June 6th, 2012 |
Posted by Osman Eralp |
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This guide describes how to install and configure OpenCV 2.4.2 and its dependencies on Ubuntu 12.04. This guide includes instructions for both 32-bit and 64-bit systems.
Revision History:
[] Updated guide to work with OpenCV 2.4.2. Updated ffmpeg section: ffmpeg 0.11.1 now requires -pic option on 64-bit systems.
[] Updated guide to work with OpenCV 2.4.1 and Ubuntu 12.04. Added instructions for 64-bit systems.
[] Initial version. Worked with OpenCV 2.3.1 and Ubuntu 11.10. Archived .
If you need help troubleshooting OpenCV installation problems, see the companion guide “.”
The Installation Procedure
To install and configure OpenCV 2.4.1, complete the following steps. The commands shown in each step can be copy and pasted directly into a Linux command line.
Remove any installed versions of ffmpeg and x264.
sudo apt-get remove ffmpeg x264 libx264-dev
Get all the dependencies for x264 and ffmpeg.
sudo apt-get update
sudo apt-get install build-essential checkinstall git cmake libfaac-dev libjack-jackd2-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libsdl1.2-dev libtheora-dev libva-dev libvdpau-dev libvorbis-dev libx11-dev libxfixes-dev libxvidcore-dev texi2html yasm zlib1g-dev
Download and install gstreamer.
sudo apt-get install libgstreamer0.10-0 libgstreamer0.10-dev gstreamer0.10-tools gstreamer0.10-plugins-base libgstreamer-plugins-base0.10-dev gstreamer0.10-plugins-good gstreamer0.10-plugins-ugly gstreamer0.10-plugins-bad gstreamer0.10-ffmpeg
Download and install gtk.
sudo apt-get install libgtk2.0-0 libgtk2.0-dev
Download and install libjpeg.
sudo apt-get install libjpeg8 libjpeg8-dev
Create a directory to hold source code.
Download and install install x264.
Download a recent stable snapshot of x264 from . The exact version does not seem to matter. To write this guide, I used version x264-snapshot-5-stable.tar.bz2, but I have used previous versions too.
wget ftp://ftp.videolan.org/pub/videolan/x264/snapshots/x264-snapshot-5-stable.tar.bz2
tar xvf x264-snapshot-5-stable.tar.bz2
cd x264-snapshot-5-stable
Configure and build the x264 libraries.
./configure --enable-static
sudo make install
IMPORTANT: If you are running a 64-bit version of Ubuntu, you must configure x264 as shown in the following command:
./configure --enable-shared --enable-pic
The -shared and -pic options might also be required when you compile for some other architectures, such as ARM. You know you need these options if you get the following error when compiling OpenCV:
[ 25%] Building CXX object modules/highgui/CMakeFiles/opencv_highgui.dir/src/bitstrm.cpp.o
Linking CXX shared library ../../lib/libopencv_highgui.so
/usr/bin/ld: /usr/local/lib/libavcodec.a(avpacket.o): relocation R_X86_64_32S against `av_destruct_packet' can not be used when ma recompile with -fPIC
/usr/local/lib/libavcodec.a: could not read symbols: Bad value
Download and install install ffmpeg.
Download ffmpeg version 0.11.1 from .
wget http://ffmpeg.org/releases/ffmpeg-0.11.1.tar.bz2
tar xvf ffmpeg-0.11.1.tar.bz2
cd ffmpeg-0.11.1
Configure and build ffmpeg.
./configure --enable-gpl --enable-libfaac --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libtheora --enable-libvorbis --enable-libx264 --enable-libxvid --enable-nonfree --enable-postproc --enable-version3 --enable-x11grab
sudo make install
IMPORTANT: Just like with x264 in the previous step, you must configure ffmpeg with the -shared and -pic options if you are running a 64-bit version of Ubuntu or some other architectures, such as ARM.
./configure --enable-gpl --enable-libfaac --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libtheora --enable-libvorbis --enable-libx264 --enable-libxvid --enable-nonfree --enable-postproc --enable-version3 --enable-x11grab --enable-shared --enable-pic
Download and install install a recent version of v4l (video for linux) from . For this guide I used version 0.8.8.
wget http://www.linuxtv.org/downloads/v4l-utils/v4l-utils-0.8.8.tar.bz2
tar xvf v4l-utils-0.8.8.tar.bz2
cd v4l-utils-0.8.8
sudo make install
Download and install install OpenCV 2.4.2.
Download OpenCV version 2.4.2 from
wget http://downloads.sourceforge.net/project/opencvlibrary/opencv-unix/2.4.2/OpenCV-2.4.2.tar.bz2
tar xvf OpenCV-2.4.2.tar.bz2
Create a new build directory and run cmake:
cd OpenCV-2.4.2/
mkdir build
cmake -D CMAKE_BUILD_TYPE=RELEASE ..
Verify that the output of cmake includes the following text:
found gstreamer-base-0.10
GTK+ 2.x: YES
FFMPEG: YES
GStreamer: YES
V4L/V4L2: Using libv4l
Build and install OpenCV.
sudo make install
Configure Linux.
Tell linux where the shared libraries for OpenCV are located by entering the following shell command:
export LD_LIBRARY_PATH=/usr/local/lib
Add the command to your .bashrc file so that you don’t have to enter every time your start a new terminal.
Alternatively, you can configure the system wide library search path. Using your favorite editor, add a single line containing the text /usr/local/lib to the end of a file named /etc/ld.so.conf.d/opencv.conf. In the standard Ubuntu install, the opencv.conf you need to create it. Using vi, for example, enter the following commands:
sudo vi /etc/ld.so.conf.d/opencv.conf
/usr/local/lib
After editing the opencv.conf file, enter the following command:
sudo ldconfig /etc/ld.so.conf
Using your favorite editor, add the following two lines to the end of /etc/bash.bashrc:
PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
export PKG_CONFIG_PATH
After completing the previous steps, your system should be ready to compile code that uses the OpenCV libraries. The following example shows one way to compile code for OpenCV:
g++ `pkg-config opencv --cflags` my_code.cpp
-o my_code `pkg-config opencv --libs`
More Information
If you encounter problems installing OpenCV, see the companion guide, “.”
Utkarsh Sinha runs AiShack, a site that has easy-to-understand tutorials using OpenCV to solve real-world problems:
Sebastian Montabone has several articles on installing OpenCV and image processing. His web site is
FakeOutdoorsman’s posted an excellent dependency install guide, which is located on the Ubuntu forums:
CategoriesDr. Zhouchen
Lin is a Professor in Department of Machine Intelligence, School of
Electronics Engineering and Computer Science, Peking University.
I am now recruiting
Ph.D.s who have
strong mathematical abilities (however, this does not imply that you
have to come from mathematics department) in order to enjoy with me how to use
mathematics to solve real problems elegantly. I am also recruiting Masters who have
strong coding skills and interests in Quantitative Trading. Welcome to send me (zlin (at) pku (dot) edu (dot) cn) your detailed resume as early as possible!
is more practical than a good theory. ---- V. Vapnik
What I am most fond of are beautiful and simple theoretical ideas that can be translated into something that works. ---- Y. LeCun
1. Call for papers: International Conf. Big Data and Information Analytics (BigDIA) 2016
2. I was invited to be a senior program committee member (= area chair) of AAAI 2017.
3. Our joint WM team won the first place
in the ILSVRC 2015 Scene Classification Challenge (the five submissions won the top five places)! ()[]
4. A new journal of American Institute of Mathematical Sciences,
(I am its Executive Editor) welcomes high-quality submissions!
