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王甦菁
认知与发展心理学研究室 副研究员
电 话:  010-64875971
传 真:  010-64875971
通讯地址:  北京市朝阳区林萃路16号院中科院心理所
邮政编码:  100101
电子邮件:  wangsujing@psych.ac.cn
课题组网站:  

简历:

2017.03至今 中国科学院心理研究所,副研究员
2015.07-2017.02 中国科学院心理研究所,助理研究员
2012.08-2015.06 中国科学院心理研究所,博士后
2008.09-2012.06 吉林大学,计算机应用技术,工学博士学位
2005.09-2007.06 吉林大学,软件工程,工程硕士学位
1999.09-2002.06 淮海工学院,计算机及应用,工学学士学位
1998.02-2005.06 江苏省灌云县中学,教师
1995.09-1997.06 江苏省广播电视大学,财务会计,普通专科

研究领域:

模式识别(特别是人脸识别和微表情识别),机器学习,图像处理,现在重点研究基于视觉的谎言识别。

社会任职:

2019.09-今 中国计算机学会人机交互专业委员会委员
2017.10-今 中国图象图形学学会机器视觉专业委员会委员
2017.09-今 中国人工智能学会人工心理与人工情感专业委员会委员
2016.09-今 中国计算机学会计算机视觉专业委员会委员
2014.02-今 Neurocomputing编委
2016-2017 Journal of Computational Science 期刊客座编辑

获奖及荣誉:

2018年第八届吴文俊人工智能科学技术奖(自然科学类)一等奖(排名第一)
2016年北京市残疾人自强模范
2014年吉林省优秀博士学位论文
2014年吉林大学优秀博士学位论文
2013年获得“北京榜样”提名奖
2013年获得新华社“中国网事?感动2012”年度人物
2013年获得“感动吉林”2012年度人物
2011年获得IBM中国优秀学生奖学金
2011年获得吉林大学第二十五届研究生“精英杯”学术成果大奖赛一等奖
2009年评为吉林大学2008-2009学年优秀研究生
2009年获得吉林大学2008-2009学年二等研究生优秀奖学金
2005年授予江苏省连云港市残疾人自强模范
2004年江苏省劳动保障厅授予“江苏省技术能手”称号决定
2002年获得江苏省残疾人电脑比赛一等奖
2001年评为江苏省精神文明建设新人新事
2001年评为淮海工学院优秀学员
2001年评为江苏省连云港市技术能手
2000年国家授予全国职工自学成才奖
2000年获得江苏省残疾人电脑比赛一等奖
1999年评为江苏省职工自学成才者
1999年评为江苏省连云港市“十佳新人新事”
1999年评为江苏省连云港市“第六届连云港市十大杰出青年”
1999年评为江苏省连云港市灌云县县级技术拔尖人才
1997年获首届全国大学生电脑大赛总决赛纪念奖
1997年评为江苏省电大优秀毕业生
1995年江苏省连云港市微机使用大赛获得第三名
1993年评为江苏省连云港市灌云县最佳青年

代表论著:

1.Wang Su-Jing, Lin Bo, Wang Yong, Yi Tongqiang, Zou Bochao, Lyu Xiang-wen. Action Units recognition based on Deep Spatial-Convolutional and Multi-label Residual network [J]. Neurocomputing, 2019, 359: 130-138.

2.See John, Yap Moi Hoon, Li Jingting, Hong Xiaopeng, Wang Su-Jing. MEGC 2019 – The Second Facial Micro-Expressions Grand Challenge [C]. Proceedings of the 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), 2019, 1-5.

3.Li J., Soladié C., Séguier R., Wang S., Yap M. H. Spotting Micro-Expressions on Long Videos Sequences [C]. Proceedings of the 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), 2019, 1-5.

4.Huang Xiaohua, Wang Su-Jng, Liu Xin, Zhao Guoying, Feng Xiaoyi, Pietikainen Matti. Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous Facial Micro-Expression Recognition [J]. IEEE Transactions on Affective Computing, 2019, 10(1): 32-47.

