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首页> 外文会议>IEEE International Conference on Control, Measurement and Instrumentation >Emotion Recognition from Facial Image Analysis Using Composite Similarity Measure Aided Bidimensional Empirical Mode Decomposition
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Emotion Recognition from Facial Image Analysis Using Composite Similarity Measure Aided Bidimensional Empirical Mode Decomposition

机译：使用复合相似性的面部图像分析情感识别测量辅助竞争经验模式分解

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摘要

The aim of this work is to automatically detect and analyse the emotions from the digital videos and images. Initially the images are extracted from pre-recorded videos, from which the faces are cropped automatically. The training dataset is formed with minimal number of images per subject for each emotion. Bi-dimensional Empirical Mode Decomposition (BEMD) is used to decompose the images in its Intrinsic Mode Functions (IMF). Composite Similarity Measure (CSM) based classification has been employed to detect the correct emotion from the images. "ENTERFACE'05 Audio-Visual Emotion Database", "JAFFE Database" and a database developed in laboratory called "DCAB database" are used to test the performance of the proposed method. The advantage of this method is to be able to classify or rank the emotions found in an image or a video even when the image or video is subjected to feature occlusion such as the subject putting on spectacles or sunglasses. Moreover, it is robust to illumination, different view point and background colour of the image or video. The performance is also invariant to the dress, hair style, facial hair or moustache of the subject. This method is also able to overcome the problem related to ageing to some extent.
机译：这项工作的目的是自动检测和分析数字视频和图像的情绪。最初从预先记录的视频中提取图像，从该视频中自动裁剪。训练数据集是针对每种情绪的每个受试者的最少数量的图像形成。双维经验模式分解（BEMD）用于将图像分解在其内部模式功能（IMF）中。基于复合相似度测量（CSM）的分类已被用于检测图像中的正确情感。 “Enterface'05视听情感数据库”，“jaffe数据库”和在实验室中开发的数据库用于测试所提出的方法的性能。这种方法的优点是能够在图像或视频经受特征遮挡时诸如俯视眼镜或太阳镜的主体的特征遮挡来对图像或视频中发现的情绪进行分类或排列。此外，它是对照明，图像或视频的不同视点和背景颜色的鲁棒。性能也不导致衣服，发型，面部头发或留言的主题。这种方法还能够在一定程度上克服与老化相关的问题。

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