Pattern Analysis & Learning Group

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• 手写汉字识别测试2010

The Pattern Analysis and Learning (PAL) Group was founded in 2005, by Dr. Cheng-Lin Liu, and supported by the “Hundred Talents Program” of the CAS. The research topics of the group include theory and methods of pattern recognition and machine learning, and the applications to document analysis, image analysis and text categorization.

Pattern classification methods have been widely applied in practical recognition problems, but are desired to yield higher performance. Classification is also a main task in machine learning. The problems to study include parametric and non-parametric density estimation, dimensionality reduction and feature selection, hybrid generative/discriminative learning, hybrid statistical/structural classification, multiple classifiers generation and fusion, incremental learning, semi-supervised learning, etc.

Character recognition and document analysis techniques are aimed to process large volumn of paper and pen-based documents. The remaining difficult problems include the recognition of unconstrained handwritten characters, character segmentation, analysis of complex layout, character recognition in low-resolution or degraded images, and so on. Also, we need to upgrade the task of document analysis to the level of linguistic contents, i.e., it can be combined with text categorization and retrieval.

• Cheng-Lin LIU(刘成林), Research Professor
• Xinwen HOU (侯新文) , Research Associate Professor
• Kaizhu Huang (黄开竹), PAL Group (黄开竹) , Research Associate Professor

1. Pattern Recognition Theory and Methods, Hundred Talents Program of CAS, Jan. 2006–Dec. 2008.
2. High Accuacy Chinese Character Recognition Based on ECOC, NSF China, Jan. 2006–Dec. 2007.
3. Pen-Based Memorandum Analysis and Recognition, supported by Central Research Laboratory, Hitachi Ltd., April 2005–March 2008.
4. Radical-Based Online Handwritten Chinese Character Recognition for Mobile Computing, supported by Microsoft Research Asia, April 2007–March 2009.
5. Information Fusion and Parameter Learning for Handwritten Character String Recognition, NSF China, Jan. 2008–Dec. 2010.
6. Pattern Recognition Theory, Methods and Applictions, NSF China, Jan. 2009–Dec. 2012.

