人脸表情识别系统中的算法主要有图像处理算法、特征提取算法和分类算法。

The algorithms of facial expression recognition system mainly contain images' preprocessing algorithms, feature extraction algorithms and classification algorithms.

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本文在研究表情识别关键算法的基础上，将重点放在特征提取方法的研究。

The key algorithms of facial expression recognition are studied in this paper and we focus our attention on the research of methods for feature extraction.

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重点按照不同的特征提取和分类器设计方法对表情识别技术进行了综述。

Then current recognition technologies are roughly introduced and classified according to different method of feature extraction and classifier design.

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表情识别系统包括人脸检测、人脸特征提取、特征选择以及表情分类等几部分。

A facial expression recognition system contains face detection, face feature extraction, feature selection and expression classification.

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本文的目的就是要寻求更适合于人脸表情识别且实现相对简单的特征提取算法来提高识别率。

The purpose of the paper is to research and improve feature extraction algorithms to improve the correct recognition rate.

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该系统大幅缩减特征提取及分类的时空需求量，表情识别率也有所提高。

The sampling method not only reduces the need of compute time and storage memory, but also improves the recognition rates.

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该系统大幅缩减特征提取及分类的时空需求量，表情识别率也有所提高。

The sampling method not only reduces the need of compute time and storage memory, but also improves the recognition rates.

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