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International Conference on Computer Vision (ICCV)

作者： Jinli Suo Xilin Chen Shiguang Shan Wen Gao Key Laboratory of Intelligent Information Processing of CAS Institute for Computing Technology Beijing China Chinese Academy and Sciences China School of Electronic Engineering and Computer Science Peking University China

Studies on face aging are handicapped by lack of long term dense aging sequences for model training. To handle this problem, we propose a new face aging model, which learns long term face aging patterns from partially dense aging databases. The learning strategy is based on two assumptions: (i) short term face aging pattern is relatively simple and is possible to be learned from currently available databases; (ii) long term face aging is a continuous and smooth Markov process. Adopting a compositional face representation, our aging algorithm learns a function-based short term aging model from real aging sequences to infer facial parameters within a short age span. Based on the predefined smoothness criteria between two overlapping short term aging patterns, we concatenate these learned short term aging patterns to build the long term aging patterns. Both the subjective assessment and objective evaluations of synthetic aging sequences validate the effectiveness of the proposed model.

关键词： Aging Databases Biological system modeling Prototypes Face detection Skin Content addressable storage Computer vision Muscles Deformable models

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Automatic entity relation extraction for the field of tourism

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Journal of Computational information Systems 2009年第6期5卷 1653-1659页

作者： Zhang, Yihao Guo, Jianyi Yu, Zhengtao Yao, Xianming Zhang, Shaomin Lei, Chunya The School of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China The Institute of Intelligent Information Processing Computer Technology Application Key Laboratory of Yunnan Province Kunming 650051 China

Entity relation extraction is an important research field in information extraction. In this paper, a machine learning algorithm that use maximum entropy to extract relations between entities in the filed of tourism is proposed. We consider comprehensively the syntactic context information, entity types, vocabulary, part of speech information and their combination features, and focus on selecting suitable feature in the field of tourism in order to build the classifier of entity relation extraction. We do our experiment on the artificial collection of 600 corpuses in the field of tourism. The methods used in this paper receive a good result in the identification of two types entity relation, The F values reached 81.21% and 78.46% respectively. Comparing with two groups of experiments, we can conclude that combination features can effectively improve the accuracy of the maximum entropy classifier's model. 1553-9105/ Copyright © 2009 Binary information Press.

关键词： Learning algorithms

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A novel method for segmentation of the cardiac MR images using generalized DDGVF snake models with shape priors

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information technology Journal 2009年第4期8卷 486-494页

作者： Liu, Lixiong Wu, Yuwei Wang, Yuanquan Beijing Laboratory of Intelligent Information Technology School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China

In this study, a novel method is presented for segmentation of the endocardium and epicardium of the left ventricle in cardiac magnetic resonance images using snake models. We first generalize the DDGVF snake model by introducing two spatially varying weighting functions which characterize the boundary information: this generalized DDGVF snake can conquer the spurious edges raised by artifacts while maintaining the desirable properties of DDGVF of distinguishing the positive and negative boundaries. This is especially helpful for the tasks on hand because the endocardium and epicardium of the LV in MR images can be characterized as positive and negative boundaries. Observed that the left ventricle is roughly a circle, a shape constraint based on circle is introduced into the snake model. This new constraint can prevent the snake contour from being trapped and leaking out so as to maintain the global shape of the snake contour during evolution. In addition, fourth-order PDEs are employed for noise removal. We demonstrate the proposed approach on an in vivo datasct and compare the segmented contours with manual collections;the results show its effectiveness. © 2009 Asian Network for Scientific information.

关键词： Magnetic resonance imaging

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Maximizing intra-individual correlations for face recognition across pose differences

Maximizing intra-individual correlations for face recognitio...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Annan Li Shiguang Shan Xilin Chen Wen Gao Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing of CAS Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media Peking University Beijing China

The variations of pose lead to significant performance decline in face recognition systems, which is a bottleneck in face recognition. A key problem is how to measure the similarity between two image vectors of unequal length that viewed from different pose. In this paper, we propose a novel approach for pose robust face recognition, in which the similarity is measured by correlations in a media subspace between different poses on patch level. The media subspace is constructed by canonical correlation analysis, such that the intra-individual correlations are maximized. Based on the media subspace two recognition approaches are developed. In the first, we transform non-frontal face into frontal for recognition. And in the second, we perform recognition in the media subspace with probabilistic modeling. The experimental results on FERET database demonstrate the efficiency of our approach.

关键词： Face recognition Shape Content addressable storage Robustness Ellipsoids Geometry information processing Computers Length measurement Databases

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Modeling latent aspects for automatic image annotation

Modeling latent aspects for automatic image annotation

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IEEE International Conference on Image processing

作者： Zhixin Li Zhiping Shi Zhiqing Li Zhongzhi Shi Chinese Academy and Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

In this paper, we present an approach based on probabilistic latent semantic analysis (PLSA) to accomplish the tasks of automatic image annotation. In order to model training data precisely, we represent an image as a bag of visual words and employ two PLSA models to capture semantic information from visual and textual modalities respectively. Furthermore, an adaptive learning approach is proposed to combine the aspects learned from both modalities. For each image document, distribution over aspects is fused by different weight in terms of the entropy of its feature distribution. Consequently, the two models are linked with the same distribution over aspects. This structure can predict semantic annotation for an unseen image because it associates visual and textual modalities properly. We compare our approach with several previous approaches on a standard Corel dataset. The experiment results show that our approach performs more effectively and accurately.

