Abstract
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.
Highlights
Hand gestures are an aspect of body language that can be conveyed through the center of the palm, the finger position and the shape constructed by the hand
[9], et al [19] provided a specific survey on hand gesture recognition for mouse control applications, who developed a computer vision system based marked gloves
[56], in which motion patterns were detected hand gesture recognition system based on time of flight (TOF) was offered in [56], in which motion patterns were based on hand received as input depth motion patterns were compared detected basedgestures on hand gestures received as images
Summary
Hand gestures are an aspect of body language that can be conveyed through the center of the palm, the finger position and the shape constructed by the hand. Camastra [9], et al [19] provided a specific survey on hand gesture recognition for mouse control applications, who developed a computer vision system based marked gloves This studythey did including methodologies and algorithms used on for colored human–machine interaction. Kaur et al [16] reviewed hand gestures that can be used under a wide range of applications like clinical operations [10], sign language [11], robot control [12], virtual environments [13], home automation [14], personal computer and tablet [15], gaming [16] These techniques essentially involve replacement of the instrumented glove with a camera.
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