[1]孙正兴,徐文晖.基于局部SVM分类器的表情识别方法[J].智能系统学报,2008,3(5):455-466.
SUN Zheng-xing,XU Wen-hui.Fac ial expression recogn ition based on local SVM classif iers[J].CAAI Transactions on Intelligent Systems,2008,3(5):455-466.
点击复制
SUN Zheng-xing,XU Wen-hui.Fac ial expression recogn ition based on local SVM classif iers[J].CAAI Transactions on Intelligent Systems,2008,3(5):455-466.
基于局部SVM分类器的表情识别方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
3
期数:
2008年第5期
页码:
455-466
栏目:
学术论文—机器感知与模式识别
出版日期:
2008-10-25
- Title:
- Fac ial expression recogn ition based on local SVM classif iers
- 文章编号:
- 1673-4785 (2008) 05-0455-12
- 分类号:
- TP391
- 文献标志码:
- A
- 摘要:
- 提出了一种新的视频人脸表情识别方法. 该方法将识别过程分成人脸表情特征提取和分类2个部分,首先采用基于点跟踪的活动形状模型(ASM)从视频人脸中提取人脸表情几何特征;然后,采用一种新的局部支撑向量机分类器对表情进行分类. 在Cohn2Kanade数据库上对KNN、SVM、KNN2SVM和LSVM 4种分类器的比较实验结果验证了所提出方法的有效性.
- Abstract:
- This paper p resents a novel technique developed for the identification of facial exp ressions in video sources. The method uses two step s: facial exp ression feature extraction and exp ression classification. Firstwe used an active shape model (ASM) based on a facial point tracking system to extract the geometric features of facial ex2 p ressions in videos. Then a new type of local support vectormachine (LSVM) was created to classify the facial ex2 p ressions. Four different classifiers using KNN, SVM, KNN2SVM, and LSVM were compared with the new LSVM. The results on the Cohn2Kanade database showed the effectiveness of ourmethod
- 参考文献/References:
-
[ 1 ] FRANCO L, TREVES A. A neural network facial exp res2 sion recognition system using unsupervised local p rocessing [C ] / / Proceeding of the 2nd International Symposium on Image and Signal Processing and Analysis ( ISPA2001 ). Pula, Croatia, 2001: 6282632.
[ 2 ]LYONSM, AKAMATSU S. Coding facial exp ressions with gaborwavelets[C ] / /Proceeding of the Third IEEE Interna2 tional Conference on Automatic Face and Gesture Recogni2 tion. Nara, Japan: IEEE Computer Society, 1998: 4542459.
[ 3 ]BASSIL I J. Emotion recognition: the role of facial move2 ment and the relative importance of upper and lower areas of the face[ J ]. J Personality Social Psychol, 1979, 37: 20492 2059.
[ 4 ] FASEL B, LUETTIN J. Recognition of asymmetric facial action unit activities and intensities [ C ] / /Proceeding of 15 th International Conference on Pattern Recognition ( ICPR 2000). Barcelona, Spain, 2000: 110021103.
[ 5 ] TIAN YL, KANADE T, COHN J F. Recognizing action u2 nits for facial exp ression analysis[ J ]. IEEE Transaction on PAM I, 2001, 23 (2) : 972115.
[ 6 ]BARTLETTM S, L ITTLEWORT G, FRANKM G, LA IN2 SCSEK C, FASEL I, MOVELLAN J. Recognizing facial ex2 p ression: Machine learning and app lication to spontaneous behavior[C ] / / Proceeding of Conference on Computer Vi2 sion and Pattern Recognition (CVPR 2005 ). San Diego, CA, USA: IEEE Computer Society, 2005: 5682573.
[ 7 ] COHEN I, SEVE N, COZMAN G G, CIRELO M C, HUANG T S. LearningBayesian network classifier for facial exp ression recognition using both labeled and unlabeled data [C ] / / Proceeding of Conference on Computer Vision and Pattern Recognition (CVPR 2003). Madison, Wisconsin, USA: IEEE Computer Society, 2003: 5952601.
?[ 8 ]L IEN J J , KANADE T, COHN J F, L I C C. Detection, tracking, and classification of action units in facial exp res2 sion [ J ]. Journal of Robotics and Autonomous Systems, 2000, 31: 1312146.
[ 9 ]L ISETTI C L, SCH IANO D J. Automatic facial exp ression interp retation: where human2computer interaction, artificial intelligence and cognitive science intersect [ J ]. Pragmatics & Cognition, 2000, 8: 1852235.
[ 10 ] ZHANG H, BERG A C, MA IRE M, MAL IK J. SVM2 KNN: Discriminative nearest neighbor classification for visual category recognition[C ] / / Proceeding of Conference on Computer Vision and Pattern Recognition ( CVPR 2006). New York, USA: IEEE Computer Society, 2006: 212622136.
[ 11 ]BASSIL I J. Emotion recognition: the role of facial move2 ment and the relative importance of upper and lower areas of the face [ J ]. J Personality Social Psychol, 1979, 37: 204922059.
[ 12 ] EKMAN P, FR IESEN W V. Facial action coding system: investigator’s guide [M ]. Palo Alto: Consulting Psycholo2 gists Press, 1978: 1562163.
?[ 13 ] PANTICM, ROTHKRANTZ L J M. Automatic analysis of facial exp ressions: the state of the art[ J ]. IEEE Trans on PAM I, 2000, 22 (12) : 142421445.