Curriculum Vitae:
April 2002 - Aug. 2004:
Researcher
Multi-Modal User
Interface Group, Microsoft Research, Asia
Digital Ink, Digital
Pen, Pattern Recognition, Machine Learning, Document Processing/Analysis,
Biometrics, Numerical Computation, Coding Theory, Security
July 2000 - March 2002:
Associate Researcher
Visual Computing
Group,& Microsoft Research, China
Computer Vision and
Computer Graphics
April 1999 - Dec. 1999:
Visual Computing
Group,& Microsoft Research, China
Computer Vision and Computer
Sept. 1997 - July 2000:
Doctoral Candidate
of Mathematics, Peking University
Image Processing,
Computer Vision, Pattern Recognition
Sept. 1995 - Aug. 1997:
Master Candidate
Dept. of Applied Mathematics,
Hong Kong Polytechnic University
Computation/Simulation
Sept. 1993 - Aug. 1995:
Master Candidate
Dept. of Mathematics,
Peking University
Image Processing, Image
Sept. 1989 - Aug. 1993:
Bachelor Candidate
&Mathematics, Nankai University
Pure Mathematics
Research Areas:
Computer Vision,
Image Processing, Machine Learning, Numerical Computation and Optimization,
Computer Graphics, Pattern Recognition
Book Chapters:
1. Liang Wan and
Zhouchen Lin, Signature Sample
Synthesis, Encyclopedia of Biometrics (Stan Z. Li (Ed.)), pp. ,
Springer, August 27, 2009. []
2. Zhouchen
Lin, Learning-Based Image
Superresolution Algorithms (in Chinese), Machine Learning and Applications
2009 (Z. Zhou and J. Wang (Ed.)), Tsinghua University Press, Nov. 2009. [pdf]
3. Wei Feng,
Liang Wan, Zhouchen Lin, Tien-Tsin Wong, Zhi-Qiang Liu, Perceptual Thumbnail Generation, Perceptual
Digital Imaging: Methods and Applications (Rastislav Lukac (Ed.)), CRC Press,
Oct. 29, 2012. []
4. Zhouchen
Lin, Rank Minimization: Theories, Algorithms, and Applications (in Chinese), Machine Learning and Applications
2013 (C. Zhang and Z. Zhou (Ed.)), Tsinghua University Press, Oct. 2013. []
5. Zhouchen
Lin and Yi Ma, Low-Rank Models in Signal and Data Processing: Theories, Algorithms, and Applications (in Chinese), Communications of China Computer Federation, 2015. []
6. Zhouchen
Lin, Wei Zhang, Learning Partial Differential Equations for Computer Vision, Proc. of the third , Higher Education Press, to appear. []
Journal Papers:
85. Fanhua Shang, Yuanyuan Liu, James Cheng, Zhi-Quan Luo, and Zhouchen Lin, Double Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications, submitted to IEEE Trans. Pattern Analysis and Machine Intelligence.
84. Yisong Chen, Antoni B. Chan, Zhouchen Lin, and Kenji Suzuki, Efficient Tree-structured SfM by RANSAC Generalized Procrustes Analysis, submitted to Computer Vision and Image Understanding.
83. Jia Li, Chenyan Bai, Zhouchen Lin, and Jian Yu, Automatic
Design of High-Sensitivity Color Filter Arrays with Panchromatic Pixels, submitted to IEEE Trans. Image Processing.
82. Yang Lin, Zhouchen Lin, and Hongbin Zha, The Shape Interaction Matrix Based Affine Invariant Mismatch Removal for Partial Duplicated Image Search, submitted to IEEE Trans. Image Processing.
81. Pan Zhou, Fang Cong, Zhouchen Lin, Chao Zhang, and Edward Chang, Dictionary Learning with Structured Noise, submitted to Neurocomputing.
80. Cong Fang, Zhenyu Zhao, Pan Zhou, and Zhouchen Lin, Feature Learning via Partial Differential Equation with Applications to Face Recognition, submitted to Pattern Recognition.
79. Zhouchen Lin, Canyi Lu, and Huan Li, Optimized Projections for Compressed Sensing via Direct Mutual Coherence Minimization, submitted to IEEE Trans. Information Theory, major revision.
78. Jia Li, Chenyan Bai, Zhouchen Lin, and Jian Yu, Ammann-Beenker Pixels , submitted to IET Image Processing.
77. Zhouchen Lin, Pan Zhou,and Chao Zhang, Bilevel Model Based Discriminative Dictionary Learning for Recognition, submitted to IEEE Trans. Image Processing.
76. Jianlong Wu, Zhouchen Lin, Wenming Zheng, and Hongbin Zha, Locality-constrained Linear Coding Based Bi-layer Model for Multi-view Facial Expression Recognition, submitted to Neurocomputing.
75. Zhouchen Lin, Chen Xu,and Hongbin Zha, Robust Matrix Factorization by Majorization-Minimization, submitted to IEEE Trans. Pattern Analysis and Machine Intelligence, major revision.
74. Chunyu Wang, Yizhou Wang, Zhouchen Lin, and Alan Yuille, Robust 3D Human Pose Estimation from a Single Image or a Video Sequence, submitted to IEEE Trans. Pattern Analysis and Machine Intelligence, major revision.
73. Li Yang, Yang Lin, Zhouchen Lin, Tong Lin, and Hongbin Zha, Factorization for Projective and Metric Reconstruction via Weighted Nuclear Norm Minimization, submitted to Neurocomputing.
72. Jinshan Pan, Risheng Liu, Zhixun Su, and Zhouchen Lin, Robust Kernel Estimation for Blind Deblurring with Severe Outliers, submitted to IEEE Trans. Image Processing.
Jinshan Pan, Zhixun
Su, Risheng Liu, Zhouchen Lin, and Yu Cai, Blind Image Deblurring via
Salient Structure Detection and Sparse Representation, submitted to Image and Vision Computing.
70. Wenming
Zheng, Hao Tang, Zhouchen Lin, and Thomas Huang, Emotion Recognition from Arbitrary View Facial Expression Images,
submitted to IEEE Trans. Neural Networks and Learning Systems.
69. Jia Li, Chenyan Bai, Zhouchen Lin, and Jian Yu, Penrose High Dynamic Range Imaging, J. Electronic Imaging, aceepted.
68. Hongyang Zhang, Zhouchen Lin, and Chao Zhang, Completing Low-Rank Matrices with Corrupted Samples from Few Coefficients in General Basis, IEEE Trans. Information Theory, accepted. []
67. Yifan Fu, Junbin Gao, David Tien, Zhouchen Lin, and Xia Hong, Tensor LRR and Sparse Coding Based Subspace Clustering,
IEEE Trans. Neural Networks and Learning Systems, accepted. []
66. Canyi Lu, Shuicheng Yan, and Zhouchen Lin, Convex Sparse Spectral Clustering: Single-view to Multi-view, IEEE Trans. Image Processing, accepted. []
65. Qi Li, Zhenan Sun, Zhouchen Lin, Ran He, and Tieniu Tan, Transformation Invariant Subspace Clustering, Pattern Recognition, accepted. []
64. Risheng Liu, Guangyu Zhong, Junjie Cao, Zhouchen Lin, Shiguang Shan, and Zhongxuan Luo, Learning to Diffuse: A New Perspective to Design PDEs for Visual Analysis, submitted to IEEE Trans. Pattern Analysis and Machine Intelligence, accepted. []
63. Zhouchen Lin, A Review on Low-Rank Models in Signal and Data Analysis, Big Data and Information Analytics, accepted. []
62. Zhenyu Zhao, Zhouchen Lin, and Yi Wu, A Fast Alternating Time-Splitting Approach for Learning Partial Differential Equations, Neurocomputing, Vol. 185, pp. 171-182, 2016. []
61. Zhouchen Lin and Yameng Huang, Fast Multidimensional Ellipsoid-Specific Fitting by Alternating Direction Method of Multipliers, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 38, No. 5, pp. , 2016. []
60. Pan Zhou, Zhouchen Lin, and Chao Zhang, Integrated Low Rank Based Discriminative Feature Learning for Recognition, IEEE Trans. Neural Networks and Learning Systems, Vol. 27, No. 5, pp. , 2016. [].
Chenyan Bai, Jia Li, Zhouchen Lin, and Jian Yu, Automatic Design of Color Filter Arrays in the Frequency Domain, IEEE Trans. Image Processing, Vol. 25, No.4, pp. , 2016. [][].
