Efficient Gesture-Based Presentation Controller Using Transfer Learning Algorithm

This research work explains how to control Presentations using hand gestures. Presentations are crucial in many aspects of our human lives. Everyone employee who has ever worked in a company or been a student has participated in a demonstration at any point in their lives. PowerPoint presentations might become irritating when you have to update and manipulate the slides using the keyboard or a dedicated device. So, this project focuses mainly on the development of interactive projection technology, which makes it more interesting and interactive by detecting the user’s motion simultaneously. Our team always wanted that users should be able to operate the presentation slideshow with hand gestures. Many functions of the PowerPoint slideshow have been attempted to be managed in research using gestures. This study attempts to map minute differences in movements using some simple PowerPoint slide show control Python applications. The motions were recognized using machine learning. Gesture recognition became more vital for operating software such as robotics, and games a few years ago. The hand gesture recognition system improves when surroundings are in well-lit conditions. Hand gestures make communication simple, useful, and technologically independent. The proposed technique is to help presenters provide more effective and interactive presentations by increasing their natural contact with the computer. The recommended approach, in particular, is more practical than a laser pen since the hand is clearer and may attract the audience’s attention more effectively.