论文标题
在脸上找到情绪：元分类者
Finding Emotions in Faces: A Meta-Classifier
论文作者
论文摘要
机器学习已被用来识别脸上的情绪，通常是通过寻找8种不同的情绪状态（中性，快乐，悲伤，惊喜，恐惧，厌恶，愤怒和蔑视）。我们考虑两种方法：基于面部标志的功能识别和所有像素的深度学习；每个人的总体准确性58％。但是，他们在不同的图像上产生了不同的结果，因此我们提出了一种结合这些方法的新元分类剂。它的精度为77％，可以产生更好的结果
Machine learning has been used to recognize emotions in faces, typically by looking for 8 different emotional states (neutral, happy, sad, surprise, fear, disgust, anger and contempt). We consider two approaches: feature recognition based on facial landmarks and deep learning on all pixels; each produced 58% overall accuracy. However, they produced different results on different images and thus we propose a new meta-classifier combining these approaches. It produces far better results with 77% accuracy
