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Real time facial expression recognition app development on mobile phones

机译:手机实时面部表情识别应用开发

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摘要

Facial expression has made significant progress in recent years with many commercial systems are available for real-world applications. It gains strong interest to implement a facial expression system on a portable device such as tablet and smart phone device using the camera already integrated in the devices. It is very common to see face recognition phone unlocking app in new smart phones which are proven to be hassle free way to unlock a phone. Implementation a facial expression system in a smart phone would provide fun applications that can be used to measure the mood of the user in their daily life or as a tool for their daily monitoring of the motion in phycology studies. However, traditional facial expression algorithms are normally computing extensive and can only be implemented offline at a computer. In this paper, a novel automatic system has been proposed to recognize emotions from face images on a smart phone in real-time. In our system, the camera of the smart phone is used to capture the face image, BRIEF features are extracted and k-nearest neighbor algorithm is implemented for the classification. The experimental results demonstrate that the proposed facial expression recognition on mobile phone is successful and it gives up to 89.5% recognition accuracy.
机译:近年来,随着许多可用于实际应用的商业系统,面部表情取得了重大进展。使用已经集成在设备中的相机在诸如平板电脑和智能电话设备之类的便携式设备上实现面部表情系统引起了人们极大的兴趣。在新的智能手机中看到人脸识别手机解锁应用程序是很常见的,事实证明这是解锁手机的简便方法。在智能手机中实施面部表情系统将提供有趣的应用程序,这些应用程序可用于测量用户日常生活中的情绪,或者用作其在生理学研究中日常监测运动的工具。但是,传统的面部表情算法通常计算量很大,并且只能在计算机上离线实现。在本文中,提出了一种新颖的自动系统,该系统可以从智能手机上的面部图像实时识别情绪。在我们的系统中,使用智能手机的摄像头捕获面部图像,提取简短特征,并实现k最近邻算法进行分类。实验结果表明,所提出的手机表情识别方法是成功的,识别率高达89.5%。

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