58. Canyi Lu, Jinhui Tang, Shuicheng Yan, and Zhouchen Lin, Nonconvex Nonsmooth Low-Rank Minimization via Iteratively Reweighted Nuclear Norm, IEEE Trans. Image Processing, Vol. 25, No. 2, pp. 829-839, 2016. []
57. Liansheng Zhuang, Jingjing Wang, Zhouchen Lin, Allen Yang, Yi Ma, and Nenghai Yu, Locality-Preserving Low-Rank Representation for Graph Construction from Nonlinear Manifolds, Neurocomputing, Vol. 175, pp. 715-722, 2016. []
56. Ming Yin, Junbin Gao, Zhouchen Lin, Laplacian Regularized Low-Rank Representation and Its Applications, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 38, No. 3, pp. 504-517, 2016. [][]
55. Zhenyu Zhao, Cong Fang, Zhouchen Lin, and Yi Wu, A
Robust Hybrid Method for Text Detection in Natural Scenes by Learning-based
Partial Differential Equations, Neurocomputing, Vol. 168, pp. 23-34, 2015. []
54. Jianjun Qian, Lei Luo, Jian Yang, Fanglong Zhang, and Zhouchen Lin, Robust Low-Rank Regularized Regression for Face Recognition with Occlusion,
Pattern Recognition, Vol. 48, No. 10, pp. , 2015. []
53. Ming Yin, Junbin Gao, Zhouchen Lin, Qinfeng Shi, and Yi Guo, Dual Graph Regularized Latent Low-rank Representation for Subspace Clustering, IEEE Trans. Image Processing, Vol. 24. No. 12, pp. , 2015. []
52. Liansheng Zhuang, Jingjing Wang, Shenghua Gao, Zhouchen Lin, Yi Ma, Tianzhu Zhuang, and Nenghai Yu, Constructing a Nonnegative Low-Rank and Sparse Graph With Data-Adaptive Features,
IEEE Trans. Image Processing, Vol. 24, No. 11, pp. , 2015. []
51. Hongyang Zhang, Zhouchen Lin, Chao Zhang, and Junbin Gao, Relation among Some Low Rank Subspace Recovery Models, Neural Computation, Vol. 27, No. 9, pp. , 2015. []
50. Li Shen, Gang Sun, Qingming Huang, Shuhui Wang, Zhouchen Lin, and Enhua Wu, Multi-Level Discriminative Dictionary Learning With Application to Large Scale Image Classification, IEEE Trans. Image Processing, Vol. 24, No. 10, pp. , 2015. []
49. Chenyan Bai, Jia Li, Zhouchen Lin, Jian Yu, and Yen-wei Chen, Penrose Demosaicking, IEEE Trans. Image Processing, Vol. 24, No. 5, pp. , May, 2015. []
48. Canyi Lu, Zhouchen Lin, and Shuicheng Yan, Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squared Minimization, IEEE Trans. Image Processing, Vol. 24, No. 2, pp. 646-654, 2015. []
47. Zhouchen Lin, Risheng Liu, and Huan Li, Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning,
Machine Learning (Special Issue for ACML2013), Vol. 99, No. 2, pp. 287-325, 2015 (arXiv: ). []
46. Hongyang Zhang, Zhouchen Lin, Chao Zhang, and Junbin Gao, Robust Latent Low Rank Representation for Subspace Clustering, Neurocomputing, Vol. 145, pp. 369-373, December 2014. [][]
45. Risheng
Liu, Zhouchen Lin, Zhixun Su, and Junbin Gao, Linear time Principal Component Pursuit and its extensions using l1 Filtering, Neurocomputing, Vol. 142, pp. 529-541, 2014. [](arXiv: )[]
44. Risheng
Liu, Zhouchen Lin, and Zhixun Su, Learning
Markov Random Walks for Robust Subspace Clustering and Estimation,
Neural Networks, Vol. 59, pp. 1-15, 2014. []
Mingyu Fan, Xiaoqin
Zhang, Zhouchen Lin, Zhongfei Zhang, and Hujun Bao, A Regularized Approach for Geodesic Based Semi-Supervised Multi-Manifold Learning,
IEEE Trans. Image Processing, Vol. 23, No. 5, pp. , May 2014. []
42. Wenming
Zheng, Zhouchen Lin, and Haixian Wang, L1-Norm Kernel Discriminant Analysis via Bayes
Error Bound Optimization for Robust Feature Extraction, IEEE Trans.
Neural Networks and Learning Systems, Vol. 25, No. 4, pp. 793-805, April 2014.
41. Xin Zhang, Zhouchen Lin, Fuchun Sun, and Yi Ma, Transform Invariant Text Extraction, The Visual Computer, Vol. 30, No. 4, pp. 401-415, April 2014. []
40. Liansheng Zhuang, Haoyuan Gao, Jiebo Luo, Zhouchen Lin, Regularized Semi-Supervised Latent Dirichlet Allocation for Visual Concept Learning, Neurocomputing, Vol. 119, pp. 26-32, Nov. 7, 2013. []
Qin Lyu, Zhouchen
Lin, Yiyuan She, and Chao Zhang, A Comparison of Typical lp Minimization Algorithms,
Neurocomputing, Vol. 119, pp. 413-424, 2013. []
38. Chunguang
Li, Zhouchen Lin, and Jun Guo, Bases Sorting: Generalizing the Concept of Frequency
for Over-complete Dictionaries, Neurocomputing, Vol. 115, pp. 192-200, Sept. 2013. []
Ren and Zhouchen Lin, Linearized
Alternating Direction Method with Adaptive Penalty and Warm Starts for Fast
Solving Transform Invariant Low-Rank Textures, International
J. Computer Vision, Vol. 104, pp. 1-14, 2013. [][]
36. Risheng
Liu, Zhouchen Lin, Wei Zhang, Kewei Tang, and Zhixun Su, Toward Designing Intelligent PDEs for Computer
Vision: An
Optimal Control Approach, Image and Vision
Computing, Vol. 31, No. 1,
pp. 43C56, 2013.
35. Dongwei
Ren, Wangmeng Zuo, Xiaofei Zhao, Zhouchen Lin, David Zhang, Fast
Gradient Vector Flow Computation Based on Augmented Lagrangian Method, Pattern Recognition Letters, vol. 34, no. 2, pp. 219-225, 2013.
34. Guangcan Liu, Zhouchen
Lin, Shuicheng Yan, Ju Sun, and Yi Ma, Robust
Recovery of Subspace Structures by Low-Rank Representation, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 35, no. 1, pp. 171-184, 2013.
33. Wenming Zheng and Zhouchen
Lin, A New Discriminant Subspace
Analysis Approach for Multi-Class Problems, Pattern Recognition, vol. 45, no. 4, pp. ,
April 2012.[]
32. Wangmeng Zuo and Zhouchen
Lin, A Generalized Accelerated
Proximal Gradient Approach for Total Variation-Based Image Restoration,
IEEE Trans. Image Processing, vol. 20, no. 10, pp. , Oct. 2011. [pdf][code]
31. Moshe Ben-Ezra, Zhouchen
Lin, Bennett Wilburn, and Wei Zhang, Penrose
Pixels for Super-Resolution, IEEE Trans. Pattern Analysis and Machine
Intelligence, vol. 33, no. 7, pp. , July 2011. [pdf]
30. Pengwei Hao, Yan Li, Zhouchen
Lin, and E. Dubois, A Geometric
Method for Optimal Design of Color Filter Arrays, IEEE Trans. Image
Processing, vol. 20, no. 3, pp. 709-722, 2011. [pdf]
29. Yan Li, Pengwei Hao,
and Zhouchen Lin, The Frequency
Structure Matrix: A Representation of Color Filter Arrays, International
Journal of Imaging Systems and Technology, vol. 21, pp. 101-106, 2011. [pdf]
Zhang, Zhouchen Lin, and Xiaoou Tang, Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction, IEEE
Trans. Knowledge Discovery and Engineering, vol. 23, no. 4, pp. 600-611, 2011. [pdf]
Risheng Liu, Zhouchen Lin, Zhixun Su, and Kewei Tang, Feature Extraction by Learning Lorentzian
Metric Tensor and Its Extensions, Pattern Recognition, Vol. 43, No. 10, pp.