5.He Ying, Yang Han-Bo, Wang Su-Jing. CDBV: A Driving Dataset with Chinese Characteristics From a Bike View [J]. IEEE Access, 2019, 7: 51714-51723.
6.Su-Jing Wang, Bing-Jun Li, Yong-Jin Liu, Wen-Jing Yan, Xinyu Ou, Xiaohua Huang, Feng Xu, Xiaolan Fu. Micro-expression Recognition with Small Sample Size by Transferring Long-term Convolutional Neural Network [J]. Neurocomputing, 2018, 312(0): 251-226.
7.Fangbing Qu#, Su-Jing Wang#, Wen-Jing Yan, He Li, Shuhang Wu, Xiaolan Fu. CAS(ME)^2: A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition [J]. IEEE Transactions on Affective Computing, 2018, 9(4): 424-436.
8.Mingyue Niu, Ya Li, Jianhua Tao, Su-Jng Wang. Micro-Expression Recognition Based on Local Two-Order Gradient Pattern [C]. Proceedings of the First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), 2018, 1-6.
9.Moi Hoon Yap, John See, Xiaopeng Hong, Su-Jing Wang. Facial Micro-Expressions Grand Challenge 2018 Summary [C]. Proceedings of the 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), 2018, 675-678.
10.Wang, S-J.*, Wu S., Qian X., Li J., Fu X. A Main Directional Maximal Difference Analysis for Spotting Facial Movements from Long-term Videos[J]. Neurocomputing, 2017, 230(382-389.
11.Wang, S-J.*, Yan, W-J., Sun, T., Zhao, G., & Fu, X. (2016). Sparse tensor canonical correlation analysis for micro-expression recognition. Neurocomputing, 214, 218-232.
12.Wang, S-J., Wu S, Fu X. A Main Directional Maximal Difference Analysis for Spotting Micro-expressions[C]. In Workshop on Facial Informatics (WFI), in conjunction with the Asian Conference on Computer Vision (ACCV) 2016, Taipei, November 20-24, 2016.
13.Liu, Y.-J., Zhang, J.-K., Yan, W.-J., Wang, S.-J.*, Zhao, G., & Fu, X. L. (2016). A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition. IEEE Transactions on Affective Computing, 7(4), 299-310.
14.Chen, H.-L., Wang, G., Ma, C., Cai, Z.-N., Liu, W.-B., & Wang, S.-J.* (2016). An Efficient Hybrid Kernel Extreme Learning Machine Approach for Early Diagnosis of Parkinson’s Disease. Neurocomputing.184, 131-144.
15.Qu, F., Wang, S.-J., Yan, W., & Fu, X.* (2016). CAS(ME)2: A Database of Spontaneous Macro-Expressions and Micro-Expressions. in Human-Computer Interaction. Novel User Experiences: 18th International Conference, HCI International 2016, Toronto, ON, Canada, July 17-22, 2016. Proceedings, Part III, M. Kurosu, Editor. 2016, Springer International Publishing: Cham. p. 48-59.
16.Yu, M., Liu, Y.-J.*, Wang, S.-J., Fu, Q., & Fu, X. (2016). A PMJ-inspired cognitive framework for natural scene categorization in line drawings. Neurocomputing, 173, Part 3, 2041-2048.
17.Huang, X., Wang, S.-J., Zhao, G., & Piteikainen, M. (2015). Facial Micro-Expression Recognition Using Spatiotemporal Local Binary Pattern with Integral Projection. Paper presented at the Computer Vision Workshop (ICCVW), 2015 IEEE International Conference on,2015, 1-9.
18.Wang, S.-J.*, Yan, W.-J., Li, X., Zhao, G., Zhou, C.-G., Fu, X., Yang, M., & Tao, J. (2015). Micro-Expression Recognition Using Color Spaces. IEEE Transactions on Image Processing, 24(12), 6034-6047.
19.Chen, H. l., Yang, B., Wang, S.-J., Wang, G., Liu, D. y., Li, H. z., & Liu, W. b. (2014). Towards an optimal support vector machine classifier using a parallel particle swarm optimization strategy. Applied Mathematics and Computation, 239(0), 180-197. doi: http://dx.doi.org/10.1016/j.amc.2014.04.039
20.Wang, S.-J., Yan, S., Yang, J., Zhou, C.-G., & Fu, X. (2014). A General Exponential Framework for Dimensionality Reduction. IEEE Transactions on Image Processing, 23(2), 920-930. doi: 10.1109/TIP.2013.2297020
21.Wang, S.-J., Chen, H.-L., Yan, W.-J., Chen, Y.-H., & Fu, X. (2014). Face Recognition and Micro-expression Recognition Based on Discriminant Tensor Subspace Analysis Plus Extreme Learning Machine. Neural Processing Letters, 39(1), 25-43. doi: 10.1007/s11063-013-9288-7
