孔瑋婷 皋軍 丁澤超 史恭波
摘要:針對(duì)基于局部紋理特征的人臉表情識(shí)別算法不能有效表達(dá)不同表情狀態(tài)下人臉運(yùn)動(dòng)單元差異性的問(wèn)題,提出一種改進(jìn)的稀疏表示人臉表情識(shí)別算法,將人臉紋理特征與全局位置特征用稀疏表示模型相結(jié)合,得到人臉表情的稀疏系數(shù)矩陣,并作為支持向量機(jī)表情識(shí)別的輸入。人臉表情庫(kù)BU_3DFE實(shí)驗(yàn)結(jié)果表明,該算法提高了表情識(shí)別的準(zhǔn)確率。
關(guān)鍵詞:表情識(shí)別;稀疏表示;特征融合
DOIDOI:10.11907/rjdk.161671
中圖分類號(hào):TP312文獻(xiàn)標(biāo)識(shí)碼:A文章編號(hào):1672-7800(2016)006-0031-02
參考文獻(xiàn):
[1]JI ZHENG Y,XIA M,MITSURU L,YU-LI X.Facial expression recognition based on feature point vector and texture deformation energy parameters[J].Journal of Electronics and Information Technology,2013,35(10):2403-2410.
[2]ZHAN YONGZHAO,YE JINGFU,NIU DEJIAO.Facial expression recognition based on gabor wavelet transformation and elastictemplates matching[J].International Journal of Image and Graphics,2006,6(1):125-138.
[3]L YIN,X WEI,J WANG,et al.A 3D facial expression database for facial behavior research[C].IEEE International Conference on Automatic Face and Gesture Recognition.(FG2006)[C],IEEE Computer Society TC PAMI.Southampton,UK,2006.
[4]MOORE S,BOWDEN R.Local binary patterns for multi-view facial expression recognition[J].Computer Vision and Image Understanding,2011,115(4):541-558.
[5]BU FA H,YIN-CHENG H,BING-XING C.A novel facial expression recognition method based on semantic knowledge of analytical hierarchy process[J].Journal of Image and Graphics,2011.
[6]RUDOVIC,OGNJEN,PATRAS.Coupled Gaussian process regression for pose-invariant facial expression recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(6):1357-1369.