面向人机交互的人脸识别与跟踪设计

2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2017-11-01 DOI:10.1109/ICITISEE.2017.8285519

W. S. M. Sanjaya, D. Anggraeni, Kiki Zakaria, Atip Juwardi, M. Munawwaroh

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引用次数: 15

摘要

本文讨论了能够识别和跟踪人脸的社交机器人SyPEHUL(物理、电子、类人机器人和机器学习系统)的开发。人脸识别和跟踪过程采用级联分类和LBPH(局部二值模式直方图)人脸识别方法，基于OpenCV库和Python 2.7。基于Arduino微控制器的社交机器人硬件包含12个自由度电机伺服器，用于驱动机器人头部和面部。在社交机器人上实现了人脸识别系统，该系统可以识别和跟踪人脸，然后提到人名。结果表明，社交机器人人脸识别系统对人机交互具有较好的准确性。

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The design of face recognition and tracking for human-robot interaction

This paper discusses the development of Social Robot named SyPEHUL (System of Physic, Electronic, Humanoid Robot and Machine Learning) which can recognize and tracking human face. Face recognition and tracking process use Cascade Classification and LBPH (Local Binary Pattern Histogram) Face Recognizer method based on OpenCV library and Python 2.7. The social robot hardware based on Arduino microcontroller contains by 12 DoF (Degree of Freedom) motor servos to actuate robotic head and its face. The face recognition system has been implemented to Social Robot which can recognize and tracking human face and then mentioned the person name. The face recognition system of Social Robot result shows a good accuracy for Human-Robot Interaction.

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2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

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