22.Wang, S.-J., Yan, W.-J., Li, X., Zhao, G., & Fu, X. L. (2014). Micro-expression Recognition Using Dynamic Textures on Tensor Independent Color Space. Paper presented at the the 22nd International Conference on Pattern Recognition (ICPR), Stockholm, Sweden.
23.Wang, S.-J., Yan, W.-J., Zhao, G., Fu, X., & Zhou, C.-G. (2014). Micro-expression Recognition using Robust Principal Component Analysis and Local Spatiotemporal Directional Features. Paper presented at the ECCV workshop on Spontaneous Facial Behavior Analysis.
24.Yan, W.-J., Wang, S.-J., Chen, Y.-H., Zhao, G., & Fu, X. (2014). Quantifying Micro-expressions with Constraint Local Model and Local Binary Pattern. Paper presented at the ECCV workshop on Spontaneous Facial Behavior Analysis.
25.Yan, W.-J., Wang, S.-J., Liu, Y.-J., Wu, Q., & Fu, X. (2014). For micro-expression recognition: Database and suggestions. Neurocomputing, 136(0), 82-87. doi: http://dx.doi.org/10.1016/j.neucom.2014.01.029
26.Yan, W.-J., Li, X., Wang, S.-J., Zhao, G., Liu, Y.-J., Chen, Y.-H., & Fu, X. (2014). CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation. Plos one, 9(1), e86041. doi: 10.1371/journal.pone.0086041
27.Chen, H.-L., Huang, C.-C., Yu, X.-G., Xu, X., Sun, X., Wang, G., & Wang, S.-J. (2013). An efficient diagnosis system for detection of Parkinson’s disease using fuzzy k-nearest neighbor approach. Expert Systems with Applications, 40(1), 263-271. doi: 10.1016/j.eswa.2012.07.014
28.Wang, S.-J., Zhou, C.-G., & Fu, X. (2013). Fusion Tensor Subspace Transformation Framework. Plos one, 8(7), e66647. doi: 10.1371/journal.pone.0066647
29.Yan, W.-J., Wu, Q., Liu, Y.-J., Wang, S.-J., & Fu, X. (2013). CASME Database: A Dataset of Spontaneous Micro-Expressions Collected From Neutralized Faces. Paper presented at the the 10th IEEE Conference on Automatic Face and Gesture Recognition (FG), Shanghai, China.
30.梁静, 颜文靖, 吴奇, 申寻兵, 王甦菁, & 傅小兰. (2013). 微表情研究的进展与展望. 中国科学基金, 27(2), 75-78.
31.Chen, H.-L., Yang, B., Wang, G., Wang, S.-J., Liu, J., & Liu, D.-Y. (2012). Support Vector Machine Based Diagnostic System for Breast Cancer Using Swarm Intelligence. Journal of Medical Systems, 36(4), 2505-2519. doi: 10.1007/s10916-011-9723-0
32.Jia, C.-C., Wang, S.-J., Peng, X.-J., Pang, W., Zhang, C.-Y., Zhou, C.-G., & Yu, Z.-Z. (2012). Incremental multi-linear discriminant analysis using canonical correlations for action recognition. Neurocomputing, 83(16), 56-63.
33.Pang, E.-P., Wang, S.-J., Qu, M.-Z., Liu, R., Jia, C.-C., & Yu, Z.-Z. (2012). 2D-SPP: A Two-dimensional Extension of Sparsity Preserving Projections. Journal of Information and Computational Science, 9(13), 3683-3692.
34.Wang, S.-J., Sun, M.-F., Chen, Y.-H., Pang, E.-P., & Zhou, C.-G. (2012). STPCA: Sparse Tensor Principal Component Analysis for Feature Extraction. Paper presented at the the 21st International Conference on Pattern Recognition (ICPR), Tsukuba, Japan.
35.Wang, S.-J., Yang, J., Sun, M.-F., Peng, X.-J., Sun, M.-M., & Zhou, C.-G. (2012). Sparse Tensor Discriminant Color Space for Face Verification. IEEE Transactions on Neural Networks and Learning Systems, 23(6), 876-888. doi: 10.1109/tnnls.2012.2191620
36.周春光, 孙明芳, 王甦菁, 陈前, 刘小华, & 刘昱昊. (2012). 基于稀疏张量的人脸图像特征提取方法. 吉林大学学报(工学版), 42(6), 1521-1526.
37.Chen, H.-L., Liu, D.-Y., Yang, B., Liu, J., Wang, G., & Wang, S.-J. (2011). An Adaptive Fuzzy k-Nearest Neighbor Method Based on Parallel Particle Swarm Optimization for Bankruptcy Prediction. Paper presented at the the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'2011), Shenzhen, China.
38.Chen, H.-L., Yang, B., Wang, G., Liu, J., Xu, X., Wang, S.-J., & Liu, D.-Y. (2011). A novel bankruptcy prediction model based on an adaptive fuzzy k-nearest neighbor method. Knowledge-Based Systems, 24(8), 1348-1359. doi: 10.1016/j.knosys.2011.06.008
