计算机工程 ›› 2010, Vol. 36 ›› Issue (15): 176-178.doi: 10.3969/j.issn.1000-3428.2010.15.062

• 人工智能及识别技术 • 上一篇    下一篇

基于多频域LBP-TOP的人脸表情识别

孔 健,詹永照   

  1. (江苏大学计算机科学与通信工程学院,镇江 212013)
  • 出版日期:2010-08-05 发布日期:2010-08-25
  • 作者简介:孔 健(1986-),男,硕士研究生,主研方向:图像处理,模式识别;詹永照,教授、博士、博士生导师
  • 基金项目:
    国家自然科学基金资助项目(60673190)

Facial Expression Recognition Based on Multi-frequency LBP-TOP

KONG Jian, ZHAN Yong-zhao   

  1. (School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang 212013)
  • Online:2010-08-05 Published:2010-08-25

摘要: 针对人脸表情时空域特征信息的有效提取问题,提出一种多频域LBP-TOP与最大间隔球形支持向量机相结合的人脸表情识别算法。采用小波分解增强序列各帧的图像信息,对同频率的子图像序列提取分块改进的LBP-TOP特征,采用最大间隔球形支持向量机进行样本的训练及识别。实验结果证明,该方法能有效提取运动的表情特征,识别率高,同时符合实时性要求。

关键词: 模式识别, 人脸表情识别, 小波分解, 二元局部模式, 最大间隔球形支持向量机

Abstract: According to the problem of effective extraction of facial expression information in space-time domain, one kind facial recognition method based on multi-frequency Local Binary Patterns from Three Orthogonal Panels(LBP-TOP) features and Maximal-margin Spherical- structured Support Vector Machine(MSSVM) is proposed. It adapts wavelet decomposition to enhance information of each frame in image sequence. It extracts improved LBP-TOP features of sub-images on the same frequency. MSSVM is applied for sample training and recognition. Experimental result indicates that, this method can extract movement expression feature more effectively, as well as recognition rate is better, and it meets the requirement of real-time.

Key words: pattern recognition, facial expression recognition, wavelet decomposition, local binary pattern, Maximal-margin Spherical-structured Support Vector Machine(MSSVM)

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