Real-time emotion recognition from facial images using Raspberry Pi II
Real-time emotion recognition from facial images using Raspberry Pi II
复制标题
使用 Raspberry Pi II 从面部图像进行实时情绪识别
作者：
Suchitra;Suja P;Shikha Tripathi
在当今的技术中，人机交互的需求越来越大，机器需要理解人类的手势和情感。如果机器能够识别人类的情感，它就可以更好地理解人类的行为，从而提高任务效率。情感可以通过文字、声音、口头和面部表情来理解。面部表情在判断一个人的情绪方面起着很大的作用。研究发现，利用人脸图像进行实时情感识别的研究工作十分有限。提出了一种从人脸图像中进行实时情感识别的方法。在该方法中，我们使用Haar级联的三步人脸检测，主动形状模型(ASM)的特征提取，(提取26个人脸点)和Adboost分类器对愤怒、厌恶、快乐、中性和惊讶五种情绪进行分类。该方法的创新之处在于在Raspberry PI II上实现了实时情感识别，平均正确率达到94%。当Raspberry PI II安装在移动机器人上时，可以在情感识别起主要作用的社交/服务环境中实时动态识别情感。
In present day technology human-machine interaction is growing in demand and machine needs to understand human gestures and emotions. If a machine can identify human emotions, it can understand human behavior better, thus improving the task efficiency. Emotions can understand by text, vocal, verbal and facial expressions. Facial expressions play big role in judging emotions of a person. It is found that limited work is done in field of real time emotion recognition using facial images. In this paper, we propose a method for real time emotion recognition from facial image. In the proposed method we use three steps face detection using Haar cascade, features extraction using Active shape Model(ASM), (26 facial points extracted) and Adaboost classifier for classification of five emotions anger, disgust, happiness, neutral and surprise. The novelty of our proposed method lies in the implementation of emotion recognition at real time on Raspberry Pi II and an average accuracy of 94% is achieved at real time. The Raspberry Pi II when mounted on a mobile robot can recognize emotions dynamically in real time under social/service environments where emotion recognition plays a major role.