, October 2010.& [pdf]
26. Wenming Zheng, Zhouchen
and Xiaoou Tang, A Rank-One Update Algorithm for
Fast Solving Kernel Foley-Sammon Optimal Discriminant Vectors, IEEE Trans. Neural
Networks, Vol. 21, No. 3, pp. 393-403, March 2010. [pdf]
25. Guangcan Liu, Zhouchen
Lin, Xiaoou Tang, and Yong Yu, Unsupervised
Object Segmentation with a Hybrid Graph Model, IEEE Trans. Pattern Analysis
and Machine Intelligence, Vol. 32, No. 5, pp. 910-924, May 2010. []
Jiaping Wang, Yue Dong, Xin Tong, Zhouchen Lin, and Baining Guo, Kernel Nystr&m Method for Light
Transport, Siggraph 2009, ACM Trans. on Graphics,
Vol. 28, No. 3, August 2009. []
23. Guangcan Liu, Zhouchen
Lin, and Yong Yu, Multi-Output
Regression on the Output Manifold, Pattern Recognition, Vol. 42, No. 11,
pp. , 2009. []
22. Guangcan Liu, Zhouchen
Lin, and Yong Yu, Radon
Representation Based Feature Descriptor for Texture Classification, IEEE
Trans. Image Processing, Vol. 18, No. 5, pp. 921-928, 2009. [pdf]
21. Wei Zhang, Zhouchen
Lin, and Xiaoou Tang, Tensor Linear
Laplacian Discrimination (TLLD) for Feature Extraction, Pattern
Recognition, Vol. 42, No. 9, pp. , 2009. [pdf]
20. John Wright, Yangyu
Tao, Zhouchen Lin, Yi Ma, and Heung-Yeung Shum, Classification via Minimum Incremental Coding Length, SIAM Journal
on Imaging Science, Vol. 2, No. 2, pp. 367-395, 2009. [pdf]
19. Zhouchen Lin,
Junfeng He, Xiaoou Tang, and Chi-Keung Tang, Fast, Automatic and Fine-Grained Tampered JPEG Images Detection via DCT
Coefficient Analysis, Pattern Recognition, Vol. 42, No. 11, pp. ,
18. Zhouchen Lin,
Junfeng He, Xiaoou Tang, and Chi-Keung Tang, Limits of Learning-Based Superresolution Algorithms, International
Journal of Computer Vision, Vol. 80, No. 3, pp. 406-420, 2008. [pdf]
17. Liang Wan, Wei Feng, Zhouchen
Lin, Tien-Tsin Wong, and Zhi-Qiang Liu, Perceptual
Image Preview, Multimedia Systems Journal, Vol. 14, No. 4, pp. 195-204,
September 2008. []
16. Jiaping Wang, Shuang
Zhao, Xin Tong, Stephen Lin, Zhouchen Lin, Yue Dong, Baining Guo, and
Heung-Yeung Shum, Modeling and Rendering
of Heterogeneous Translucent Materials Using the Diffusion Equation, ACM
Trans. on Graphics, Vol.27, No. 1, pp. 1-18, 2008. [pdf]
15. Zhouchen Lin,
Lifeng Wang, Yunbo Wang, Singbing Kang, and Tian Fang, High Resolution Animated Scenes from Stills, IEEE Trans.
Visualization and Computer Graphics, Vol. 13, No. 3, pp. 562-568, 2007. [pdf]
14. Zhouchen Lin
and Liang Wan, Style-Preserving
Handwriting Synthesis, Pattern Recognition, Vol. 40, No. 7, pp. ,
13. Zhouchen Lin,
Rongrong Wang, and Heung-Yeung Shum, Rule-Based Cleanup of On-line English
Ink Notes, Pattern Recognition, Vol. 39, No. 6,
pp. , June 2006. []
12. Zhouchen Lin,
Junfeng He, Zhicheng Zhong, Rongrong Wang, and Heung-Yeung Shum, Table
Detection in Online Ink Notes, IEEE Trans. on Pattern Analysis and Machine
Intelligence, Vol. 28, No. 8, pp. , August 2006. [pdf]
11. Zhouchen Lin
and Heung-Yeung Shum, Response to Comments on Fundamental Limits of
Reconstruction-Based Superresolution Algorithms under Local Translation,
IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 28, No. 5, p.
847, May 2006.
10. Zhouchen Lin,
Hai-Tao Chen, Heung-Yeung Shum, and Jian Wang, Pre-filtering 2D Polygons
without Clipping, Journal of Graphics Tools, 10(1):17-26, 2005. [pdf]
9. Zhouchen Lin,
Hai-Tao Chen, Heung-Yeung Shum, and Jian Wang, Optimal Polynomial Filters,
Journal of Graphics Tools, 10(1):27-38, 2005. [pdf]
8. Zhouchen Lin
and Heung-Yeung Shum, A Geometric Analysis of Light Field Rendering,
International J. of Computer Vision, Vol. 58, No. 2, pp. 121-138, July 2004. [pdf]
7. Zhouchen Lin
and Heung-Yeung Shum, Fundamental Limits of Reconstruction-Based Superresolution
Algorithms under Local Translation, IEEE Trans. Pattern Analysis and
Machine Intelligence, Vol. 26, No. 1, pp. 83-97, 2004. [pdf]
6. Ke Deng, Lifeng Wang, Zhouchen
Lin, Tao Feng, and Zhidong Deng, Correction and Rectification of Light
Fields, Computers & Graphics, Vol. 27, No. 2, pp. 169-177, 2003. [pdf]
5. Zhouchen Lin,
Tien-Tsin Wong, Heung-Yeung Shum, Relighting with the Reflected Irradiance
Field: Representation, Sampling and Reconstruction, International J. of
Computer Vision, Vol. 49, No. 2/3, pp. 229-246, Sept. 2002. [pdf]
4. 林宙辰，石青云，用四次多项式插值消除医用X射线CT中的金属伪影，(Reduction of Metal
Artifact in X-ray CT using Quartic-Polynomial Interpolation), &Journal
of Image and Graphics (中国图象图形学报), Vol. 6, no. 2, pp. 142-147, 2001.
3. 林宙辰，石青云，一个能去噪和保持真实感的各向异性扩散方程, (Anisotropic Diffusion
Equation that Can Remove Noise and Keep Naturalness), Chinese Journal of
Computers (计算机学报),
Vol.22, No.11, pp., 1999.
2. 林宙辰，石青云，用二进小波消除磁共振图像中的振铃效应，(Using Dyadic Wavelets
to Reduce the Ringing Artifacts in NMR Images), Pattern Recognition and
Artificial Intelligence (模式识别与人工智能)，Vol.12, No.3, pp.320-324
1. Zhouchen Lin,
Tsai-Man Shih, Mathematical Optimal Control Models of Continuous Casting,
Mathematica Applicata (应用数学), Vol. 11, No. 1, pp. 119-127, 1998.
Refereed Conference Papers:
