基本信息
常虹 女 博导 计算技术研究所
电子邮件：changhong@ict.ac.cn
通信地址：北京市海淀区科学院南路6号 中科院计算所523室 100190
主页：http://vipl.ict.ac.cn/members/hchang

研究领域 机器学习与模式识别的算法和模型，特别是半监督学习、度量学习、深度学习、流形学习等
机器学习的方法在图像处理、计算机视觉、数据挖掘等领域的应用

招生信息
招生专业081203-计算机应用技术

招生方向 模式识别，机器学习，计算机视觉



教育、工作经历2008年3月 — 今 ：中国科学院计算技术研究所，副研究员；
2006年11月 — 2007年12月：施乐（欧洲）研究院，研究员（永久职位）；
2006年2月 — 11月：香港科技大学计算机系，博士后；
2001年9月— 2006年1月：香港科技大学计算机系，博士生；
1998年9月— 2001年4月：天津大学计算机系，硕士生；
1994年9月— 1998年7月：河北工业大学计算机系，本科生

教授课程 模式识别与机器学习、 概率论与数理统计、 机器学习、 机器学习方法

主要科研项目NSFC青年基金项目：面向图像识别的半监督距离度量学习方法研究，项目负责人；

NSFC面上项目：人物动作的时空层次表示与识别研究， 主要参加人；

NSFC重点项目：面向视频监控的生物特征识别关键理论与技术研究，主要参加人；

973课题：基于视觉特性的视频编码理论与方法研究，主要参加人；


NSFC重大项目课题：面向群体数据的AVS云媒体标准及验证平台，合作单位负责人


指导学生已指导学生
李哲硕士研究生081203-计算机应用技术
李瑞平硕士研究生081203-计算机应用技术
王占孔硕士研究生081203-计算机应用技术
严兴硕士研究生081203-计算机应用技术
现指导学生
邓雪松硕士研究生081203-计算机应用技术
徐霞清硕士研究生081203-计算机应用技术
李煜林硕士研究生085211-计算机技术

主要论文Journal Papers
Deming Zhai, Yu Zhang, Dit-Yan Yueng, Hong Chang, Xilin Chen, Wen Gao. Instance-specific canonical correlation analysis. Neurocomputing 155: 205-218, 2015.

Zhen Cui, Hong Chang, Shiguang Shan, Bingpeng Ma, Xilin Chen. Joint sparse representation for video-based face recognition. Neurocomputing, 2014.

W. Zheng, H. Chang, L. Liang, H. Ren, S. Shan, and X. Chen . Strip features for fast object detection . IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 2013.

D. Zhai, H. Chang, S. Shan, X. Chen, W. Gao. Multi-View Metric Learning with Global Consistency and Local Smoothness. ACM Transactions on Intelligent Systems and Technology. Volume 3 Issue 3, May 2012 .

Xiaopeng Hong, Hong Chang, Shiguang Shan, Bineng Zhong, Xilin Chen, Wen Gao. Sigma Set Based Implicit Online Learning For Object Tracking. IEEE Signal Processing Letters. vol.17, no.9, pp.807-810, Sept. 2010.

Bo Li, Hong Chang, Shiguang Shan, Xilin Chen. Low-Resolution Face recognition via Coupled Locality Preserving Mappings. IEEE Signal Processing Letters. Vol. 17, No. 1, 2010.

Bo Li, Hong Chang, Shiguang Shan, Xilin Chen. Aligning Coupled Manifolds for Face Hallucination. IEEE Signal Processing Letters. Vol. 16, No. 11, 2009.

D.Y. Yeung, H. Chang, G. Dai. A scalable kernel-based semi-supervised metric learning algorithm with out-of-sample generalization ability. Neural Computation. 20(11):2839-2861, November 2008.

H. Chang, D.Y. Yeung. Robust path-based spectral clustering. Pattern Recognition, 41(1):191-203, January 2008.

D.Y. Yeung, H. Chang, G. Dai. Learning the kernel matrix by maximizing a KFD-based class separability criterion. Pattern Recognition, 40(7):2021-2028, July 2007.

H. Chang, D.Y. Yeung. Kernel-based distance metric learning for content-based image retrieval. Image and Vision Computing, 25(5):695-703, May 2007.

D.Y. Yeung, H. Chang. A kernel approach for semi-supservised metric learning. IEEE Transactions on Neural Networks, 18(1):141-149, January 2007.

H. Chang, D.Y. Yeung, W.K. Cheung. Relaxational metric adaptation and its application to semi-supervised clustering and content-based image retrieval. Pattern Recognition, 39(10):1905-1917, October 2006.

H. Chang, D.Y. Yeung. Locally linear metric adaptation with application to semi-supervised clustering and image retrieval. Pattern Recognition, 39(7):1253-1264, July 2006.

H. Chang, D.Y. Yeung. Robust locally linear embedding. Pattern Recognition, 39(6):1053-1065, June 2006.

D.Y. Yeung, H. Chang. Extending the relevant component analysis algorithm for metric learning using both positive and negative equivalence constraints. Pattern Recognition, 39(5):1007-1010, May 2006.



Conference Papers


K. Liang, H. Chang, S. Shan, X. Chen. Attribute conjunction learning with recurrent neural network. ECML/PKDD(1):345-360, 2016.