?[ 14 ]MASE K. Recognition of facial exp ression from op tical flow [ J ]. IEICE Transactions on Communications ( Special Is2 sue on ComputerVision and itsApp lications) , 1991, 10: 347423483.
[ 15 ]BLACKM J , YACOOB Y. Tracking and recognizing rigid and non2rigid facialmotions using local parametric models of image motion [ C ] / /Proceeding of Fifth International Conference on Computer Vision ( ICCV95 ). Cambridge, MA, USA, 1995: 3742381.
?[ 16 ]OL IVER N, PENTLAND A, ERARD F B. LAFTER: a real2time face and lip s trackerwith facial exp ression recog2 nition[ J ]. Pattern Recognition, 2000, 33: 136921382.
[ 17 ]BARTLETTM S, L ITTLEWORT G, FASEL I, MOVEL2 LAN J R. Real time face detection and facial exp ression recognition: development and app lications to human com2 puter interaction[ C ] / /Proceeding of Conference on Com2 puter Vision and Pattern Recognition ( CVPR 2003 ). Madison, Wisconsin, USA: IEEE Computer Society, 2003: 53258.
[ 18 ]COHEN I, SEBE N, GARG S, CHEN L S, HUANGA T S. Facial exp ression recognition from video sequences: temporal and static modeling [ J ]. Computer Vision and Image Understanding, 2003, 91 (122) : 1602187.
[ 19 ]COOTES T F, TAYLOR C J , COOPER D H, GRAHAM J. Active shape models2their training and app lication[ J ]. Computer Vision and Image Understanding, 1995, 61 (1) : 38259.
?[ 20 ]KOBAYASH IH, HARA F. Facial interaction between an2 imated 3D face robot and human beings[C ] / / Proceedings of IEEE International Conference on Systems, Man, and Cybernetics. IEEE Computer Society Press, 1997: 37322 3737.
[ 21 ]COVER T, HART P. Nearest neighbor pattern classifica2 tion[ J ]. IEEE Transactions in Information Theory, 1967, 13: 21227.
[ 22 ]BURGES C J C. A tutorial on support vector machines for pattern recognition [ J ]. Knowledge Discovery and Data Mining, 1998, 2: 1212167.
[ 23 ]KANADE T, COHN J , TIAN Y. Comp rehensive database for facial exp ression analysis[ C ] / / Proceedings of Fourth IEEE International Conference on Face and Gesture Recog2 nition. IEEE Computer Society Press, 2000: 46253.
?[ 24 ] PANTICM, ROTHKRANTZ L JM. Expert system for au2 tomatic analysis of facial exp ressions [ J ]. Image and Vi2 sion Computing, 2000, 18 (11) : 8812905.
- 相似文献/References:
-
[1]彭程,刘帅师,万川,等.基于局部纹理ASM模型的人脸表情识别[J].智能系统学报,2011,6(3):231.
PENG Cheng,LIU Shuaishi,WAN Chuan,et al.An active shape model for facial expression recognition based on a local texture model[J].CAAI Transactions on Intelligent Systems,2011,6():231.
[2]童莹.一种方向性的局部二值模式在人脸表情识别中的应用[J].智能系统学报,2015,10(3):422.[doi:10.3969/j.issn.1673-4785.201405016]
TONG Ying.Local binary pattern based on the directions and its application in facial expression recognition[J].CAAI Transactions on Intelligent Systems,2015,10():422.[doi:10.3969/j.issn.1673-4785.201405016]
[3]高涛,杨朝晨,陈婷,等.深度多尺度融合注意力残差人脸表情识别网络[J].智能系统学报,2022,17(2):393.[doi:10.11992/tis.202107028]
GAO Tao,YANG Zhaochen,CHEN Ting,et al.Deep multiscale fusion attention residual network for facial expression recognition[J].CAAI Transactions on Intelligent Systems,2022,17():393.[doi:10.11992/tis.202107028]
[4]梁艳,温兴,潘家辉.融合全局与局部特征的跨数据集表情识别方法[J].智能系统学报,2023,18(6):1205.[doi:10.11992/tis.202212030]
LIANG Yan,WEN Xing,PAN Jiahui.Cross-dataset facial expression recognition method fusing global and local features[J].CAAI Transactions on Intelligent Systems,2023,18():1205.[doi:10.11992/tis.202212030]
备注/Memo
收稿日期: 2008-07-11.
基金项目: National High Technology Research and Development Program (863) of China ( 2007AA01Z334) ; National Natural Science Foundation of China (69903006, 60373065, 0721002) .
作者简介: 孙正兴,男, 1964 年生,教授、博士生导师,中国图像图形学会计算机动画与数字艺术专委会常务委员,中国计算机学会计算机辅助设计与图形学专委会委员,中国人工智能学会人工心理与人工情感专委会委员,江苏省微型电脑应用协会副理事长兼多媒体技术专委会主任,江苏省计算机学会计算机辅助设计与图形学专委会主任. 主要研究方向为多媒体计算、计算机视觉和环境智能. 获省部级科技进步三等奖3次. 已在国内外重要刊物上发表学术论文90余篇,主编教材3部、译著1部.
徐文晖, 男, 1984 年生, 硕士研究生,主要研究方向为计算机视觉与智能人机交互.
通信作者:孙正兴. E-mail: szx@nju. edu. cn.
更新日期/Last Update:
2009-05-18