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python+opencv+dlib实现人脸检测与表情识别
一,dlib简单介绍:Dlib包含广泛的机器学习算法。所有的设计都是高度模块化的,快速执行,并且通过一个干净而现代的C ++
API,使用起来非常简单。它用于各种应用,包括机器人技术,嵌入式设备,手机和大型高性能计算环境。
二,识别规则:
1、嘴巴张开距离占面部识别框宽度的比例越大,说明情绪越激动,可能是非常开心,也可能是非常惊讶。
2、眉毛上扬,17-21 或者 22-26
号特征点距离面部识别框顶部与识别框高度的比值越小,说明眉毛上扬越厉害,可表示惊讶、开心。眉毛的倾斜角度,开心时眉毛一般是上扬,愤怒时皱眉,同时眉毛下压的比较厉害。
3、眯眼睛,人在开怀大笑的时候会不自觉的眯起眼睛,愤怒或者惊讶的时候会瞪大眼睛。
系统缺点:不能捕捉细微表情的变化,只能大致的判断出人的情绪,开心、愤怒、惊讶、自然。
系统优点:结构简单,易于上手。
应用领域:微笑抓拍,捕捉瞬间的美好、缓解儿童自闭症、交互式游戏开发。由于人感情的复杂性,这些表情确实不能完完全全的代表一个人内心深处的情绪波动,如要提高判断的准确性,则需要心率检测、语音处理等综合评价。
三、实施思路
四,效果图