openpr_nlpr has posted 20 projects.
Showing Items 1-20 of 38 on page 1 of 2: 1 2 Next

Logo RFD 1.0

by openpr_nlpr - April 28, 2014, 10:34:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 918 views, 213 downloads, 1 subscription

About: This is an unoptimized implementation of the RFD binary descriptor, which is published in the following paper. B. Fan, et al. Receptive Fields Selection for Binary Feature Description. IEEE Transaction on Image Processing, 2014. doi: http://dx.doi.org/10.1109/TIP.2014.2317981

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Initial Announcement on mloss.org.


About: Kaiye Wang, Ran He, Wei Wang, Liang Wang, Tiuniu Tan. Learning Coupled Feature Spaces for Cross-modal Matching. In ICCV, 2013.

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Initial Announcement on mloss.org.


Logo Two dimensional relaxed representation 1.0

by openpr_nlpr - November 4, 2013, 05:48:12 CET [ Project Homepage BibTeX Download ] 814 views, 178 downloads, 1 subscription

About: Q. Dong, Two-dimensional relaxed representation, Neurocomputing, 121:248-253, 2013, http://dx.doi.org/10.1016/j.neucom.2013.04.044

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Initial Announcement on mloss.org.


Logo Evaluation toolkit 1.0

by openpr_nlpr - August 13, 2013, 08:58:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1047 views, 211 downloads, 1 subscription

About: This evaluation toolkit provides a unified framework for evaluating bag-of-words based encoding methods over several standard image classification datasets.

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Initial Announcement on mloss.org.


About: This letter proposes a new multiple linear regression model using regularized correntropy for robust pattern recognition. First, we motivate the use of correntropy to improve the robustness of the classicalmean square error (MSE) criterion that is sensitive to outliers. Then an l1 regularization scheme is imposed on the correntropy to learn robust and sparse representations. Based on the half-quadratic optimization technique, we propose a novel algorithm to solve the nonlinear optimization problem. Second, we develop a new correntropy-based classifier based on the learned regularization scheme for robust object recognition. Extensive experiments over several applications confirm that the correntropy-based l1 regularization can improve recognition accuracy and receiver operator characteristic curves under noise corruption and occlusion.

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Initial Announcement on mloss.org.


About: Robust sparse representation has shown significant potential in solving challenging problems in computer vision such as biometrics and visual surveillance. Although several robust sparse models have been proposed and promising results have been obtained, they are either for error correction or for error detection, and learning a general framework that systematically unifies these two aspects and explore their relation is still an open problem. In this paper, we develop a half-quadratic (HQ) framework to solve the robust sparse representation problem. By defining different kinds of half-quadratic functions, the proposed HQ framework is applicable to performing both error correction and error detection. More specifically, by using the additive form of HQ, we propose an L1-regularized error correction method by iteratively recovering corrupted data from errors incurred by noises and outliers; by using the multiplicative form of HQ, we propose an L1-regularized error detection method by learning from uncorrupted data iteratively. We also show that the L1-regularization solved by soft-thresholding function has a dual relationship to Huber M-estimator, which theoretically guarantees the performance of robust sparse representation in terms of M-estimation. Experiments on robust face recognition under severe occlusion and corruption validate our framework and findings.

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Initial Announcement on mloss.org.


Logo MROGH 1.0

by openpr_nlpr - October 16, 2012, 04:41:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1750 views, 361 downloads, 1 subscription

About: An implementation of MROGH descriptor. For more information, please refer to: “Bin Fan, Fuchao Wu and Zhanyi Hu, Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011, pp.2377-2384.” The most up-to-date information can be found at : http://vision.ia.ac.cn/Students/bfan/index.htm

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Initial Announcement on mloss.org.


Logo SkyVoice TTS and SDK 1.0

by openpr_nlpr - September 10, 2012, 03:48:47 CET [ Project Homepage BibTeX Download ] 1476 views, 334 downloads, 1 subscription

About: Text-to-Speech (TTS) is a kind of speech processing technology that converts text into speech. It involves phonetics, linguistics, digital signal processing technology, computer technology, multimedia technology, and other technologies. It is a frontier technology in Chinese information processing field. With TTS technology, any text used to be read by eyes can also be listened by ears.

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Initial Announcement on mloss.org.


Logo Threshold Image for Small object 1.0

by openpr_nlpr - July 23, 2012, 11:25:46 CET [ Project Homepage BibTeX Download ] 1549 views, 432 downloads, 1 subscription

About: Including source code of Threshold Method,SVM,Play Scan and Play detection.

