Performance analysis of frequency domain based feature extraction techniques for facial expression recognition

Neha Janu, Pratistha Mathur, S. Gupta, S. Agrwal
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引用次数: 7

Abstract

Facial Expression Recognition is a vital topic for research in current scenario which has many applications as machine based HR interviews and human-machine interaction. Facial Expression recognition is applied for identification of person using face of a person. Researchers have proposed many research techniques for facial expression recognition but still accuracy, illumination and occlusion are the research issues which have to improve. Key Research issue of facial expression is improving the accuracy of system which is measured in term of recognition rate. Feature extraction is the main stage on which accuracy depends for facial expression recognition. In this paper we have analyzed different feature extraction technique in frequency domain as Discrete Wavelet Transform, Discrete Cosine Transform feature extraction technique, Gabor filter and different feature reduction technique developed so far and future aspects.
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基于频域特征提取技术的面部表情识别性能分析
面部表情识别是当前场景下的一个重要研究课题,在基于机器的人力资源面试和人机交互等领域有着广泛的应用。面部表情识别是一种利用人脸识别人的方法。研究人员提出了许多面部表情识别的研究方法,但准确性、光照和遮挡等仍是有待提高的研究问题。面部表情的研究重点是提高系统的准确率,以识别率为衡量标准。特征提取是人脸表情识别的主要环节,其准确性取决于特征提取的准确性。本文分析了频域上不同的特征提取技术,如离散小波变换、离散余弦变换特征提取技术、Gabor滤波器和目前发展起来的各种特征约简技术以及未来的发展方向。
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