39.Liu, Y., Wang, G., Chen, H., Dong, H., Zhu, X., & Wang, S.-J. (2011). An Improved Particle Swarm Optimization for Feature Selection. Journal of Bionic Engineering, 8(2), 191-200. doi: 10.1016/S1672-6529(11)60020-6
40.Sun, M.-F., Wang, S.-J., Liu, X.-H., Jia, C.-C., & Zhou, C.-G. (2011). Human Action Recognition Using Tensor Principal Component Analysis. Paper presented at the the 4th IEEE International Conference on Computer Science and Information Technology.
41.Wang, S.-J., Yang, J., Zhang, N., & Zhou, C.-G. (2011). Tensor Discriminant Color Space for Face Recognition. IEEE Transactions on Image Processing, 20(9), 2490-2501. doi: 10.1109/TIP.2011.2121084
42.Wang, S.-J., Chen, H.-L., Peng, X.-J., & Zhou, C.-G. (2011). Exponential locality preserving projections for small sample size problem. Neurocomputing, 74(17), 3654-3662. doi: 10.1016/j.neucom.2011.07.007
43.Wang, S.-J., Zhou, C.-G., Chen, Y.-H., Peng, X.-J., Chen, H.-L., Wang, G., & Liu, X. (2011). A novel face recognition method based on sub-pattern and tensor. Neurocomputing, 74(17), 3553-3564. doi: 10.1016/j.neucom.2011.06.017
44.Wang, S.-J., Zhou, C.-G., Zhang, N., Peng, X.-J., Chen, Y.-H., & Liu, X. (2011). Face recognition using second-order discriminant tensor subspace analysis. Neurocomputing, 74(12-13), 2142-2156. doi: 10.1016/j.neucom.2011.01.024
45.Wang, S.-J., Jia, C.-C., Chen, H.-L., & Zhou, C.-G. (2011). Matrix Exponential LPP for Face Recognition. Paper presented at the the First Asian Conference on Pattern Recognition (ACPR), Beijing, China.
46.Wang, S.-J., Zhou, C.-G., Sun, M.-F., Chen, H.-L., Liu, X.-H., & Peng, X.-J. (2011). Can Estimate Age Range Using 'a Face a Person'? Journal of Computational Information Systems, 7(13), 4586-4593.
47.Wang, S.-J., Zhang, N., Peng, X.-J., & Zhou, C.-G. (2011). Two-dimensional Locality Preserving Projection Based on Maximum Scatter Difference. Journal of Information and Computational Science, 8(3), 484-494.
48.Wang, S.-J., Zhang, N., Sun, M.-F., & Zhou, C.-G. (2011). The Analysis of Parameters t and k of LPP on Several Famous Face Databases. Paper presented at the the Second International Conference on Swarm Intelligence.
49.陈前, 王甦菁, 刘小华, 高蕾, & 周春光. (2011). 一种快速的虹膜定位算法. 吉林大学学报(理学版), 49(06), 1095-1100.
50.刘小华, 石娜, 王甦菁, & 李春玲. (2011). 复杂背景下同光度性质物体的图像分割. 吉林大学学报(理学版), 49(05), 901-905.
51.王甦菁, 周春光, 张娜, 李建朋, & 张利彪. (2011). 一种基于形状和纹理特征的人脸年龄估计方法. 吉林大学学报(工学版), 41(5), 1383-1387.
52.张德才, 周春光, 周强, 池淑珍, & 王甦菁. (2011). 基于轮廓的孔洞填充算法. 吉林大学学报(理学版), 49(1), 82-86.
53.Jia, C.-C., Wang, S.-J., Xu, X., Zhou, C.-G., & Zhang, L. (2010). Tensor analysis and multi-scale features based multi-view human action recognition. Paper presented at the the Second International Conference on Computer Engineering and Technology (ICCET). 10.1109/ICCET.2010.5485732%\ 2011-05-04 23:55:00
54.Wang, S.-J., Zhang, D.-C., Jia, C.-C., Zhang, N., Zhou, C.-G., & Zhang, L.-B. (2010). A Sign Language Recognition Based on Tensor. Paper presented at the the Second International Conference on Multimedia and Information Technology (MMIT). 10.1109/MMIT.2010.21%\ 2011-07-14 09:09:00
55.Zhang, L., Xu, X., Wang, S.-J., Ma, M., Zhou, C.-G., & Sun, C. (2010). Solved Environmental/Economic Dispatch Based on Multi-objective PSO. Paper presented at the the 2010 International Conference on Intelligent Computation Technology and Automation (ICICTA). 10.1109/ICICTA.2010.470%\ 2010-08-19 18:06:00
56.Zhang, L., Xu, X., Wang, S.-J., Zhou, C.-G., & Sun, C. (2010). Environmental/Economic Dispatch using a improved Differential Evolution. Paper presented at the the Second International Conference on Computer Engineering and Technology (ICCET).
57.陈震, 张娜, & 王甦菁. (2010). 一种基于概念矩阵的概念格生成算法. 计算机科学, 37(9), 180-183.

