Although great progress has been made by leveraging the use of sensors in various fields like human body tracking, robust, accurate, and efficient hand gesture recognition still remains an open problem. The authors draw a comparison on how the HSV (hue, saturation, value) model used in hand gesture recognition is better than the other models. Also, the focus will be laid on the different segmentation techniques that are being used nowadays and how thresholding is an important part of it. The extraction of noisy hand contours is really challenging, and for the same reason, the authors propose the usage of convexity defects to record deviation from contours and the dilution and erosion of the binary images to recognize hand gestures like rock-paper-scissors. This model has been tried and tested on different devices with various hand gestures and yields a positive result.
TopIntroduction
The term Human-Computer Interaction(HCI) came into being in the early 1980s. It was made famous by Stuart K. Card, Allen Newell, and Thomas P. Moran in their seminal 1983 book, “The Psychology of Human-Computer Interaction”. With the development of new technologies and the studies of various researchers, Human-Computer Interaction has reached great heights. It has been in trend for the past few years and has been growing rapidly since then.
The continuous development in this area gave rise to various fields in this sector. The prominent ones include:
Figure 1. Adjusting volume using hand gestures
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Object Tracking - Object Tracking involves tracking the motion state of a particular object, such as a person, to read their anatomy, detect their location, record and analyze their activities, etc., in each frame of an image sequence or a video. Example: Monitoring the traffic of a particular area, i.e. the number of vehicles, their types, and their speed (Lee, Y. H.,et al.,2019) as shown in Fig.2.
Figure 2. Traffic monitoring system
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Natural Language User Interface(LUI or NLUI): NLUI is an interface that provides the user with the liberty to interact with the computer system using human-understandable language. Unfortunately, Natural Language is quite uncertain and is dependant on a vast amount of world knowledge. It can be combined with other ways of interaction to widen the range of interaction bandwidth. Example: Dialog System whose working is shown in Fig.3.
Figure 3. Architecture overview of dialog management system
The future of HCI is vast and promising since we have seen the world go from keyboard to mouse point-and-click, to touch, and now we’re into the world of gesture and voice recognition, which in itself is a remarkable evolution for Human-Computer Interaction. As far as HCI is concerned, hand gesture recognition plays a significant role in it and has a variety of applications. The development in the field of hand gesture recognition systems also avoided diseases such as Parkinson’s disease, trigger finger, gorilla arm, etc., which is caused by excessive use of the mouse or keyboard (Rautaray, S. S., & Agrawal, A. (2015)). The main aim of developing a hand gesture recognition system is to establish an interaction between humans and computers from the recognized gestures. Many vision-based and non-vision-based methods have been proposed in recognizing hand gestures and extracting information from them, as discussed under the section of comparative analysis.
This chapter focuses on the different approaches in hand-gesture recognition; segmentation in the HSV model; comparison on how the HSV(Hue, Saturation, Value) model is better than the other models; challenges faced during gesture recognition; and The ROCK-PAPER-SCISSORS GAME Model explanation.
TopThe recent development in the field of Artificial intelligence has given rise to various gesture recognition devices. Moreover, hand gesture recognition has received a great deal of attention because of its numerous applications in virtual reality, sign language recognition, and computer games. Through human-computer interaction, hand gesture recognition models give the user the ability to interact with the machine efficiently.