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Fuzzy emotion recognition model for video sequences

机译:视频序列的模糊情感识别模型

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摘要

Automatic facial expression recognition from video clips is a challenging task due to computational complexity, limitations of image analysis and subjectivity. This paper advocates a fuzzy based approach for emotion classification. On the other hand, several proposals have been put forward to enhance the pre-processing stage prior to the classification. This includes a combination of a boundary elliptical model for skin detection, adaptive thresholding, principal component analysis and use of cam-shift for face tracking. The performances of the developed system have been evaluated using TFEID and video clips and compared with Bayes' classifier.
机译:由于计算复杂性,图像分析的局限性和主观性,从视频剪辑中自动识别面部表情是一项具有挑战性的任务。本文提出了一种基于模糊的情感分类方法。另一方面,已经提出了一些建议以增强分类之前的预处理阶段。这包括用于皮肤检测的边界椭圆模型,自适应阈值,主成分分析以及使用凸轮平移进行面部跟踪的组合。已使用TFEID和视频剪辑评估了开发系统的性能,并与贝叶斯分类器进行了比较。

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