IJCATR Volume 11 Issue 12

Presentation Slide Control Based on Hand Gestures

Nelson Sinaga, Baharuddin, Hesti Fibriasari, Bakti Dwi Waluyo, Joni Syafrin Rambey
10.7753/IJCATR1112.1012
keywords : opencv; hand gesture recognition; presentation slides; machine learning

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In today's digital world, presentation using a slideshow is an effective and attractive way that helps speakers to convey information and convince the audience. There are ways to control slides with devices like a mouse, keyboard, or laser pointer. The drawback is that one should have previous knowledge about the devices to manage them. Gesture recognition acquired importance a couple of years prior and is utilized to control applications like media players, robot control, and gaming. The hand gesture recognition system is built with gloves and markers. However, using such gloves or tags expands the expense of the system. An Artificial intelligence-based hand gesture detection methodology is proposed in this proposed system. By hand gestures, users can change the presentation slides in forward and backward directions. The use of hand gestures causes the connection simple and helpful and does not need any additional gadgets. The suggested method is to help speakers with a product presentation with naturally improved communication with the computer. Specifically, the proposed system is more viable than a laser pointer since the hand is more apparent and thus can better grab the audience's attention.
@artical{n11122022ijcatr11121012,
Title = "Presentation Slide Control Based on Hand Gestures ",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "11",
Issue ="12",
Pages ="464 - 469",
Year = "2022",
Authors ="Nelson Sinaga, Baharuddin, Hesti Fibriasari, Bakti Dwi Waluyo, Joni Syafrin Rambey"}
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