论文标题
真实：使用欧几里得空间和可能性估计的实时面部检测和识别
REaL: Real-time Face Detection and Recognition Using Euclidean Space and Likelihood Estimation
论文作者
论文摘要
准确地检测和识别面孔一直是一个挑战。区分面部特征，训练图像和产生快速结果需要大量计算。我们在本文中提出的实际系统讨论了其功能以及在短时间内进行计算的方式。实际实验是在实时图像上进行的，并且识别率很有希望。该系统还成功地从其计算中删除了非人类对象。该系统使用本地数据库存储捕获的图像，并经常馈送神经网络。捕获的图像会自动裁剪以消除不必要的噪音。系统计算欧拉角度，以及面部是否微笑，左眼和右眼张开的概率。
Detecting and recognizing faces accurately has always been a challenge. Differentiating facial features, training images, and producing quick results require a lot of computation. The REaL system we have proposed in this paper discusses its functioning and ways in which computations can be carried out in a short period. REaL experiments are carried out on live images and the recognition rates are promising. The system is also successful in removing non-human objects from its calculations. The system uses a local database to store captured images and feeds the neural network frequently. The captured images are cropped automatically to remove unwanted noise. The system calculates the Euler angles and the probability of whether the face is smiling, has its left eye, and right eyes open or not.