关键词： Image retrieval Hidden Markov models Laboratories information processing Computers Image analysis information analysis Training data Entropy Content based retrieval

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Facilitating dynamic web service composition with fine-granularity context management

Facilitating dynamic web service composition with fine-granu...

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IEEE International Conference on Granular computing (GRC)

作者： Wenjia Niu Gang Li Xinghua Yang Xu Han Zhongzhi Shi Chinese Academy of Sciences Beijing Beijing CN School of Information Technology Deakin University VIC Australia Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Context is an important factor for the success of dynamic service composition. Although many context-based AI or workflow approaches have been proposed to support dynamic service composition, there is still an unaddressed issue of the support of fine-granularity context management. In this paper, we propose a granularity-based context model together with an approach to supporting the intelligent context-aware service composing problem. The corresponding case study is provided to show the validity of our approach.

关键词： Web services Context-aware services Artificial intelligence Simple object access protocol Concrete Road transportation technology management Laboratories information processing Computers

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Tolerance Granular computing based on incomplete information system

Tolerance Granular Computing based on incomplete information...

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IEEE International Conference on Granular computing (GRC)

作者： Zhongzhi Shi Zuqiang Meng Yuan Lu The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China College of Computer Electronics and Information Guangxi University Nanning 530004 China College of Computer Guangxi University Nanning China

At present GrC mainly is divided into three categories: computing with words (CW), rough set (RS) and quotient space (QS). From the perspective of essential characteristic of GrC, this demarcation is not comprehensive and accurate. In fact, CW is based on fuzzy granules (fuzzy subset) and both RS and QS are based on disjoint granules, which essentially are equivalence classes, either equal to each other or with empty overlap. In practical application, intersecting granules however need to be handled. Therefore there is another kind of GrC which is based on intersecting granules. This kind of GrC is referred to as tolerance GrC (TGrC) in our work. By constructing a Boolean algebra on super-granular space and a decision algebraic system, this paper will present an incomplete information system-based TGrC. With the TGrC, an example about extracting rules incomplete information is given, so as to show its basic principle.

关键词： information systems information processing Data mining Artificial intelligence Humans Problem-solving Arithmetic Laboratories Computers Educational institutions

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Interpolating fine texturess with fields of experts prior

Interpolating fine texturess with fields of experts prior

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IEEE International Conference on Image processing

作者： Kai Guo Xiaokang Yang Rui Zhang Songyu Yu Hongyuan Zha Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiaotong University Shanghai China College of Computing Georgia Institute of Technology Atlanta GA USA

Traditional image interpolation methods assume that the local spatial structure of the low-resolution (LR) and high-resolution (HR) images are approximately the same, and use edge information of the LR image to estimate the missing pixels. This assumption, however, no longer holds for natural images with fine and dense textures. Consequently, those methods cannot restore dense textures well and tend to generate over-fitting visual effects. In this paper, a learned HR image prior is exploited to overcome the problems. In particular, we use Fields of Experts (FoE) with student's t-distribution experts to model the prior, taking advantage of its representative ability of non-Gaussian natures in images. Then Maximum a Posterior (MAP) estimation incorporating FoE prior is used to estimate the missing pixels. Experimental results compared with traditional interpolation methods demonstrate that our method not only can recover fine details and produce superior PSNR values, but also avoid the visual over-fitting problems.

关键词： Interpolation Pixel Image restoration Visual effects PSNR Layout Image resolution Image communication information processing Biometrics

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High-Precision Discrete Convolution Algorithm Based on Moments

High-Precision Discrete Convolution Algorithm Based on Momen...

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WRI International Conference on Communications and Mobile computing, CMC

作者： Jianguo Liu Zhenbing Liu Guoyou Wang Key Laboratory of Education Ministry for Image Processing and Intelligent Control State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

Convolution is an important and useful operation in the fields of digital signal processing. In this paper, based on the previous work of performing discrete Fourier transform (DFT) via linear sums of discrete moments, we have made development to eliminate multiplications in discrete Fourier transforms by performing appropriate bit operations and shift operations in binary system, which can be implemented by integer additions of fixed points; then using the convolution theorem with the DFT, we compute the convolution with two DFTs, a point-by-point product, and an inverse DFT. Our algorithm involves fewer multiplications and can deal with arbitrary length signals.

关键词： Convolution Signal processing algorithms Discrete Fourier transforms Very large scale integration Algorithm design and analysis Laboratories Educational technology Digital signal processing Mobile communication Mobile computing

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High-Precision and Arbitrary-length Fixed-Point Fast Hartley Transform without Multiplications

High-Precision and Arbitrary-length Fixed-Point Fast Hartley...

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WRI International Conference on Communications and Mobile computing, CMC

作者： Zhenbing Liu Jianguo Liu Guoyou Wang Key Laboratory of Education Ministry for Image Processing and Intelligent Control State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

Discrete Hartley transform (DHT) is an important tool in digital signal processing. In this paper, based on our previous work of performing DHT via linear sums of discrete moments, we have made development to eliminate multiplications in discrete Hartley transforms by performing appropriate bit operations and shift in binary system, which can be implemented by integer additions of fixed points. An efficient and regular systolic array is designed to implement it, and the complexity analysis is also given. Different to other fast Hartley transforms, our algorithm can deal with arbitrary length signals and get high precision. The approach is also applicable to multi-dimensional DHT and DHT inverses.

关键词： Discrete transforms Signal processing algorithms Digital signal processing Systolic arrays Laboratories Educational technology Very large scale integration Hardware Mobile communication Mobile computing

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