71. Four paper submitted to NIPS 2016.
70. One paper submitted to ECCV 2016.
69. Yuqing Hou, Zhouchen Lin, and Jinge Yao. Subspace Clustering Based Tag Sharing for Inductive Tag
Matrix Refinement with Complex Errors, SIGIR 2016. []
68. Canyi Lu, Jiashi Feng, Yudong chen, Wei Liu, Zhouchen Lin, and Shuicheng Yan, Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization, CVPR 2016. []
67. Jinshan Pan, Zhouchen Lin, Zhixun Su, and Ming-Hsuan Yang, Robust Kernel Estimation with Outliers Handling for Image Deblurring, CVPR 2016. []
66. Canyi Lu, Huan Li, Zhouchen Lin, and Shuicheng Yan, Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting, pp. 739-745, AAAI 2016. [][]
65. Chen Xu, Zhouchen Lin, and Hongbin Zha, Relaxed
Majorization-Minimization for Non-smooth and Non-convex Optimization, pp. 812-818, AAAI 2016. []
64. Jianlong Wu, Zhouchen Lin, and Hongbin Zha, Multiple Models Fusion for Emotion Recognition in the
Wild, ICMI 2015. []
63. Yuqing Hou and Zhouchen Lin, Image Tag Completion and Refinement by Subspace Clustering and Matrix Completion,
VCIP2015. []
62. Huan Li and Zhouchen Lin, Accelerated Proximal Gradient Methods for Nonconvex Programming, NIPS2015. [][][]
61. Chunguang Li, Zhouchen Lin, Honggang Zhang, and Jun Guo, Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning, ICCV2015. []
60. Zhizhong Li, Deli Zhao, Zhouchen Lin, Edward Y. Chang, Determining Step Sizes in Geometric Optimization Algorithms, International Symposium on Information Theory (ISIT), 2015. []
59. Li Shen, Gang Sun, Zhouchen Lin, Qingming Huang, and Enhua Wu, Adaptive Sharing for Image Classification, IJCAI 2015, pp. . []
58. Baohua Li, Ying Zhang, Zhouchen Lin, and Huchuan Lu, Subspace Clustering by Mixture of Gaussian Regression, CVPR 2015. []
57. Zhizhong Li, Deli Zhao, Zhouchen Lin,
and Edward Chang, A New Retraction for Accelerating the Riemannian Three-Factor Low-Rank Matrix Completion Algorithm, CVPR 2015. []
56. Canyi Lu, Changbo Zhu, Chunyan Xu, Shuicheng Yan, and Zhouchen Lin, Generalized Singular Value Thresholding,
AAAI2015, pp. . [][]
55. Hongyang Zhang, Zhouchen Lin, Chao Zhang, and Edward Chang, Exact Recoverability of Robust PCA via Outlier Pursuit with Tight Recovery Bounds, AAAI2015, pp. . [][]
54. Yang Lin, Chen Xu, Li Yang, Zhouchen Lin, and Hongbin Zha, L1-Norm Global Geometric Consistency for Partial-Duplicate Image Retrieval, ICIP2014, pp. . []
53. Li Yang, Yang Lin, Zhouchen Lin, and Hongbin Zha, Low Rank Global Geometric Consistency for Partial-Duplicate Image Search,
ICPR2014, oral presentation, pp. . []
52. Canyi Lu, Yunchao Wei, Zhouchen Lin, and Shuicheng Yan, Proximal Iteratively Reweighted Algorithm with Multiple Splitting for Nonconvex Sparsity Optimization, AAAI2014, pp. . []
51. Yifan Fu, Junbin Gao, David Tien, and Zhouchen Lin, Tensor LRR Based Subspace Clustering, International Joint Conference on Neural Networks (IJCNN) 2014, oral presentation, pp. . []
50. Jianjun Qian, Jian Yang, Fanlong Zhang, and Zhouchen Lin,
Robust Low-Rank Regularized Regression for Face Recognition with Occlusion, CVPR 2014 Biometrics Workshop, pp. 21-26.
49. Han Hu, Zhouchen Lin, Jianjiang Feng, and Jie Zhou, Smooth Representation Clustering, CVPR2014, oral presentation, pp. . [][][]
48. Jiashi Feng, Zhouchen Lin, Huan Xu, and Shuicheng Yan, Robust Subspace Segmentation with Block-diagonal Prior,
CVPR2014, oral presentation, pp. . [][][]
47. Risheng Liu, Junjie Cao, Zhouchen Lin, and Shiguang Shan, Adaptive Partial Differential Equation Learning for Visual Saliency Detection, CVPR2014, oral presentation, pp. . [][]
46. Chunyu Wang, Yizhou Wang, Zhouchen Lin,
Alan Yuille, and Wen Gao, Robust Estimation of 3D Human Poses from Single Images,
CVPR2014, pp. . [][]
45. Canyi Lu, Shuicheng Yan, and Zhouchen Lin, Generalized Nonconvex Nonsmooth Low-Rank Minimization, CVPR2014, pp. . []
44. Risheng Liu, Zhouchen Lin,
and Zhixun Su, Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning, ACML2013. [][]
43. Canyi Lu, Jinhui Tang, Min Lin, Liang Lin, Shuicheng Yan, and Zhouchen Lin, Correntropy Induced L2 Graph for Robust Subspace Clustering, ICCV2013. []
42. Canyi Lu, Zhouchen Lin, and Shuicheng Yan, Correlation Adaptive Subspace Segmentation by Trace Lasso, ICCV2013. [] [] []
41. Hongyang Zhang, Zhouchen Lin, and Chao Zhang, A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank,
ECML/PKDD2013, arXiv:
40. Xin Zhang, Zhouchen Lin, Fuchun Sun, and Yi Ma, Rectification of Optical Characters as Transform Invariant Low-rank Textures,
ICDAR2013. []
Mingyu Fan, Xiaoqin Zhang, Zhouchen Lin, Zhongfei Zhang, and Hujun Bao,
Geodesic Based Semi-supervised Multi-manifold Feature Extraction, ICDM 2012, pp. 852-857.
38. Risheng Liu, Zhouchen
Lin, Fernando De La Torre, and Zhixun Su, Fixed-Rank Representation for Unsupervised Visual Learning, CVPR
2012. [][supplementary
37. Liansheng Zhuang,
Haoyuan Gao, Zhouchen Lin, Yi Ma, Xin Zhang, and Nenghai Yu, Non-Negative Low Rank and Sparse Graph for
Semi-Supervised Learning, CVPR2012. [pdf]
36. Zhouchen Lin,
Risheng Liu, and Zhixun Su, Linearized
Alternating Direction Method with Adaptive Penalty for Low Rank Representation,
NIPS 2011, arXiv: . [][][code]
Wenming Zheng, Hao Tang, Zhouchen Lin and Thomas Huang, Emotion Recognition from Arbitrary View
Facial Images, ECCV 2010. []
34. Risheng Liu, Zhouchen
Lin, Wei Zhang and Zhixun Su, Learning
PDEs for Image Restoration via Optimal Control, ECCV 2010. [pdf]
33. Guangcan Liu, Zhouchen
Lin and Yong Yu, Robust Subspace
Segmentation by Low-Rank Representation, ICML 2010. [pdf]
32. Moshe Ben-Ezra, Zhouchen
Lin, and Bennett S. Wilburn, Aperiodic
pixel layout for super-resolution (Invited Paper), Optics, Photonics and
Digital Technologies for Multimedia Applications (SPIE photonics Europe 2010),
Proceedings of SPIE, Volume 7723, April
Wangmeng Zuo, Zhouchen Lin, Zhenhua Guo, and David Zhang, The Multiscale Competitive Code via
Sparse Representation for Palmprint Verification, CVPR 2010. [pdf]
30. Jingjing Fu, Zhouchen
Lin, Bing Zeng, and Feng Wu, Tree
Structure Based Analyses on Compressive Sensing for Binary Sparse Sources, Data Compression Conference (DCC) 2010.
29. Arvind Ganesh, Zhouchen
Lin, John Wright, Leqin Wu, Minming Chen, and Yi Ma, Fast Algorithms for Recovering a Corrupted Low-Rank Matrix,
International Workshop on Computational Advances in Multi-Sensor Adaptive
Processing, December 2009, invited paper. [pdf]
28. Wenming Zheng and Zhouchen
Lin, Optimizing Multi-class
Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification,
NIPS 2009, oral presentation. []
27. Yanlin Geng, Tong
Lin, Zhouchen Lin, and Pengwei Hao, Refined
Exponential Filter with Applications to Image Restoration and Interpolation,
ACCV 2009. []
Risheng Liu, Zhixun Su, Zhouchen Lin, and Xiaoyu Hou, Lorentzian Discriminant Projection and Its
Applications, ACCV 2009. [pdf]
Wenming Zheng, Hao Tang, Zhouchen Lin and Thomas Huang, A Novel Approach to Expression Recognition
from Non-frontal Face Images, ICCV 2009. [pdf]
Feng Wu, Jingjing Fu, Zhouchen Lin, and Bing Zeng, Analysis on Rate-distortion Performance of Compressive Sensing for
Binary Sparse Source, Data Compression Conference (DCC) 2009, pp. 113-122.
