CAJ | 학술논문

为更好获取人脸局部表情特征，提出了一种融合局部二值模式（Local Binary Pattern，LBP）和局部稀疏表示的人脸表情特征与识别方法。为深入分析表情对人脸子区域的影响，根据五官特征对人脸进行非均匀分区，并提取局部LBP特征；为精细刻画人脸局部纹理，整合人脸局部特征，设计了人脸局部稀疏重构表示方法，并根据表情对各局部子区域的影响因子，加权融合局部重构残差进行人脸表情识别。在JAFFE2表情人脸库上的对比实验，验证了该方法的可行性和鲁棒性。
위경호획취인검국부표정특정，제출료일충융합국부이치모식（Local Binary Pattern，LBP）화국부희소표시적인검표정특정여식별방법。위심입분석표정대인검자구역적영향，근거오관특정대인검진행비균균분구，병제취국부LBP특정；위정세각화인검국부문리，정합인검국부특정，설계료인검국부희소중구표시방법，병근거표정대각국부자구역적영향인자，가권융합국부중구잔차진행인검표정식별。재JAFFE2표정인검고상적대비실험，험증료해방법적가행성화로봉성。
In order to effectively represent facial expression feature, a novel method fusing Local Binary Pattern(LBP) and local sparse representation is proposed for facial expression representation and recognition. The face image is divided into non-uniform local regions based on face features, and the LBP features are calculated for every facial local region. For depicting facial local texture exactly and integrating facial local features, a facial local reconstruction method based on sparse representation is designed. According to the influence on the facial regions for expression, a weighted fusion algorithm is presented to collect all the local reconstruction residuals and address the expression recognition task. The experiments tested on JAFFE2 face expression database demonstrate the proposed method is feasible and robust to facial expression.