个性化无人机交互:带有面部验证功能的自适应手势控制

Idris Seidu, Jafaar Olasunkanmi Lawal
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引用次数: 0

摘要

本文介绍了一种新型的个性化无人机交互系统,该系统集成了自适应手势控制和面部认证功能。该系统利用配备 500 万像素摄像头的大疆 Tello 无人机,采用先进的计算机视觉和机器学习技术,确保安全、直观的控制。使用直方图梯度(HOG)方法和 FaceNet 模型进行的面部识别可验证用户身份,而 MediaPipe 和定制的卷积神经网络(CNN)可促进准确的手势识别。系统的实时处理能力确保了无缝和灵敏的用户交互。实验结果表明了该系统在各种场景下的稳健性和准确性,凸显了其在安全、娱乐和个人辅助等不同应用领域的潜力。
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Personalized Drone Interaction : Adaptive Hand Gesture Control with Facial Authentication
This paper presents a novel system for personalized drone interaction, integrating adaptive hand gesture control with facial authentication. Utilizing the DJI Tello drone equipped with a 5 MP camera, the system employs advanced computer vision and machine learning techniques to ensure secure and intuitive control. Facial recognition using the Histogram of Oriented Gradients (HOG) method and FaceNet model verifies user identity, while MediaPipe and a custom convolutional neural network (CNN) facilitate accurate hand gesture recognition. The system’s real-time processing capabilities ensure seamless and responsive user interaction. Experimental results demonstrate the system’s robustness and accuracy in various scenarios, highlighting its potential for diverse applications such as security, entertainment, and personal assistance.
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