23. Deli Zhao, Zhouchen
Lin, and Xiaoou Tang, Classification
via Semi-Riemannian Spaces, CVPR 2008. [pdf]
22. John Wright, Yangyu
Tao, Zhouchen Lin, Yi Ma, and Heung-Yeung Shum, Classification via Minimum Incremental Coding Length (MICL),
Advances in Neural Information Processing Systems 2007. [pdf]
21. Deli Zhao, Zhouchen
Lin, and Xiaoou Tang,&Laplacian
PCA and Its Applications, Int’l Conf. Computer Vision’07. [pdf]
20. Deli Zhao, Zhouchen
Lin, and&Xiaoou Tang,&Contextual
Distance for Data Perception, Int’l Conf. Computer Vision’07. [pdf]
19. Guangcan Liu, Zhouchen
Lin, Xiaoou Tang, and Yong Yu, A
Hybrid Graph Model for Unsupervised Object Segmentation, Int’l Conf.
Computer Vision’07. []
18. Moshe Ben-Ezra, Zhouchen
Lin, and Bennett Wilburn, Penrose
Pixels: Super-Resolution in the Detector Layout Domain, Int’l Conf.
Computer Vision’07. []
17. Zhouchen Lin,
Junfeng He, Xiaoou Tang, and Chi-Keung Tang, Limits of Learning-Based Superresolution Algorithms, Int’l Conf.
Computer Vision’07. []
16. Deli Zhao, Zhouchen
Lin, Rong Xiao, and Xiaoou Tang, Linear
Laplacian Discrimination for Feature Extraction, IEEE Conf. on Computer
Vision and Pattern Recognition 2007 (CVPR’07). [pdf]
15. Lifeng Wang, Zhouchen
Lin, Tian Fang, Xu Yang, Xuan Yu, and Singbing Kang, Real-Time Rendering of Realistic Rain, Siggraph 2006 Sketches, p. 156. [pdf]
14. Zhouchen Lin,
Lifeng Wang, and Liang Wan, First Order
Approximation for Texture Filtering, Pacific Graphics 2006, Taipei, Taiwan,
October 2006. []
13. Junfeng He, Zhouchen
Lin, Lifeng Wang, and Xiaoou Tang, Detecting
Doctored JPEG Images via DCT Coefficient Analysis, 9th European Conf. on
Computer Vision, Lecture Notes on Computer Science, Vol. 3953, pp. 423-435,
12. Liang Wan, Bin Wan,
and Zhouchen Lin, On-Line
Signature Verification With Two-Stage Statistical Models, Int’l Conf. on
Document Analysis and Recognition 2005 (ICDAR’05), pp. 282-286, 2005. [pdf]
11. Zhouchen Lin,
Rongrong Wang, Xiaoou Tang, and Heung-Yeung Shum, Detecting Doctored Images Using Camera Response Normality and
Consistency, IEEE Conf. on Computer Vision and Pattern Recognition 2005
(CVPR’05), pp.. []
10. Liang Wan, Zhouchen
Lin, and Rong Chun Zhao, Signature
verification using integrated classifiers, The 4th Chinese Conference
on Biometric Recognition (Sinobiometrics'03), Beijing, P.R. China, Dec. 7-8, 2003.
9. Liang Wan, Zhouchen
Lin, Rong-Chun Zhao, Off-line Signature Verification Incorporating the
Prior Model, International Conference on Machine Learning and Cybernetics
(ICMLC2003), Xi'an, China, pp. , 2-5 November, 2003. [pdf]
8. Ke Deng, Lifeng Wang, Zhouchen
Lin, Tao Feng, Zhidong Deng, Baining Guo, Correction and Rectification
of Light Field, Proceedings of Virtual Reality and Its Implement
(VRAI’2002), pp. 84-91, Hangzhou ,China, 2002.
7. Zhouchen Lin,
Tien-Tsin Wong, Heung-Yeung Shum, Relighting with the Reflected Irradiance
Field: Representation, Sampling and Reconstruction, CVPR'01, Kauai, Hawaii,
pp. 561-567, Vol. 1, 8-14 December, 2001, oral presentation. [pdf]
6. Zhouchen Lin
and Heung-Yeung Shum, On the Fundamental Limits of Reconstruction-Based
Super-resolution Algorithms, CVPR'01, Kauai, Hawaii, pp. , Vol. 1,
8-14 December, 2001. []
5. Zhouchen Lin
and Heung-Yeung Shum, On the Number of Samples Needed in Light Field
Rendering with Constant-depth Assumption, Proceedings of IEEE Computer
Vision and Pattern Recognition (CVPR’2000), Hilton Head Island, South Carolina,
USA, pp. 588-579, June 2000, oral presentation. [pdf]
4. Zhouchen Lin,
Qing-Yun Shi, An Anisotropic Diffusion PDE
for Noise Reduction and Thin Edge Preservation, Proceedings of ICIAP'99
(10th International Conference on Image Analysis and Processing), Venice,
Italy, pp. 102-107, 1999. []
3. Zhouchen Lin,
Tsai-Man Shih, Constrained Optimal Control of Continuous Casting，Proceedings of THERMEC'97
(International Conference on Thermo-mechanical Processing of Steels and Other
Materials), Wollongong, Australia, The Minerals, Metals and Materials Society,
pp. , 1997.
2. Zhouchen Lin,
Tsai-Man Shih, Numerical Analysis of the Bulging of Continuously Cast Slabs，Workshop on Scientific
Computing (G. Golub et al. eds.)，Springer-Verlag, pp. 243-249, 1997.
1. 林宙辰，石济民，连续铸钢的最优控制 (Optimal Control
of Continuous Casting)，第九届全国炼钢学术会议论文集，广州，中国，pp. 630-637,& 1996.
Technical Reports:
Wang, Zhouchen Lin, Tian Fang, Xu Yang, Xuan Yu, Sing Bing Kang, Real-Time Rendering of
Realistic Rain, MSR-TR-, July 2006.
Zhouchen Lin, Junfeng He, Xiaoou Tang, and Chi-Keung Tang, Limits of Learning-Based Superresolution
Algorithms, MSR-TR-2009-92, August 2007.
Lifeng Wang, Zhouchen Lin, Wenle Wang, and Kai Fu, One-Shot
Approximate Local Shading,
Yan Li, Pengwei Hao, and Zhouchen
Lin, Color Filter Arrays:
Representation and Analysis, Tech. Report no. RR-08-04,
Dept. of Computer Science, Queen Mary, Univ. of London, 2008.
5. Yan Li, Pengwei Hao,
and Zhouchen Lin, Color Filter
Arrays: A Design Methodology, Tech. report no. RR-08-03,
Dept. of Computer Science, Queen Mary, Univ. of London, 2008.
6. Zhouchen Lin,
Wei Zhang, and Xiaoou Tang, , MSR-TR-,
August 2008.
7. Zhouchen Lin,
Wei Zhang, and Xiaoou Tang, , MSR-TR-,
August 2009.
8. Zhouchen Lin, Arvind
Ganesh, John Wright, Leqin Wu, Minming Chen, and Yi Ma,
Convex Optimization Algorithms for Exact Recovery of a Corrupted Low-Rank
Matrix, Technical
Report UILU-ENG-09-2214, UIUC, August 2009.
9. Zhouchen Lin,
Minming Chen, and Yi Ma, The Augmented
Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrix,
Technical Report UILU-ENG-09-2215, UIUC, October 2009 (arXiv: ). [pdf][code] Please cite this technical report as &Zhouchen Lin,
Risheng Liu, and Zhixun Su, Linearized
Alternating Direction Method with Adaptive Penalty for Low Rank Representation,
Advances in Neural Information Processing Systems (NIPS) 2011.& instead. Thanks!
10. Zhouchen Lin, Some Software Packages for Partial SVD
Computation, arXiv: .
11. Siming Wei and Zhouchen
Lin, Analysis and Improvement of Low
Rank Representation for Subspace segmentation, arXiv: .
