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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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Automatically discovering semantic links among documents

Automatically discovering semantic links among documents

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4th International Conference on Semantics, Knowledge, and Grid, SKG 2008

作者： Hai, Zhuge Junsheng, Zhang Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

ISBN: (纸本)9780769534015

Knowing semantic links among documents is the basis for intelligent applications over large-scale document resources. Discovering these semantic links with little human interference is a challenge issue. This paper proposes an approach to automatically discover semantic links in document set based on a probabilistic documentary semantic link network model. The approach has the following advantages: 1) It supports probabilistic relational reasoning. 2) The semantic link networks and relevant rules automatically evolve. 3) It does not rely on any predefined ontology. 4) It can adapt to the update of the adopted techniques. Experiments on document sets of different types (scientific papers and Web pages) and different scales show the proposed approach feasible. The approach can be used to automatically construct semantic overlays on large document sets to support advanced applications like various relational queries on scientific documents. © 2008 IEEE.

关键词： Websites

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Data-deficiency-tolerated method for viewpoint independent sign language recognition

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Jisuanji Xuebao/Chinese Journal of Computers 2009年第5期32卷 953-961页

作者： Wang, Qi Chen, Xi-Lin Wang, Chun-Li Gao, Wen School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Science and Technology Dalian Maritime University Dalian 116026 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

This paper proposes a Sample-Consensus method for viewpoint independent sign language recognition under data deficiency (matched features are possibly deficient with regard to some frame pairs). The proposed method is based on the epipolar geometry and inspired by RANSAC. The basic idea is that all corresponded frames between two sequences of the same sign can be roughly considered as captured synchronously by a virtual stereo vision system and thus they will satisfy the same fundamental matrix. In addition, the fundamental matrix can be estimated from point correspondences contained by some part of corresponding frames. Experimental results demonstrate the efficiency of the proposed method. Moreover, this Sample-Consensus method can be easily extended to some similar problems, such as viewpoint independent activity analysis and rigid-motion analysis.

关键词： Stereo image processing

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The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex

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Science China(Life Sciences) 2008年第10期51卷 902-912页

作者： HU Hong1, LI Su2, WANG YunJiu2, QI XiangLin2 & SHI ZhongZhi1 1 key lab.ratory of intelligent information processing, institute of computing technology, Chinese Academy of Sciences, Beijing 100080, China 2 lab.ratory of Visual information processing, institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 1. Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China 2. Laboratory of Visual Information Processing Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.

关键词： nonlinear dynamical system fuzzy logic visual cortex

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A computational model for feature binding

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Science China(Life Sciences) 2008年第5期51卷 470-478页

作者： SHI ZhiWei1,2, SHI ZhongZhi1, LIU Xi1,2 & SHI ZhiPing1 1 key lab.ratory of intelligent information processing, institute of computing technology, Chinese Academy of Sciences, Beijing 100190, China 2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.

关键词： Binding Problem computational model Bayesian Linking Field Model

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Focused crawling with heterogeneous semantic information

Focused crawling with heterogeneous semantic information

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2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008

作者： Huang, Rui Lin, Fen Shi, Zhongzhi Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China Graduate University Chinese Academy of Sciences 100049 Beijing China

ISBN: (纸本)9780769534961

Focused crawlers selectively retrieve Web documents that are relevant to a predefined set of topics. To intelligently make predictions and decisions about relevant URLs and web pages, different topic models have been introduced to represent topic-specific knowledge. Yet it is difficult to support semantic interoperability among different models. Moreover, some manually specified additional semantic information, such as semantic markups and social annotations, could not be effectively used to improve crawling. This paper proposes to boost focused crawling with four kinds of semantic models and semantic information, including thesauruses, categories, ontologies, and folksonomies. A statistical semantic association model is proposed to integrate different semantic models, represent heterogeneous semantic information, and support semantic relevance computation. A focused crawling framework is developed which adopts both keyword based contents and different kinds of additional information for relevance prediction and ranking. Experiments show that the proposed model and framework effectively integrates heterogeneous semantic information for focused crawling. © 2008 IEEE.

关键词： Websites

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