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A fuzzy support vector machine algorithm with dual membership based on hypersphere

Journal of Computational Information Systems 2011年第6期7卷 2028-2034页

作者： Ding, Shifei Gu, Yaxiang School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China

In traditional fuzzy support vector machine(FSVM), membership function is established in global scope will reduce the membership of support vectors, and the FSVM based dismissing margin increases the training speed, but will remove some support vector artificially. So, a new algorithm of Fuzzy Support Vector Machine with Dual Membership based on Hypersphere (HDM-FSVM) is proposed. In this algorithm, the two classes of hyperspheres are divided into two parts respectively. Then, according to most support vectors are in the hemispheres which close together, we use the membership function that can enhance the membership of support vector, and because of there are a few of support vectors in other hemispheres, we must ensure the high membership of support vectors and reduce the membership of non-support vector. In order to removal noise and outliers, we introduce a radius controlling factor to control size of hyperspheres, the samples that outside of hyperspheres are considered as noise and outliers. Experimental results show that HDM-FSVM can enhance the classification accuracy rate of the sample sets that contain noise and outliers. Copyright © 2011 Binary Information Press.

关键词： Membership functions

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Adaptive discriminant analysis for face recognition from single sample per person

Adaptive discriminant analysis for face recognition from sin...

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IEEE International Conference on Automatic Face and Gesture Recognition

作者： Kan, Meina Shan, Shiguang Su, Yu Chen, Xilin Gao, Wen Digital Media Research Center Institute of Computing Technology CAS Beijing China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Beijing China Department of Computer Science University of Caen France Institute for Digital Media Peking University Beijing China School of Computer Science and Technology Harbin Institute of Technology Beijing China

ISBN: (纸本)9781424491407

Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition from Single Sample per Person (SSPP), since they need more than one sample per person to estimate the within-class scatter matrix. To break this inability of traditional discriminant analysis, our paper proposes Adaptive Discriminant Analysis (ADA). In our method, the within-class scatter matrix of each enrolled subject is estimated from his/her single sample, by inferring from a generic training set with multiple samples per person. The inference is inspired by a simple intuition that similar person follows similar within-class variations. Specifically, both kNN regression and Lasso regression are explored for this purpose. We evaluate our method on FERET database and a large real-world face database. The results are very impressive compared with dominant traditional solutions to SSPP problem. © 2011 IEEE.

关键词： Discriminant analysis

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Multi-kernel Co-SVM with a new strategy using unlabeled data for image retrieval

Multi-kernel Co-SVM with a new strategy using unlabeled data...

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International Conference on Pervasive computing and Applications (ICPCA)

作者： Li Zongmin Liu Yang Li Hua School of Computer and Communications Engineering China University of Petroleum Shandong China Key Laboratory Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457702099

Relevance feedback based on SVM classifier shows a good performance recently but the finite feedback counts limited by user's patience and the small sample size problem are not solved well, Co-SVM does a good job in solving these problems but still has some flaws. We propose three strategies to try to improve this algorithm: (1) different kernel functions are used to characterize the color and texture visual similarities; (2) a new method is proposed to caculate the confident scores of the contention samples; (3) a bunch of the most irrelevant images with the highest confident score are added into the labeled images to extend the size of labeled data while choosing a bunch of images for user labeling. Experimental results verify the superiority of our method over Co-SVM.

关键词： Support vector machines Multimedia communication Classification algorithms

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A novel coarse-to-fine hair segmentation method

A novel coarse-to-fine hair segmentation method

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International Conference on Automatic Face and Gesture Recognition

作者： Dan Wang Xiujuan Chai Hongming Zhang Hong Chang Wei Zeng Shiguang Shan Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China NEC Laboratories Beijing China