X. Deng, B. Ma, H. Chang, S. Shan, X. Chen. Deep second-order Siamese network for pedestrian re-identification. ACCV(2):321-337, 2016.

K. Liang, H. Chang, S. Shan, X. Chen. A unied multiplicative model for attribute learning. International conference on Computer Vision (ICCV), 2015.

M. Ye, H. Chang, X. Chen. Online visual tracking via coupled object-context dictionary. BMVC, 2015.

Z. Cui, H. Chang, S. Shan, X. Chen. Generalized unsupervised manifold alignment. Proceedings of Neural Information Processing System (NIPS), 2014.

X. Yan, H. Chang, S. Shan, X. Chen. Modeling video dynamics with deep dynencoder. Proceedings of the Ninth European Conference on Computer Vision (ECCV), 2014.

Z. Cui, H. Chang, S. Shan, B. Zhong, X. Chen. Deep network cascade for image super-resolution. Proceedings of the Ninth European Conference on Computer Vision (ECCV),2014.

M. Kan, S. Shan, H. Chang, X. Chen. Stacked progressive auto-encoders (SPAE) for face recognition across poses. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2014.

D. Zhai, H. Chang, Y. Zhen, X. Liu, X. Chen, W. Gao. Parametric Local Multimodal Hashing for Cross-view Similarity Search. Proceedings of the 23rd International Joint Conference on Articial Intelligence (IJCAI). Beijing, China , August 3-9, 2013.

Y. Xie, H. Chang, Z. Li, L. Liang, X. Chen, D. Zhao. A unied framework for locating and recognizing human actions. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

Deming Zhai, Hong Chang, Bo Li, Shiguang Shan, Xilin Chen, Wen Gao. Manifold Alignment Via Corresponding Projections. BMVC'2010.

Xiaopeng Hong, Hong Chang, Xilin Chen, and Wen Gao. Boosted Sigma Set for Pedestrian Detection. ICPR'2010.

Bo Li, Hong Chang, Shiguang Shan, and Xilin Chen. Coupled Metric Learning for Face Recognition with Degraded Images. ACML'2009.

Deming Zhai, Hong Chang, Bo Li, Shiguang Shan, Xilin Chen, Wen Gao. Semi-Supervised Discriminant Analysis via Spectral Transduction. BMVC'2009.

Bo Li, Hong Chang, Shiguang Shan, Xilin Chen. Locality preserving constraints for super resolution with neighbor embedding. ICIP'2009.

Xiaopeng Hong, Hong Chang, Shiguang Shan, Xilin Chen and Wen Gao. Sigma Set: A Small Second Order Statistical Region Descriptor. CVPR'2009.

Bo Li, Hong Chang, Shiguang Shan, Xilin Chen, Wen Gao. Hallucinating Facial Images and Features. ICPR'2008.

Youhan Fang, Shiguang Shan, Hong Chang, Xilin Chen, Wen Gao. Parzen Discriminant Analysis. ICPR'2008.

H. Chang, D.Y. Yeung. Locally smooth metric learning with application to image retrieval. Proceedings of the Eleventh IEEE International Conference on Computer Vision (ICCV) , Rio de Janeiro, Brazil, 14-20 October 2007.

D.Y. Yeung, H. Chang, G. Dai. A scalable kernel-based algorithm for semi-supervised metric learning. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI) , Hyderabad, India, 6-12 January, 2007.

J.J. Pan, Q. Yang, H. Chang, D.Y. Yeung. A manifold regularization approach to calibration reduction for sensor-network-based tracking. Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI) , Boston, Massachusetts, USA, 16-20 July 2006.

H. Chang, D.Y. Yeung. Graph Laplacian kernels for object classification from a single example. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) , New York, NY, USA, 17-22 June 2006.

G. Dai, D.Y. Yeung, H. Chang. Extending kernel Fisher discriminant analysis with the weighted pairwise Chernoff criterion. Proceedings of the Ninth European Conference on Computer Vision (ECCV) , Graz, Austria, 7-13 May 2006.

H. Chang, D.Y. Yeung. Robust path-based spectral clustering with application to image segmentation. Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV) . Beijing, China. 15-21 October 2005.

H. Chang, D.Y. Yeung. Stepwise metric adaptation based on semi-supervised learning for boosting image retrieval performance. Proceedings of the Sixteenth British Machine Vision Conference (BMVC) . Oxford, UK. 5-8 September 2005.

D.Y. Yeung, H. Chang, Y. Xiong, S. George, R. Kashi, T. Matsumoto, G. Rigoll. SVC2004: First International Signature Verification Competition. Proceedings of the International Conference on Biometric Authentication (ICBA) , Hong Kong, 15-17 July 2004.

H. Chang, D.Y. Yeung. Locally linear metric adaptation for semi-supervised clustering. Proceedings of the Twenty-First International Conference on Machine Learning (ICML) , pp.153-160, Banff, Alberta, Canada, 4-8 July 2004.

H. Chang, D.Y. Yeung, Y. Xiong. Super-resolution through neighbor embedding. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) , vol.1, pp.275-282, Washington, DC, USA, 27 June - 2 July 2004.

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