• Symposium on Machine Learning in Image and Document
  
  Highlight Photos

• Xiaobo Jin, Cheng-Lin Liu, Xinwen Hou, Regularized margin-based conditional log-likelihood loss for prototype learning. Pattern Recognition, 43(7): 2428-2438, 2010.
• Bilan Zhu, Xiang-Dong Zhou, Cheng-Lin Liu, Masaki Nakagawa, A robust model for on-line handwritten japanese text recognition. IJDAR, 13(2): 121-131, 2010.
• 马龙龙，刘成林，基于统计部首模型的联机手写汉字识别方法，智能系统学报， 5(5): 385-391, 2010.
• Kaizhu Huang, Rong Jin, Zenglin Xu, Cheng-Lin Liu, Robust Metric Learning by Smooth Optimization, Proc. 26th UAI, California, USA, 2010.
• Guoqiang Zhong, Wu-Jun Li, Dit-Yan Yeung, Xinwen Hou, Cheng-Lin Liu: Gaussian Process Latent Random Field. Proc. 24th AAAI, Georgia, USA, 2010.
• Yan-Ming Zhang, Yu Zhang, Dit-Yan Yeung, Cheng-Lin Liu, Xinwen Hou: Transductive Learning on Adaptive Graphs. Proc. 24th AAAI, Georgia, USA, 2010.
• Cheng-Lin Liu, One-Vs-All Training of Prototype Classifier for Pattern Classification and Retrieval. Proc. 20th ICPR, Istanbul, Turkey, 2010, pp.3328-3331.
• Heng Wang, Xinwen Hou, Cheng-Lin Liu: Boosting Incremental Semi-supervised Discriminant Analysis for Tracking. Proc. 20th ICPR, Istanbul, Turkey, 2010, pp.2748-2751.
• Bo Xu, Kaizhu Huang, Cheng-Lin Liu: Dimensionality Reduction by Minimal Distance Maximization. Proc. 20th ICPR, Istanbul, Turkey, 2010, pp.569-572.
• Xiaobo Jin, Xinwen Hou, Cheng-Lin Liu: Multi-class AdaBoost with Hypothesis Margin. Proc. 20th ICPR, Istanbul, Turkey, 2010, pp.65-68.
• Fei Yin, Qiu-Feng Wang, Cheng-Lin Liu, Integrating Geometric Context for Text Alignment of Handwritten Chinese Documents, Proc. 12th ICFHR, Kolkata, India, 2010.
• Xiang-Dong Zhou, Da-Han Wang, Masaki Nakagawa, Cheng-Lin Liu, Error Reduction by Confusing Characters Discrimination for Online Handwritten Japanese Character Recognition, Proc. 12th ICFHR, Kolkata, India, 2010.
• Tong-Hua Su, Cheng-Lin Liu, Improving HMM-Based Chinese handwriting recognition using Delta features and synthesized string samples, Proc. 12th ICFHR, Kolkata, India, 2010.
• Heng Zhang, Da-Han Wang, Cheng-Lin Liu, Keyword Spotting from Online Chinese Handwritten Documents Using One-Vs-All Trained Character Classifier, Proc. 12th ICFHR, Kolkata, India, 2010.
• Long-Long Ma, Cheng-Lin Liu, Special Radical Detection by Statistical Classification for On-line Handwritten Chinese Character Recognition, Proc. 12th ICFHR, Kolkata, India, 2010.
• Cheng-Lin Liu, Fei Yin, Da-Han Wang, Qiu-Feng Wang, Online and Offline Handwritten Chinese Character Recognition: Benchmarking on New Databases, Proc. 2th CJKPR, Fukuoka, Japan, 2010.
• Da-Han Wang, Cheng-Lin Liu, An Approach to Real-Time Recognition of Chinese Handwritten Sentences, Proc. 2th CJKPR, Fukuoka, Japan, 2010.
• Cheng-Lin Liu, Fei Yin, Da-Han Wang, Qiu-Feng Wang, Chinese Handwriting Recognition Contest 2010, Proc. 4th CCPR, Chongqing, China, 2010.
• Yi-Feng Pan, Cheng-Lin Liu, Performance Evaluation for Text Localization Algorithms: An Empirical Study, Proc. 4th CCPR, Chongqing, China, 2010.
• Liang Xu, Fei Yin, Cheng-Lin Liu, Touching Character Splitting of Chinese Handwriting Using Contour Analysis and DTW, Proc. 4th CCPR, Chongqing, China, 2010.
• Yi-Feng Pan, Cheng-Lin Liu, Xinwen Hou, Fast Scene Text Localization by Learning-based Filtering and Verification, Proc. 17th ICIP, HongKong, China, 2010.
• An Lu, Xinwen Hou, Xiaolin Chen, Cheng-Lin Liu, Insect Species Recognition using Sparse Representation, Proc. 21th BMVC, Aberystwyth, UK, 2010.
• Guoqiang Zhong, Kaizhu Huang, Cheng-Lin Liu, Learning ECOC and Dichotomizers Jointly from Data. ICONIP (1) 2010, pp.494-502.
• Xiao-Hua Liu, Cheng-Lin Liu, Discriminative Training of Subspace Gaussian Mixture Model for Pattern Classification. ICIC (1) 2010, pp.213-221.

