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Review

Hand Gesture Recognition Based on Computer Vision: A Review of Techniques

1
Electrical Engineering Technical College, Middle Technical University, Baghdad 10022, Iraq
2
School of Engineering, University of South Australia, Mawson Lakes SA 5095, Australia
*
Author to whom correspondence should be addressed.
Received: 23 May 2020 / Revised: 15 July 2020 / Accepted: 21 July 2020 / Published: 23 July 2020
Hand gestures are a form of nonverbal communication that can be used in several fields such as communication between deaf-mute people, robot control, human–computer interaction (HCI), home automation and medical applications. Research papers based on hand gestures have adopted many different techniques, including those based on instrumented sensor technology and computer vision. In other words, the hand sign can be classified under many headings, such as posture and gesture, as well as dynamic and static, or a hybrid of the two. This paper focuses on a review of the literature on hand gesture techniques and introduces their merits and limitations under different circumstances. In addition, it tabulates the performance of these methods, focusing on computer vision techniques that deal with the similarity and difference points, technique of hand segmentation used, classification algorithms and drawbacks, number and types of gestures, dataset used, detection range (distance) and type of camera used. This paper is a thorough general overview of hand gesture methods with a brief discussion of some possible applications. View Full-Text
Keywords: hand gesture; hand posture; computer vision; human–computer interaction (HCI) hand gesture; hand posture; computer vision; human–computer interaction (HCI)
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MDPI and ACS Style

Oudah, M.; Al-Naji, A.; Chahl, J. Hand Gesture Recognition Based on Computer Vision: A Review of Techniques. J. Imaging 2020, 6, 73. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6080073

AMA Style

Oudah M, Al-Naji A, Chahl J. Hand Gesture Recognition Based on Computer Vision: A Review of Techniques. Journal of Imaging. 2020; 6(8):73. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6080073

Chicago/Turabian Style

Oudah, Munir; Al-Naji, Ali; Chahl, Javaan. 2020. "Hand Gesture Recognition Based on Computer Vision: A Review of Techniques" J. Imaging 6, no. 8: 73. https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6080073

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