论文标题
在电影中使用手势识别的计算机指针控制
Control of Computer Pointer Using Hand Gesture Recognition in Motion Pictures
论文作者
论文摘要
本文介绍了一个用户界面，旨在通过手动检测和手势分类来启用计算机光标控制。收集了一个包含6720个图像样本的全面手数据集，其中包括四个不同的类：拳头，棕榈，指向左侧，并指向右侧。这些图像是在各种环境下从15个个人中捕获的，包括具有不同观点和照明条件的简单背景。在该数据集上对卷积神经网络（CNN）进行了训练，以准确预测每个捕获的图像的标签并测量其相似性。该系统结合了光标运动，左键单击和右键单击操作的定义命令。实验结果表明，所提出的算法的精度为91.88％，并证明了其在各种背景上的潜在适用性。
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.