• X.-D. Zhou, D.-H. Wang, C.-L. Liu, A robust approach to text line grouping in online handwritten Japanese documents, Pattern Recognition, 42(9): 2077-2088, 2009.
• C.-L. Liu, C.Y. Suen, A new benchmark on the recognition of handwritten Bangla and Farsi numeral characters, Pattern Recognition, 42(12): 3287-3295, 2009.
• F. Yin, C.-L. Liu, Handwritten text line segmentation by clustering with distance metric learning, Pattern Recognition, 42(12): 3146-3157, 2009.
• 于金伦、周祥东、刘成林，手写字符串识别搜索算法研究，模式识别与人工智能，22(2): 182-187, 2009.
• B. Zhu, X.-D. Zhou, C.-L. Liu, M. Nakagawa, A robust model for on-line handwritten Japanese text recognition, Document Recognition and Retrieval XVI, Proc. SPIE, Vol.7247, 2009.
• F. Yin, Q.-F. Wang, C.-L. Liu, A tool for ground-truthing text lines and characters in off-line handwritten Chinese documents, Proc. 10th ICDAR, Barcelona, Spain, 2009.
• F. Yin, C.-L. Liu, A variational Bayes method for handwritten text line segmentation, Proc. 10th ICDAR, Barcelona, Spain, 2009.
• Q.-F. Wang, F. Yin, C.-L. Liu, Integrating language model in handwriting Chinese text recognition, Proc. 10th ICDAR, Barcelona, Spain, 2009.
• D.-H. Wang, C.-L. Liu, J.-L. Yu, X.-D. Zhou, CASIA-OLHWDB1: A database of online handwritten Chinese characters, Proc. 10th ICDAR, Barcelona, Spain, 2009.
• X.-D. Zhou, C.-L. Liu, M. Nakagawa, Online handwritten Japanese character string recognition using conditional random fields, Proc. 10th ICDAR, Barcelona, Spain, 2009.
• Y.-F. Pan, X. Hou, C.-L. Liu, Text localization in natural scene images based on conditional random field, Proc. 10th ICDAR, Barcelona, Spain, 2009.
• Y.-M. Zhang, X. Hou, S. Xiang, C.L. Liu, Subspace regularization: a new semi-supervised learning method, ECML PKDD2009, Bled, Slovenia.
• H. Wang, X. Hou, C.-L. Liu, Object tracking by bidirectional learning with feature selection, ICIP2009, Cairo, Egypt, 2009.

• T.-F. Gao, C.-L. Liu, High accuracy handwritten Chinese character recognition using LDA-based compound distances, Pattern Recognition, 42(11): 3442-3451, 2008.
• C.-L. Liu, H. Fujisawa, Classification and learning in character recognition: Advances and remaining problems, In: Machine Learning in Document Analysis and Recognition, S. Marinai and H. Fujisawa (Eds.), Springer, 2008, pp.139-161.
• C.-L. Liu, Handwritten Chinese character recognition: Effects of shape normalization and feature extraction, In: Arabic and Chinese Handwriting Recognition, S. Jaeger and D. Doermann (Eds.), LNCS Vol.4768, Springer, 2008, pp.104-128.
• C.-L. Liu, Partial discriminative training of neural networks for classification of overlapping classes, Artificial Neural Networks in Pattern Recognition: Third IAPR Workshop, Paris, France, 2008, LNAI 5064, Springer, pp.137-146.
• X.-H. Liu, C.-L. Liu, X. Hou, A pooled subspace mixture density model for pattern classification in high-dimensional spaces, Proc. IJCNN 2008, Hong Kong, pp.2467-2472.
• C.-L. Liu, C.Y. Suen, A new benchmark on the recognition of handwritten Bangla and Farsi numeral characters, Proc. 11th ICFHR, Montreal, Canada, Aug. 2008, pp.278-283.
• F. Yin, C.-L. Liu, Handwritten text line segmentation by clustering with distance metric learning, Proc. 11th ICFHR, Montreal, Canada, Aug. 2008, p.229-234.
• X.-D. Zhou, D.-H. Wang, C.-L. Liu, Grouping text lines in online handwritten Japanese documents by combining temporal and spatial information, Proc. 8th IAPR Int. Workshop on DAS, Nara, Japan, Sep. 2008.
• Y.-F. Pan, X. Hou, C.-L. Liu, A robust system to detect and localize texts in natural scene images, Proc. 8th IAPR Int. Workshop on DAS, Nara, Japan, Sep. 2008.
• L. Ma, C.-L. Liu, A new radical-based to online handwritten Chinese character recognition, Proc. 19th ICPR, Tampa, USA, 2008.
• X. Jin, C.-L. Liu, X. Hou, Prototype learning by margin-based conditional log-likelihood loss, Proc. 19th ICPR, Tampa, USA, 2008.
• T.-F. Gao, C.-L. Liu, Combining quadratic classifier and pair discriminators by pairwise coupling for handwritten chinese character recognition, Proc. 19th ICPR, Tampa, USA, 2008.

