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Fuzzy Emotion Recognition Model For Video Sequences

机译:用于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,图像分析和主体性的限制,来自视频剪辑的自动面部表情识别是一个具有挑战性的任务。 本文倡导基于模糊的情感分类方法。 另一方面,已经提出了几个提案,以在分类之前提升预处理阶段。 这包括用于皮肤检测,自适应阈值,主成分分析和凸轮转移的适应阈值,主成分分析和面部跟踪的使用的组合。 已经使用TFEID和视频剪辑进行了评估了开发系统的性能,并与贝叶斯分类器相比。

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