基于特征向量分布特征和欧氏距离决策技术的人脸表情识别
Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique
摘要：
本文提出了一种基于特征向量的人脸表情识别系统。该方法首先采集图像，并对图像中的五个重要部分进行裁剪，提取并存储表情的特征向量。同时计算测试图像的特征向量，最后通过计算测试图像与不同表情之间的最小欧氏距离来获得相似度，从而实现对输入人脸图像的识别。
英文摘要：
In this paper, an Eigenvector based system has been presented to recognize facial expressions from digital facial images. In the approach, firstly the images were acquired and cropping of five significant portions from the image was performed to extract and store the Eigenvectors specific to the expressions. The Eigenvectors for the test images were also computed, and finally the input facial image was recognized when similarity was obtained by calculating the minimum Euclidean distance between the test image and the different expressions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