• M. Cheriet, N. Kharma, C.-L. Liu, C.Y. Suen, Character Recognition Systems: A Guide for Students and Practitioners, John Wiley & Sons (Book's Page), 2007.
• C.-L. Liu, Normalization-cooperated gradient feature extraction for handwritten character recognition, IEEE Trans. Pattern Analysis and Machine Intelligence, 29(8): 1465-1469, 2007.
• 刘成林、谭铁牛，模式识别研究进展，中国计算机学会通讯，2007年12期，45-52.
• R. Dai, C. Liu, B. Xiao, Chinese character recognition: history, status and prospects, Frontiers of Computer Science in China, 1(2): 126-136, 2007.
• S. Andra, G. Nagy, C.-L. Liu, Frequency coding: An effective method for combining dichotomizers, Document Recognition and Retrieval XIV, San Jose, CA, Jan. 31-Feb. 1, Proceedings of SPIE, Vol.6500, 2007.
• T.-F. Gao, C.-L. Liu, LDA-based compound distance for handwritten Chinese character recognition, In: Proc. 9th ICDAR, Curitiba, Brazil, 2007.
• X.-D. Zhou, C.-L. Liu, Text/non-text ink stroke classification in Japanese handwriting based on Markov random fields, In: Proc. 9th ICDAR, Curitiba, Brazil, 2007.
• X.-D. Zhou, J.-L. Yu, C.-L. Liu, T. Nagasaki, K. Marukawa, Online handwritten Japanese character string recognition incorporating geometric context, In: Proc. 9th ICDAR, Curitiba, Brazil, 2007.
• S. Wang, C.-L. Liu, L. Zheng, Feature selection by combining Fisher criterion and principal feature analysis, In: Proc. ICMLC 2007, Hong Kong, pp.1149-1154.
• F. Yin, C.-L. Liu, Handwritten text line extraction by minimum spanning tree clustering, In: Proc. Int. Conf. on Wavelet Analysis and Pattern Recognition, Beijing, 2007.
• X. Jin, X. Hou, C.-L. Liu, A hybrid generative-discriminative learning algorithm for Bayesian network structure, In: Proc. Int. Conf. on Wavelet Analysis and Pattern Recognition, Beijing, 2007.

• X. Hou, C.-L. Liu, T. Tan, Learning boosted asymmetric classifiers for object detection, Proc. CVPR 2006, New York, Vol.1, pp.330-338.
• C.-L. Liu, High accuracy handwritten Chinese character recognition using quadratic classifiers with discriminative feature extraction, Proc. 18th ICPR, Hong Kong, 2006, Vol.2, pp.942-945.
• C.-L. Liu, Polynomial network classifier with discriminative feature extraction, Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR Int. Workshops, D.-Y. Yeung et al (Eds.), LNCS Vol.4109, Springer, 2006, pp.732-740.
• C.-L. Liu, X.-D. Zhou, Online Japanese character recognition using trajectory-based normalization and direction feature extraction, Proc. 10th IWFHR, France, 2006.
• C.-L. Liu, Handwritten Chinese character recognition: effects of shape normalization and feature extraction, Summit on Arabic and Chinese Handwriting Recognition (SACH06), University of Maryland, College Park, MD, 2006 (Invited talk).

• C.-L. Liu, H. Fujisawa, Classification and learning in character recognition: comparison of methods and remaining problems, Proc. Int. Workshop on Neural Networks a d Learning in Document Analysis and Recognition, Seoul, Korea, August, 2005.

• To be posted.

Location: Room 1115 Time: Monday every week

Lecturer Order

• 黄亮
• 白博
• 许亮
• 王秋锋
• 王大寒
• 王恒
• 张煦尧
• 张恒
• 陆安
• 陈雪云
• 刘颖璐 陈凯
• 杨沛沛
• 周明可 王冬冬
• 杨杰 钟子沙

Machine Learning Progress Seminar(MLP Seminar 2006~2007)

Reading Group on Pattern Recognition and Machine Learning(Since 2009)

Machine Learning Reading Group(Since 2010)

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— JIN Xiaobo 2009/06/05 12:48