12. Zhouchen Lin
and Siming Wei, A Block Lanczos with Warm
Start Technique for Accelerating Nuclear Norm Minimization Algorithms,
arXiv: . []
US Patents: (Those marked by ‘*’
have been approved)
1. Inertial
Sensors Integration
2. ****Decoding and
Error Correction in 2-D Arrays
(Four Patents)
3. *High Quality
Anti-Aliasing
4. *Enhanced
Approach of m-Array Decoding and Error Correction
*System and Method for Shape Recognition of Hand-Drawn Objects
6. *System and
Method for Detecting a List in Ink Input
*(OC#41/MS#) Personalized Ink Font
*(OC#86/MS#) Ink Input Region Adjustments
*(OC#38/MS#) Form Factor and Input Method for Language Input
*(OC#71/MS#) Direct Homography Computation by Local
Linearization
*(OC#43/MS#) Digital Pen Calibration by Local Linearization
(OC#15/MS#) Embedding Method for Embedded Interaction Code
*(OC#80/MS#) Global Metadata Embedding and Decoding
*(OC#46/MS#) Local Metadata Embedding and Decoding
(OC#US/MS#) Stroke Localization and Binding to Electronic
*(OC#69/MS#) Spatial Transforms from Displayed Codes
*(OC#78/MS#) Fast Error-Correcting of Embedded Interaction
*(OC#23/MS#) Detecting Doctored Images Using Camera Response
Normality and Consistency
*(MS#) Analyzing Scripts and Determining Characters in Expression
Recognition
*(MS#) Analyzing Subordinate Sub-Expressions in Expression Recognition
*(OC#/MS#US) Cleaning up Handwriting
Intra-Stroke and Inter-Stroke Overtracing
22. *(OC#08/MS#)
Script Recognition for Ink Notes
*(OC#09/MS#) Table Detection in Ink Notes
*(OC#68/MS#) Framework for Detecting a Structured
Handwritten Object
*(OC#13/MS#) Handwriting Recognition Training and Synthesis
*(OC#12/MS#) Signature Verification
*(OC#14/MS#) Annotation Detection and Anchoring on Ink Notes
*(OC#MS1-2868US/MS#) Strategies for Processing Annotations
*(OC#10/MS#) Ink-Parser-Parameter Optimization
*(OC#MS1-3025US/MS#) Detecting Doctored JPEG Images
*(OC#MS1-3026US/MS#) Method, Device and Program for Detecting
Perceptual Features of a Larger Image and Incorporating Information of the
Detected Perceptual Features into a Smaller Preview Image
*(OC#MS1-3144US/MS#) Producing Animated Scenes from Still Images
*(OC#MS1-3129US/MS#) Real-Time Rendering of Realistic Rain
34. *(OC#MS1-3165US/MS#)
Decoding Technique for Linear Block Codes
(OC#MS1-3232US/MS#) Revenue-Based Advertising Auction
*(OC#MS1-3430US/MS#) 2D Barcode Recognition
*(MS#) Super-resolution in Periodic and Aperiodic Pixel Imaging
*(OC#MS1-3608US/MS#) Hybrid Graph Model for Unsupervised Object
Segmentation
*(MS#) Method for Modeling Data Structures Using Local Context
*(OC#MS1-366US/ MS#) Laplacian Principal Components Analysis (LPCA)
*(OC#MS1-3609US/MS#) Modeling and Rendering of Heterogeneous
Translucent Materials Using the Diffusion Equation
*(OC#MS1-3668US/MS#) Linear Laplacian Discrimination for Feature
Extraction
(MS#) Multi-class Transform for Discriminant Subspace Analysis
(MS#) Globally Invariant Radom Feature Transforms for Texture
Classification
(OC#US /MS#) Learning-Based Partial Differential Equations
for Computer Vision
*(MS#) Tensor Linear Laplacian Discrimination for Feature Extraction
*(MS#) Classification via Semi-Riemannian Spaces
*(MS#) Computing Minimal Polynomials of Radical Expressions
*(MS#) Computing Minimal Polynomials
50. *(MS#)
Kernel Nystrom Method for Light Transport
(MS#) Rectification of Characters and Text as Transform Invariant
Low-Rank Textures
Chinese Patents:
1. (.7) 基于低秩全局几何一致性检验的错误匹配检测方法
2. (.0) 基于L1范数全局几何一致性检验的错误匹配检测方法
3. (.4) 一种基于形状交互矩阵的图像错误匹配检验方法
Academic Activities:
1. Associate
Editor of IEEE Trans. Pattern Analysis and Machine Intelligence.
2. Associate
Editor of International Journal of Computer Vision.
3. Executive Editor of Big Data and Information Analytics.
3. Associate
Editor of Neurocomputing.
Professor of Northeast Normal University.
Professor of Shanghai Jiaotong University.
Researcher of Institute of Computing Technologies, Chinese Academy of Sciences.
Professor of Southeast University.
Professor and Ph.D. Supervisor of Beijing Jiaotong University.
9. Technical Advisory Board of Guangdong Key Lab. of Machine Vision and Virtual Reality.
Technical Advisory Board of Key Lab. of Machine Vision and Pattern Recognition,
Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen.
11. Reviewer to
IEEE Trans.
Pattern Analysis and Machine Intelligence, International Journal of Computer
Vision, IEEE Trans. Information Theory, J. Machine Learning Research, Mathematical Reviews, IEEE Trans. Image
Processing, IEEE Trans. Signal Processing, IEEE Trans. Neural Network,
Optimization Letters, IEEE Trans. Circuits and Systems for Video Technology,
Pattern Recognition, IEEE Trans. Multimedia, IEEE Trans. Information Forensics
and Security, ACM Trans. on Graphics, Signal Processing, IEEE Signal Processing
Magazine, IEEE
Signal Processing Letters, SIAM J. Numerical Analysis, SIAM J. Imaging Sciences, Signal Processing Letters, The Visual
Computer, Computer Vision and Image Understanding, Multimedia Systems Journal,
Machine Vision and Applications, Photogrammetric Engineering and Remote
Sensing, 中国科学(E辑) [Science in China
(Series E)]
12. Reviewer to
Conferences:
ICPR 2018 (Tutorial Chair), AAAI 2017 (Senior Program Committee), IJCAI 2016 (Senior Program Committee), ICML 2016, CVPR 2016 (Area Chair), AAAI 2016 (Senior Program Committee), NIPS 2015 (Area Chair), IJCAI 2015, ICCV 2015 (Area Chair), ICML 2015, CVPR 2015, AAAI 2015, NIPS 2014, ECCV 2014, ICML 2014, CVPR 2014 (Area Chair), Siggraph Asia 2013, ICCV 2013, IJCAI 2013, ACCV 2012,
Siggraph 2012, IEEE Computer Vision and Pattern Recognition 2012, Asian Conf.
Machine Learning 2011, NIPS 2011, Int’l Conf. Computer Vision 2011,
Eurographics 2011, IEEE Computer Vision and Pattern Recognition 2011, Asian
Conf. Machine Learning 2010, IEEE Computer Vision and Pattern Recognition 2010,
Asian Conf. Computer Vision 2009 (Area
Chair), Int’l Conf. Computer Vision 2009,& IEEE Computer Vision and Pattern
Recognition 2009, Asian Conf. Machine Learning 2009, European Conf. Computer
Vision 2008, IEEE Computer Vision and Pattern Recognition 2008, Int’l Conf.
Computer Vision 2007, IEEE Computer Vision and Pattern Recognition 2007, Asian
Conf. Computer Vision 2007, Pacific Graphics 2006, Geometric Modeling and
Processing 2006, IEEE Computer Vision and Pattern Recognition 2005, Visual
Communications and Image Processing 2005, IEEE Computer Vision and Pattern
Recognition 2004, Eurographics 2002, Asian Conf. Computer Vision 2002, Int’l
Conf. Multimodal Interfaces 2002, Int’l Conf. Images and Graphics 2002, Int’l
Conf. Computer Vision 2001, Pacific Graphics 2001
13. Membership:
IEEE Senior Member
1. Fundamentals of Data Analysis (, subject to change)
2. Manifold Learning and Sparse Representation (, subject to change)()
Graduated Students:
1. Guangcan Liu,
from Shanghai Jiaotong University, Ph.D. in 2010.
