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arXiv · 2012.13188

Control of Computer Pointer Using Hand Gesture Recognition in Motion Pictures

Yalda Foroutan·Ahmad Kalhor·Saeid Mohammadi Nejati·Samad Sheikhaei
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Abstract

This paper presents a user interface designed to enable computer cursor control through hand detection and gesture classification. A comprehensive hand dataset comprising 6720 image samples was collected, encompassing four distinct classes: fist, palm, pointing to the left, and pointing to the right. The images were captured from 15 individuals in various settings, including simple backgrounds with different perspectives and lighting conditions. A convolutional neural network (CNN) was trained on this dataset to accurately predict labels for each captured image and measure their similarity. The system incorporates defined commands for cursor movement, left-click, and right-click actions. Experimental results indicate that the proposed algorithm achieves a remarkable accuracy of 91.88% and demonstrates its potential applicability across diverse backgrounds.

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Yalda Foroutan, Ahmad Kalhor, Saeid Mohammadi Nejati, Samad Sheikhaei. 2020-12-24. Control of Computer Pointer Using Hand Gesture Recognition in Motion Pictures. https://arxiv.org/abs/2012.13188

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