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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 lab.ratories 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 lab.ratories information processing Computers

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Mechanism for maximizing area-centric coding gains in wireless multihop networks

Mechanism for maximizing area-centric coding gains in wirele...

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2009 IEEE International Conference on Communications, ICC 2009

作者： Yan, Yan Baoxian, Zhang Zhuang, Zhao Xiaojun, Shen Jian, Ma Institution of Computing Technology Chinese Academy of Sciences Beijing 100080 China CCCE Graduate University Chinese Academy of Sciences Beijing 100049 China Key Lab. of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China School of Computing and Engineering University of Missouri Kansas City MO 64110 United States Nokia Research Center Beijing 100176 China

ISBN: (纸本)9781424434350

Localized network coding is a promising technique to improve the throughput of wireless multihop networks with multiple concurrent unicast sessions. However, most existing mechanisms in this field perform network coding without considering the maximization of joint coding gain among neighboring nodes. In this paper, we study how to improve network performance by maximizing the area-centric coding gains in wireless networks. To achieve this goal, we design an efficient coding-aware transmission scheduling mechanism. Simulation results show that our mechanism can remarkably improve the network throughput as compared with existing mechanisms. ©2009 IEEE.

关键词： Network coding

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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 lab.ratories Computers Educational institutions

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A ROI quality adjustable rate control scheme for low bitrate video coding

A ROI quality adjustable rate control scheme for low bitrate...

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Picture Coding Symposium, PCS

作者： Ling Yang Li Zhang Siwei Ma Debin Zhao Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media School of Electronic Engineering and Computer Science Peking University Beijing China Department of Computer Science and Engineering Harbin Institute of Technology Harbin China

This paper proposed a novel Region of Interest (ROI) based rate control algorithm for video communication systems, in which the subjective quality of ROI can be adjusted according to users' requirements. In the proposed scheme, in order to analyze the relationship between subjective quality and encoding parameters, a structural similarity index map - quantization parameter (SSIM-QP) model is established. Through this relation, the possible visual quality range of ROI is defined according to the range of ROI QP, which is predicted by rate control algorithm. Then, with interest levels being identified within the visual quality range, resources allocated to ROI is determined. Finally, considering both the quality of ROI and the entire frame, resource allocation is slightly adjusted. Experimental results demonstrate that the subjective visual quality of ROI in our proposed scheme can be adjustable improved compared to the existing rate control algorithms.

关键词： Bit rate Video coding Quadratic programming Humans Computer science Quantization Resource management Videoconference PSNR Data mining

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Single vs. population cell coding: Gaze movement control in target search

Single vs. population cell coding: Gaze movement control in ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jun Miao Laiyun Qing Lijuan Duan Baixian Zou Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China School of Information Science and Engineering Chinese Academy of Sciences Beijing China College of Computer Science and Technology University of Technology Beijing China Department of Information Science and Technology College of Art and Science Beijing Union Technology Beijing China

Gaze movement plays an important role in human visual search system. In literature, the winner-take-all method is wildly used to simulate the controlling of the gaze movement. The winner-take-all is a type of single-cell coding method, which uses one cell (grandmother cell) or one response to represent an object. However, eye movement is affected by the visual context which includes more than one object in images, especially in target search. Therefore, we propose to use the population coding with more than one response rather than the single-cell coding on gaze movement control. The proposed method is supported by the theoretical analysis and experiments on a real image database which show the population-cell-coding improves the target locating accuracy by 44.4% only at the cost of coding 22.4% more information than that of single-cell-coding.

关键词： Humans Image coding Image databases Costs information science Educational institutions Biological neural networks Control systems Image analysis information analysis

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Boid particle swarm optimisation

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International Journal of Innovative computing and Applications 2009年第2期2卷 78-85页

作者： Cui, Zhihua Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No. 6 Kexueyuan South Rd. Zhongguancun Haidian District Beijing 100190 China Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology No. 66 Waliu Rd. Wanbailin District Taiyuan Shanxi 030024 China

Particle swarm optimisation (PSO) is a novel population-based stochastic optimisation algorithm inspired by the Reynolds' boid model. The original biological background of boid obeys three basic simple steering rules: separation, alignment and cohesion. However, to promote a simple update equation, none of these rules of boid model is employed by PSO methodology. Due to the weakness of biological background of PSO, in this paper, a new variant of PSO, boid particle swarm optimisation (BPSO), is designed in which cohesion rule and alignment rule are both employed to improve the performance. In BPSO, each particle has two motions: divergent motion and convergent motion. For divergent motion, each particle adjusts its moving direction according to the alignment direction and the cohesion direction, as well as in convergent motion, the original update equation of the standard version of PSO is used. To make a motion transition, a threshold is introduced to make the divergent motion is employed in the first period, whereas the convergent motion is used in the final stage. To testify the efficiency, several unconstrained benchmarks are used to compare. Simulation results show the proposed variant is more effective and efficient than other two variants of PSO when solving multi-modal high-dimensional numerical problems. Copyright © 2009 Inderscience Enterprises Ltd.

关键词： Alignment

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A Novel Hebbian Rules Based Method for Computation of Sparse Coding Basis Vectors

A Novel Hebbian Rules Based Method for Computation of Sparse...

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International Conference on Natural Computation (ICNC)

作者： Baixian Zou Jun Miao Xiaoling Yang Lijuan Duan Yuanhua Qiao Department of Information Science and Technology College of Arts and Science of Beijing Union University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Tianjin Academy of Agricultural Science Tianjin China College of Computer Science and Technology Beijing Beijing China College of Applied Science Beijing University of Technology Beijing China

Sparse coding has high-performance encoding and ability to express images, sparse encoding basis vector plays a crucial role. The computational complexity of the most existing sparse coding basis vectors of is relatively large. In order to reduce the computational complexity and save the time to train basis vectors. A new Hebbian rules based method for computation of sparse coding basis vectors is proposed in this paper. A two-layer neural network is constructed to implement the task. The main idea of our work is to learn basis vectors by removing the redundancy of all initial vectors using Hebbian rules. The experiments on natural images prove that the proposed method is effective for sparse coding basis learning. It has the smaller computational complexity compared with the previous work.

关键词： Computer science Stability Space technology Collab.ration Mathematical model Euclidean distance Extraterrestrial measurements Particle measurements Fitting Game theory

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Fea-Accu cascade for face detection

Fea-Accu cascade for face detection

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IEEE International Conference on Image processing

作者： Shengye Yan Shiguang Shan Xilin Chen Wen Gao Chinese Academy and Sciences Beijing China Institute of Computing Technology Digital Media Research Center Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China School of EE & CS Peking University Beijing China

Aiming at unloading the high training time burden of the popular cascaded classifier, in this paper, a novel cascade structure called Fea-Accu cascade is proposed. In Fea-Accu cascade training, the times of feature selection are largely reduced by enhancing the correlation among different stage classifiers of the cascaded classifier. In detail, for each stage classifier, before selecting new features out, the features selected out by previous stage classifiers are reused through creating new corresponding weak classifiers. To verify the efficiency and effectiveness of the proposed method, experiment is designed on frontal face detection problem. The experimental results show that it can largely reduce the training time. A frontal face detector with state-of-the-art classification performance can be learned in less than 10 hours.

关键词： Face detection Detectors Content addressable storage Design methodology information processing Computer vision Cameras Robustness Boosting Computer architecture

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