A Proposed Method of Gesture-controlled presentation software design

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Abstract

This paper introduces an innovative method for developing a presentation application that empowers users to seamlessly control slide transitions and other essential actions through intuitive hand gestures. The approach integrates sophisticated computer vision algorithms capable of real-time gesture detection and interpretation from a standard webcam feed. Furthermore, machine learning techniques personalize the system to individual users' unique gestures, enhancing usability and accuracy. The proposed method is a groundbreaking innovation that seamlessly integrates with existing presentation tools. Furthermore, the research delves into cross-device synchronization, enabling a cohesive presentation experience. To ensure optimal usability and performance, we follow established software engineering principles, resulting in a user-friendly interface and an efficiently structured codebase. This paper comprehensively guides the design, implementation, and potential of this gesture-controlled presentation software.

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APA

Hussien, N. M., Mohialden, Y. M., & Jbara, W. A. (2024). A Proposed Method of Gesture-controlled presentation software design. Babylonian Journal of Machine Learning, 2024, 56–62. https://doi.org/10.58496/BJML/2024/005

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