition; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.1458
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : It is extremely challenging to accomplish excellent accuracy for gesture recognition using an approach where complexity in computation time for recognition is less. This study compares accuracy in hand gesture recognition of a single viewpoint set‐up with proposed two viewpoint set‐up for different classification techniques. The efficacy of the presented approach is verified practically with various image processing, feature extraction and classification techniques. Two camera system make geometry learning and three‐dimensional (3D) view feasible compared to a single camera system. Geometrical features from additional viewpoint contribute to 3D view estimation of the hand gesture. It also improves the classification accuracy. Experimental results demonstrate that the proposed method show escalation in recognition rate compared to the single‐camera system, and also has great performance using simple classifiers like the nearest neighbour and decision tree. Classification within 1 s is considered as real‐time in this study.