It can be utilized for many computer vision tasks, such as face detection and recognition, low bit rate video transmission, image restoration, facial expression analysis and digital zooming.
它有着广泛的应用背景，如：人脸检测与识别，低带宽的视频传输，图像恢复，人脸表情分析，数码相机的digital zooming技术等。
参考来源 - 基于学习的图像超分辨率技术·2,447,543篇论文数据，部分数据来源于NoteExpress
Robust facial expression feature extraction method is the key part of the computer aided facial expression analysis system.
面部表情特征抽取的针对性和鲁棒性在计算机辅助面部表情自动分析系统中具有举足轻重的作用。
Facial feature points localization takes an important role in the face recognition, facial expression analysis, cartoon face synthesis, etc.
人脸特征点的定位在人脸识别、人脸表情分析以及卡通人脸生成等方面具有非常重要的作用。
Given FACS's three decades of acceptance and CERT's record of accuracy, automated facial-expression analysis might well meet those criteria.
由于30年来FACS已得到承认和CERT的精确性记录，面部表情分析的自动化非常符合这些标准。
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