基于加权局部二值模式的面部表情识别

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI:10.1109/ICCITECHN.2010.5723877

M. Shoyaib, M. Abdullah-Al-Wadud, Jo Moo Youl, Muhammad Mahbub Alam, O. Chae

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引用次数: 4

摘要

提出了一种面部表情识别方法，该方法在局部二值模式(Local Binary Pattern, LBP)中加入权重，生成实体表情特征。此外，我们使用Adaboost选择一小部分显著特征，并将其用于支持向量机(SVM)对面部表情进行有效分类。实验结果表明，我们的方法在准确性和复杂性方面都优于目前最先进的方法。

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Facial expression recognition based on a weighted Local Binary Pattern

We introduce a facial expression recognition method, which incorporates a weight to the Local Binary Pattern (LBP), and generates solid expression features. Furthermore, we use Adaboost to select a small set of prominent features, which is used by the Support Vector Machine (SVM) to classify facial expressions efficiently. Experimental results demonstrate that our method outperforms the state-of-the-art methods in terms of both accuracy and complexities.

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2010 13th International Conference on Computer and Information Technology (ICCIT)

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