Vision Based Gesture Recognition Article Swipe
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· 2024
· Open Access
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· DOI: https://doi.org/10.1016/j.procs.2024.04.031
· OA: W4399202644
The use of computers has become an integral part of our daily lives, and they are utilized in various fields. However, traditional input devices such as a mouse and keyboard can sometimes be limiting. Hand gestures can provide a more natural and efficient way of interacting with computers. However, since gestures can vary in orientation and shape from person to person, this creates a non-linear problem. Hence we propose an image-based gesture recognition method that leverages well-established models. The models were trained on a diverse dataset encompassing a wide range of gestures performed by various individuals under different environmental conditions. The experiments exhibit remarkable adaptability to different gestures resulting in a robust and accurate recognition in real-world scenarios. This research will help in creating better human-computer interaction interfaces offering users more natural and efficient ways to interact with computers. The improved gesture recognition systems elevate overall user experience and productivity.
