首页> 外文OA文献 >FMX (EEPIS FACIAL EXPRESSION MECHANISM EXPERIMENT): PENGENALAN EKSPRESI WAJAH MENGGUNAKAN NEURAL NETWORK BACKPROPAGATION
【2h】

FMX (EEPIS FACIAL EXPRESSION MECHANISM EXPERIMENT): PENGENALAN EKSPRESI WAJAH MENGGUNAKAN NEURAL NETWORK BACKPROPAGATION

机译:FmX(EEpIs面部表情机制实验):利用神经网络反向传播引入面部表情

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

udIn the near future, it is expected that the robot can interact with humans. Communication itself has many varieties. Not only from word to word, but body language also be the medium. One of them is using facial expressions. Facial expression in human communication is always used to show human emotions. Whether it is happy, sad, angry, shocked, disappointed, or even relaxed? This final project focused on how to make robots that only consist of head, so it could make a variety facial expression like human beings. This Face Humanoid Robot divided into several subsystems. There are image processing subsystem, hardware subsystem and subsystem of controllers. In image processing subsystem, webcam is used for image data acquisition processed by a computer. This process needs Microsoft Visual C compiler for programming that has been installed with the functions of the Open Source Computer Vision Library (OpenCV). Image processing subsystem is used for recognizing human facial expressions. With image processing, it can be seen the pattern of an object. Backpropagation Neural Network is useful to recognize the object pattern. Subsystem hardware is a Humanoid Robot Face. Subsystem controller is a single microcontroller ATMega128 and a camera that can capture images at a distance of 50 to 120 cm. The process of running the robot is as follows. Images captured by a camera webcam. From the images that have been processed with image processing by a computer, human facial expression is obtained. Data results are sent to the subsystem controller via serial communications. Microcontroller subsystem hardware then ordered to make that facial expression. Result of this final project is all of the subsystems can be integrated to make the robot that can respond the form of human expression. The method used is simple but looks quite capable of recognizing human facial expression. Keyword: OpenCV, Neural Network BackPropagation, Humanoid Robot
机译:ud在不久的将来,机器人有望与人类互动。通讯本身有很多种类。不仅单词之间,而且肢体语言也成为媒介。其中之一是使用面部表情。人类交流中的面部表情始终被用来表达人类的情感。是快乐,悲伤,愤怒,震惊,失望还是放松?这个最后的项目着重于如何制造仅由头部组成的机器人,因此它可以像人类一样做出各种各样的面部表情。这款Face Humanoid机器人分为几个子系统。有图像处理子系统,硬件子系统和控制器子系统。在图像处理子系统中,网络摄像头用于由计算机处理的图像数据获取。此过程需要Microsoft Visual C编译器进行编程,该编译器已与开源计算机视觉库(OpenCV)的功能一起安装。图像处理子系统用于识别人的面部表情。通过图像处理,可以看到物体的图案。反向传播神经网络可用于识别对象模式。子系统硬件是类人机器人面孔。子系统控制器是单个微控制器ATMega128和摄像机,可以在50到120 cm的距离处捕获图像。运行机器人的过程如下。摄像头网络摄像头捕获的图像。从已经用计算机进行图像处理的图像中,获得人脸表情。数据结果通过串行通信发送到子系统控制器。然后,微控制器子系统硬件下令做出该面部表情。这个最终项目的结果是可以集成所有子系统,以使机器人可以响应人类表达的形式。所使用的方法很简单,但看起来很能够识别人脸表情。关键字:OpenCV,神经网络反向传播,人形机器人

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号