Minming Chen, from Institute of Computing Technologies, Chinese Academy of
Sciences, Master in 2010. Thesis: Algorithms and
Implementations of Matrix Reconstruction (in Chinese).
Risheng Liu, from Dalian University of Technology, Ph.D. in 2012.
Keynote Speeches:
1. Low Rank
Representation: Theories, Algorithms, and Applications
At: Digital
Image Computing: Techniques and Applications ()
Tutorials:
Minimization: Theories, Algorithms, and Applications
At: Charles-Sturt University (July 25-26, 2013)
2. Low-Rank
Matrix Recovery: Theories, Algorithms, and Applications
At: Int’l Conf.
Image Processing (), Int’l Conf. Imaging and Graphics (ICIG) 2011,
Mathematics for Machine Learning
At: Hong Kong
Polytechnic University (Aug. 27, 18, and 31, 2012)
4. Practical High Dimensional Data Analysis
At. Northeastern Normal University (Nov. 29, 2014 -- Jan. 20, 2015)
5. Low-Rank and Sparse Modeling for Visual Analytics
(June 26, 2016)
Invited Talks:
1.Fundamental Limits
of Reconstruction-Based Superresolution
At: Peking University, Institute
Sensing Applications (Chinese Academy of Sciences)
2.Applications of
Mathematics in Computer Vision by Examples
At: Peking University, Tsinghua
University, Nankai University, Dalian University of Technology, Huazhong
University of Science and Technology, Beijing Jiaotong University
3.Learning-Based
Superresolution
At: Lotus Hill Institute for
Computer Vision and Information Science, Institute of Automation (Chinese
Academy of Sciences) (Oct. 27, 2008), Nanjing University (Nov. 8, 2008)
4.Contextual
Asymmetric Data Perception
At: Institute of Automation
(Chinese Academy of Sciences), Institute of Computing Technologies (Chinese
Academy of Sciences), Shanghai Jiaotong University, Beijing Jiaotong
University, Southeast University, Sichuan University
5.Doctored Image
At: Beijing Jiaotong University,
Shanghai Jiaotong University
6.How to Write Good Papers [] []
( []) () ()
At: Institute of Computing
Technologies (Chinese Academy of Sciences) (Apr. 24, 2008), Southeast
University (May 26, 2008), Nanjing University of Aeronautics and Astronautics
(May 27, 2008), Peking University (Oct. 10, 2008),
Ritsumeikan University (Aug. 1, 2014), Northwestern Polytechnical University (Nov. 10, 2014)
7.A Glance over
Manifold Learning
At: Peking University (Oct. 9,
2008), Institute of Computing Technologies (Chinese Academy of Sciences, Oct.
8.A Geometric Method
for Optimal Design of Color Filter Arrays
At: Peking University (Nov. 30,
University of Science and Technology of China (Nov. 20, 2012), University of Science and Technology of China (Nov. 20, 2012), 2014全国图形图像处理技术应用大会 (Beijing, Nov. 1, 2014)
9. Sparsity: the Current Surge
At: People’s University of China
(Dec. 10, 2008)
10. Solving the Close-Class-Means
Heteroscedastic Discriminant Analysis Problems via Bayes Error Estimation
At: ACCV 2009 Workshop on Computer Vision (July
11. Robust PCA: Theories, Algorithms and
Applications
At: Peking University (April 20, 2010)
12. Rank Minimization C A Way to 2D Sparsity
At: Institute of Computing Technologies
(Chinese Academy of Sciences, Dec. 1, 2010), Northeast Normal University (Dec.
8, 2010), Fudan University (Dec. 15, 2010), Beijing University of Posts and
Communications, Dec. 22, 2010), Dalian University of Technology (Sept. 26,
13. Advances and Problems in 2D and Higher
Dimensional Sparsity
At: Peking University (June 8, 2011)
14. Rank Minimization: Theories, Algorithms,
and Applications
At: Zhejiang University (Jul. 28, 2011),
Nanjing University of Aeronautics and Astronautics (May 4, 2012), A-Star
Singapore (Aug. 3, 2012), Hong Kong Polytechnic University (Aug. 29, 2012), Sino-Foreign-Interchange Workshop on Intelligence Science and Intelligence Data
Engineering (), Machine
Learning and Applications (),
University of Science and Technology of China (Nov. 19, 2012)
15. New Advances in Rank Minimization
At: Northeast Normal University (Sept. 19,
2011), Xi’an Jiaotong University (Sept. 22, 2011)
16. Computation Techniques in Nuclear Norm
Minimization
At: Zhejiang University (Oct. 28, 2011)
17. Low Rank Representation: Theories,
Algorithms, and Applications
At: PKU KLMP Annual Conference (March 24,
2012), Vision and Learning
Seminar (), Nanjing
Univ. of Information Science & Technology (May 3, 2012), Nanjing University
of Science and Technology (May 3, 2012), Nanyang Technology University (Aug. 1,
(Nov. 18, 2012), Ritsumeikan University (July 15, 2014), Beihang University (Apr. 17, 2015), Henan University (May 24, 2015),
(Oct. 30, 2015),
(Nov. 29, 2015), National University of Defense Technology (Jan. 10, 2016)
18. Fast Solving Transform Invariant Low-Rank
Textures (TILT)
At: National University of Singapore (Aug.10,
2012), Hong Kong Baptist University (Aug. 21, 2012)
19. Learning Partial Differential Equations for Computer Vision and Image Processing
At: University of Science and Technology of China (Nov. 20, 2012), International Conf. Image Science (, Dec. 12, 2013),
(Jan. 6, 2013), Osaka University (Mar. 26, 2013), Charles-Sturt University (July 31, 2013), University of Technology Sydney (Aug. 7, 2013), Institute of Information Engineering, Chinese Academy of Sciences (Sept. 12, 2013), Ritsumeikan University (July 18, 2014), Tokyo Institute of Technology (Aug. 18, 2014), University of Tokyo (Aug. 20, 2014), Xi'an Jiaotong University (Nov. 7, 2014), Tsinghua University (Dec. 24, 2014),
(June 21, 2015)
20. Subspace Clustering - Recent Advances
At: Tsinghua University (Oct. 10, 2013, Dec. 11, 2014), Institute of Automation, Chinese Academy of Sciences (Oct.
16, 2013), National University of Defense Technologies (Oct. 22, 2013), Hunan University (Oct. 23, 2013), Beijing Jiaotong University (Oct. 28, 2013), Shanghai Jiaotong University (Oct. 31, 2013), Beijing Institute of Technology (Nov. 6, 2013), Beijing University of Technology (Dec. 18, 2013),Tianjin University (Dec. 26, 2013),
(Feb. 24, 2014), Beijing University of Posts and Telecommunications (Apr. 10, 2014), Xi'an Jiaotong University (Nov. 8, 2014), Northwestern Polytechnical University (Nov. 10, 2014), Xidian University (Nov. 10,
(Nov. 30, 2014), Tsinghua University (Dec. 11, 2014), Nankai University (Dec. 31, 2014), University of Science and Technology of China (July 23, 2015), 2015 Joint Academic Forum between Sungkyunkwan University and Peking Unviersity (Sept. 10, 2015),
(Oct. 11, 2015)
21. Linearized Alternating Direction Method: Two Blocks and Multiple Blocks
(Dec. 22, 2013), VALSE QQ Webcast (Dec. 23, 2014),
2016 (Apr. 25, 2016)
22. Block-Diagonality in Subspace Clustering
(The First Annual Conference of Computer Vision Task Forces, China Computer Federation, Sept. 13, 2014), Nankai University (Dec. 30, 2015)
23. Text Detection and Rectification Using Low-Rank Models
At: 第四届全国文字与计算学术研讨会(NSCC) (Beijing, Oct. 25, 2014), Forum on Frontiers of Image Processing (Beijing, Dec. 18, 2014),
(July 24, 2015)
24. Optimized Projections for Compressed Sensing via Direct Mutual Coherence Minimization
(Oct. 20, 2015).
25. Closed-Form Solutions in Low-Rank Subspace Recovery Models and Their Implications
(Nov. 7, 2015).
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