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@article{174316,
        author = {Akkireddy Pavan Kumar and Gudiwaka Vijaya Lakshmi and Tumula Dileep and Karapati Karthik and Duli Prakash},
        title = {Gesture Master: Real-time Hand Gesture Control for interactive presentation using computer vision},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3475-3480},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174316},
        abstract = {This paper presents a Hand Gesture-Based Presentation Control System that uses computer vision and speech recognition to enable users to control PowerPoint presentations using hand gestures and voice commands. The system utilizes the cvzone library and OpenCV to recognize hand gestures, enabling users to move slides forward and backward, manipulate a virtual pointer, create annotations with a specific color, delete content, and even zoom in or out with simple hand gestures. Furthermore, an enhanced speech recognition module based on the Speech Recognition and PyAudio libraries allows users to jump directly to a particular slide using voice commands. The system to be proposed increases presentation delivery accessibility and efficiency, as it eradicates the use of conventional input devices such as keyboards, mouse, or clickers. The system works with a webcam to record hand gestures in real-time, and this provides smooth and interactive presentation delivery. A threshold-based method is employed to differentiate gesture inputs, with the aim of providing accuracy and promptness. Implementation is made light-weight such that it can run with typical hardware configurations, and thus it can be implemented in diverse professional, academic, and business environments. Different light conditions and usage patterns are tested for the system to ensure its reliability and ruggedness. The outcome shows the efficacy of presentation control through hand gesture recognition opening up future possibilities such as the incorporation of machine learning-based gesture classification and personalized gesture mapping. This study adds to the emerging field of Human-Computer Interaction (HCI) and seeks to redefine the conduct of presentations with a more natural and interactive approach.},
        keywords = {Computer Vision, Hand Gesture Recognition, Human-Computer Interaction, OpenCV, Presentation control, Speech Recognition.},
        month = {March},
        }