Segmenting hair regions from human images facilitates many tasks like hair synthesis and hair style trends forecast. However, hair segmentation is quite challenging due to hair/background confusion and large hair pattern diversity. To address these problems to some extent, this paper proposes a novel coarse-to-fine hair segmentation method. In our approach, firstly, the recently proposed “Active Segmentation with Fixation” (ASF) is used to coarsely define an enclosed candidate region with high-recall (but possibly low-precision) of hair pixels and exclude considerable part of the backgrounds which are easily confused with hair. Then Graph Cuts (GC) method is applied to the candidate regions to remove additional false positives by incorporating hair-specific information. Specifically, Bayesian method is employed to select some reliable hair and background regions (seeds) among the ones over-segmented by Mean Shift. SVM classifier is then learnt online from these seeds and explored to predict hair/background likelihood probability, which is subsequently fed into GC algorithm. The novelty of the proposed approach lies in three folds: 1) an elaborate design of hair segmentation framework, which utilizes ASF to reduce the candidate hair regions and adopts GC to achieve more accurate hair region contours; 2) the region-based strategy for seed selection; 3) the exploration of the discriminative method, SVM, to predict the probability of each pixel belonging to hair and background regions. Extensive experimental results demonstrate the approach outperforms recently proposed methods.

关键词： Hair Pixel Image segmentation Support vector machines Bayesian methods Image color analysis Databases

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China's grain security warning based on multifactor information fusion

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2011年第5期27卷 183-189页

作者： Su, Xiaoyan Zhang, Huijie Li, Zhiqiang Deng, Yong School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing 100081 China College of Computer and Information Sciences Southwest University Chongqing 400715 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China

China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: as well as quantitative and qualitative information. In order to get the grain security status comprehensively, we proposed a method to evaluate risk in grain security based on multifactor information fusion. In the method, the quantitative and qualitative information were used to construct the basic probability assignment, and the attribute weights was got based on the Analytic Hierarchy Process method. After that, the multifactor fusion results were got based on the Dempster combination rule. The effectiveness of the method was verified with a numeric example that the data comes from the yearbook of China in 2007. The Results show that the method is effective and can correctly reflect the grain safety warning degrees.

关键词： Analytic hierarchy process

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Shape-based web image clustering for unsupervised object detection?

Shape-based web image clustering for unsupervised object det...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Wei Zheng Changhu Wang Xilin Chen Graduate School Chinese Academy and Sciences Beijing China Microsoft Research Asia Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781612843483

Automatic object detection for an arbitrary class is an important but very challenging problem, due to the countless kinds of objects in the world and the large amount of labeling work for each object. In this work, we target at solving the problem of automatic object detection for an arbitrary class without the laborious human effort. Motivated by the explosive growth of Web images and the phenomenal success of search techniques, we develop an unsupervised object detection framework by automatically training the object detector on the top returns of certain image search engine queried by the name of the object class. In order to automatically isolate the objects from the Web images for training, only clipart images with simple background are used, which preserve most of the shape information of the objects. A two-stage shape-based clustering algorithm is proposed to mine typical shapes of the object, in which the inner-class variance of object shapes is considered and undesired images are filtered out. In order to reduce the gap between clipart images and real-world images, we introduce an efficient algorithm to synthesize the real-world images from clipart images, and only shape feature is used in the detector training part. Finally, the synthetic images could be used to train object detectors by an off-the-shelf discriminative algorithm, e.g., boosting or SVM. Extensive experiments show the effectiveness of the proposed framework on objects with simple and representative shapes, and the proposed framework could be considered as a good beginning of solving this challenging problem.

关键词： Shape Clustering algorithms Training Detectors Image edge detection Object detection Image color analysis

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Context constrained facial landmark localization based on discontinuous Haar-like feature

Context constrained facial landmark localization based on di...

