Abstract
As human–computer interaction continues to evolve, gesture-based applications are becoming more and more popular. Traditionally, computer interfaces were limited only to keyboard and mouse functions where the input depended on the click of the button. With the advancement in technology, vision-based human–computer interaction provides a more extensive range of taking input by using computer vision in order to process data from multiple cameras. Computer Vision alludes to a field of study that tries to create systems that allow computers “to see” and comprehend the content of digital images such as photographs and videos. The gesture-based interaction interface being proposed in this paper can have several applications, although the main focus is on the gaming aspect. This interface consists of the detection, tracking, and recognition module. This paper explores the use of Computer Vision to create a gesture-based game, controlled by hand using the Haar Cascade classifier to classify and detect the object. With the help of simple hand gestures, the model has been trained to enable users to play the game of “Flying Wing Mario”. In this proof-of-concept game, the users are able to play the game through gesture recognition as it provides them with an enhanced interactive experience integrating the virtual and the real-world object. The concept, however, can be applied to any other game as well.
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Singhvi, S., Gupta, N., Satapathy, S.M. (2022). Virtual Gaming Using Gesture Recognition Model. In: Sahoo, J.P., Tripathy, A.K., Mohanty, M., Li, KC., Nayak, A.K. (eds) Advances in Distributed Computing and Machine Learning. Lecture Notes in Networks and Systems, vol 302. Springer, Singapore. https://doi.org/10.1007/978-981-16-4807-6_12
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