Changes:

Initial Announcement on mloss.org.


About: We study the problem of robust feature extraction based on L21 regularized correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that an L21-norm minimization can be justified from the viewpoint of half-quadratic (HQ) optimization, which facilitates convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify L1-norm and L21-norm minimization within a common framework. In algorithmic part, we propose an L21 regularized correntropy algorithm to extract informative features meanwhile to remove outliers from training data. A new alternate minimization algorithm is also developed to optimize the non-convex correntropy objective. In terms of face recognition, we apply the proposed method to obtain an appearance-based model, called Sparse-Fisherfaces. Extensive experiments show that our method can select robust and sparse features, and outperforms several state-of-the-art subspace methods on largescale and open face recognition datasets.

Changes:

Initial Announcement on mloss.org.


Logo Action Recognition by Dense Trajectories 1.0

by openpr_nlpr - June 6, 2012, 11:38:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3193 views, 605 downloads, 1 subscription

About: The code is for computing state-of-the-art video descriptors for action recognition. The most up-to-date information can be found at: http://lear.inrialpes.fr/people/wang/dense_trajectories

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Initial Announcement on mloss.org.


About: Ran He, Wei-Shi Zheng,Tieniu Tan, and Zhenan Sun. Half-quadratic based Iterative Minimization for Robust Sparse Representation. Submitted to IEEE Trans. on Pattern Analysis and Machine Intelligence.

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Initial Announcement on mloss.org.


About: This code is developed for incorporating a class of linear priors into the regression model.

Changes:

Initial Announcement on mloss.org.


Logo Multilinear Principal Component Analysis 1.2 1.2

by openpr_nlpr - April 16, 2012, 09:04:08 CET [ Project Homepage BibTeX Download ] 1787 views, 542 downloads, 1 subscription

About: This archive contains a Matlab implementation of the Multilinear Principal Component Analysis (MPCA) algorithm and MPCA+LDA, as described in the paper Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "MPCA: Multilinear Principal Component Analysis of Tensor Objects", IEEE Transactions on Neural Networks, Vol. 19, No. 1, Page: 18-39, January 2008.

Changes:

Initial Announcement on mloss.org.


Logo Oboe A Chinese Syntactic Parser 1.0

by openpr_nlpr - April 9, 2012, 09:08:35 CET [ Project Homepage BibTeX Download ] 1891 views, 414 downloads, 1 subscription

About: Oboe is a software for Chinese syntactic parsing, and it can display syntactic trees in a graphical view with two kinds of representation: phrase tree and dependency tree. So it is very helpful for NLP researchers, especially for researchers focusing on syntax-based methods.

Changes:

Initial Announcement on mloss.org.


Logo Thresholding program 1.0

by openpr_nlpr - March 1, 2012, 03:18:52 CET [ Project Homepage BibTeX Download ] 3638 views, 441 downloads, 1 subscription

About: This is demo program on global thresholding for image of bright small objects, such as aircrafts in airports. the program include four method, otsu,2D-Tsallis,PSSIM, Smoothnees Method.

Changes:

Initial Announcement on mloss.org.


Logo Efficient Nonnegative Sparse Coding Algorithm 1.0

by openpr_nlpr - January 4, 2012, 09:44:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2059 views, 436 downloads, 1 subscription

About: Nonnegative Sparse Coding, Discriminative Semi-supervised Learning, sparse probability graph

Changes:

Initial Announcement on mloss.org.


About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.

Changes:

Initial Announcement on mloss.org.


Logo Metropolis Hastings algorithm 1.0.0

by openpr_nlpr - December 2, 2011, 05:43:20 CET [ Project Homepage BibTeX Download ] 1389 views, 356 downloads, 1 subscription

About: Metropolis-Hastings alogrithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. Thi sequence can be used to approximate the distribution.

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Initial Announcement on mloss.org.


About: This code is developed based on Uriel Roque's active set algorithm for the linear least squares problem with nonnegative variables in: Portugal, L.; Judice, J.; and Vicente, L. 1994. A comparison of block pivoting and interior-point algorithms for linear least squares problems with nonnegative variables. Mathematics of Computation 63(208):625-643.Ran He, Wei-Shi Zheng and Baogang Hu, "Maximum Correntropy Criterion for Robust Face Recognition," IEEE TPAMI, in press, 2011.

Changes:

Initial Announcement on mloss.org.


Showing Items 1-20 of 38 on page 1 of 2: 1 2 Next