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International Conference on Automatic Face and Gesture Recognition

作者： Xiaowei Zhao Xiujuan Chai Zhiheng Niu Cherkeng Heng Shiguang Shan Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Panasonic Singapore Laboratories Private Limited (PSL) Singapore

Facial landmark localization is well known as one of the bottlenecks in face recognition. This paper proposes a novel facial landmark localization method, which introduces facial context constrains into cascaded AdaBoost framework. The motivation of our method lies in the basic human physiology observation that not only the local texture information but also the global context information is used together for human to realize the landmark location task. Therefore, in our solution, a novel type of Haar-like feature, called discontinuous Haar-like feature, is proposed to characterize the facial context, i.e. the cooccurrence relationship between target facial landmark and other local texture patterns within face region (including other landmarks, facial organs and also smoothing regions). For the locating task, traditional Haar-like features (characterizing local texture information) and discontinuous Haar-like features (characterizing context constrains in global sense) are combined together to form more powerful representations. Through Real AdaBoost learning, distinctive features are selected automatically and used for facial landmark detection. Our experiments on BioID and Cohn-Kanade databases have validated the proposed method by comparing with other state-of-the-art results.

关键词： Context Face Feature extraction Mouth Databases Pixel Accuracy

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Topic level sampling towards optimized locality sensitive vocabulary coding

Topic level sampling towards optimized locality sensitive vo...

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International Conference on Information, Communications and signal processing

作者： Jie Chen Ling-Yu Duan Bing Li Rongrong Ji Wen Gao Institute of Digital Media School of Electronic Engineering and Computer Science Peking University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457700293

We propose a novel locality sensitive vocabulary coding scheme to extract compact descriptors for low bit rate visual search. We employ Latent Dirichlet Allocation (LDA) to learn the topic vocabularies of lower dimension to generate compact descriptors. To deal with diverse datasets, LDA model is introduced to subdivide a dataset into groups of images with a topic model, where the code word distributions in each group produce coherent statistics from generative learning. Moreover, our empirical study has shown that the original Bag-of-Word (BoW) is sparse, and the occurrences of non-zero words is coherent within a topic. Our proposed topic-wise vocabulary learning yields a more compact yet discriminative codebook to search images. Given a query image, multiple topics are determined, which is fed into the topic vocabularies to generate more compact topical descriptor. Comparison experiments show our topic-wise locality sensitive vocabulary coding produces more compact and discriminative descriptors than the state-of-the-arts.

关键词： Vocabulary Visualization Encoding Mobile communication Image coding Histograms Bit rate

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Wind shear signal simulation of the airborne weather radar

Wind shear signal simulation of the airborne weather radar

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IEEE National Conference on Radar

作者： Yi Fan Renbiao Wu Zhichao Meng Zhigang Su Xiaoguang Lu Jingxiong Huang Tianjin Key Laboratory for Advanced Signal Processing Civil Aviation University of China Tianjin P.R. China Intelligent Information Institute of ATR Lab Shenzhen University Shenzhen P.R. China

Wind shear is recognized by a major hazard during takeoff and landing of aircraft, which can be detected by airborne forward-looking weather radar. A high-fidelity wind shear model constructed by the Computational Fluid Dynamics software has been implemented in this study. The model is reasonably representative of the downward wind falling to the ground during the mature phase of the microburst wind shear. The results of the radar echo signal simulation based on the above wind shear model show that the distribution of the velocities has an obvious horizontal "S" shape. The simulated results demonstrate the typical characteristic of the microburst wind shear.

关键词： Wind Atmospheric modeling Numerical models Computational modeling Meteorological radar

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Roughness in vector spaces

Roughness in vector spaces

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IEEE International Conference on Granular computing (GRC)

作者： Mingfen Wu Xiangyun Xie School of Computer Science Wuyi University Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Mathematics and Computational Science Wuyi University China

Rough set theory proposed by Pawlak, is a complementary generalization of classical set theory. The relations between rough sets and algebraic systems endowed with two binary operations such as rings, groups and semigroups have been already considered. Wu, Xie and Cao defined a pair of rough approximation operators based on a sub-space. In this paper we do the further study about the upper (lower)approximations. We propose concepts of W-upper(lower) rough subspaces in an approximation space and give some properties of the upper(lower) and rough subspaces. Some characterizations of the upper(lower) rough subspace are expressed with addition and intersection operations of subspaces. At the same time, some counterexamples are offered to illustrate the relevant results.

关键词： Approximation methods Rough sets Vectors Educational institutions Laboratories

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