承担科研项目情况:

20202023 国家自然科学基金联合基金重点支持项目“面向社会公共安全的隐藏情绪分析与识别方法究”(U19B2032)
                                       资助金额         255万元

20192020 社会安全风险感知与防控大数据应用国家工程实验室主任基金“面向审讯场景的无感知情绪监测分析技术研
           究”(18112403)子课题,    资助金额         100万元

20182021 国家自然科学基金委面上项目“基于深度学习的微表情检测和识别的研究” (61772511)
                                       
资助金额         68万元
20142017 国家自然科学基金委面上项目“基于稀疏张量的微表情识别研究” (61379095)
                                       
资助金额         73万元
20152017 北京市自然科学基金面上项目“基于稀疏张量和深度学习的微表情识别的研究” (4152055)
                                       
资助金额         18万元
20142015 中国博士后科学基金第七批特别资助项目 “基于稀疏张量的彩色微表情视频的动态纹理提取”(2014T70133)
                                       
资助金额         15万元
2012
2014 中国博士后科学基金面上项目“彩色微表情视频的张量表示及其特征抽取的研究”(2012M520428)
                                       
资助金额         5万元
2013
2014 符号计算与知识工程教育部重点实验室开放基金项目“彩色微表情视频的稀疏表示”(93K172013K04)
                                       
资助金额         5万元
2014
2015 模式识别国家重点实验室开放课题“彩色微表情视频纹理提取和稀疏表示的研究”(201306295)
                                       
资助金额         5万元