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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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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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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 Collaboration Mathematical model Euclidean distance Extraterrestrial measurements Particle measurements Fitting Game theory

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Sigma Set: A small second order statistical region descriptor

Sigma Set: A small second order statistical region descripto...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiaopeng Hong Hong Chang Shiguang Shan Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology China Institute of Computing Technology Chinese Academy and Sciences China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China Institute of Computing Technology Chinese Academy of Sciences China Institute for Digital Media Peking University China

Given an image region of pixels, second order statistics can be used to construct a descriptor for object representation. One example is the covariance matrix descriptor, which shows high discriminative power and good robustness in many computer vision applications. However, operations for the covariance matrix on Riemannian manifolds are usually computationally demanding. This paper proposes a novel second order statistics based region descriptor, named “Sigma Set”, in the form of a small set of vectors, which can be uniquely constructed through Cholesky decomposition on the covariance matrix. Sigma Set is of low dimension, powerful and robust. Moreover, compared with the covariance matrix, Sigma Set is not only more efficient in distance evaluation and average calculation, but also easier to be enriched with first order statistics. Experimental results in texture classification and object tracking verify the effectiveness and efficiency of this novel object descriptor.

关键词： Robustness Histograms Fractals Lighting Statistics Solids Computer science Power engineering and energy Mathematics Power engineering computing

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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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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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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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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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Personalized multimedia web summarizer for tourist 08

Personalized multimedia web summarizer for tourist

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17th International Conference on World Wide Web 2008, WWW'08

作者： Wu, Xiao Li, Jintao Zhang, Yongdong Tang, Sheng Neo, Shi-Yong Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Department of Computer Science National University of Singapore Singapore

ISBN: (纸本)9781605580852

In this paper, we highlight the use of multimedia technology in generating intrinsic summaries of tourism related information. The system utilizes an automated process to gather, filter and classify information on various tourist spots on the Web. The end result present to the user is a personalized multimedia summary generated with respect to users queries filled with text, image, video and real-time news made retrievable for mobile devices. Preliminary experiments demonstrate the superiority of our presentation scheme to traditional methods.

关键词： Automation

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Robust appearance-based method for head pose estimation

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Ruan Jian Xue Bao/Journal of Software 2009年第6期20卷 1651-1663页

作者： Ma, Bing-Peng Shan, Shi-Guang Chen, Xi-Lin Gao, Wen Key Laboratory of Intelligent Information Processing Chinese Acad. of Sci. Beijing 100190 China Institute of Computing Technology Chinese Acad. of Sci. Beijing 100190 China Graduate University Chinese Acad. of Sci. Beijing 100049 China School of Electronic Engineering and Computer Science Peking University Beijing 100871 China

This paper proposes a new pose estimation method based on the appearance of 2D head image. First, the 1D Gabor filters are used to extract the features on the raw images. Compared with the traditional 2D Gabor represents, the 1D Gabor represents are more closely related to the head pose, while the advantages of computation and storage are obvious. Second, for the extracted features, a new method, named kernel local fisher discriminant analysis, is applied to eliminate the multimodal problem, while at the same time enhance the discrimination ability. Experimental results show that the proposed method is effective for pose estimation. It must be pointed out that the generalizability of the proposed method is illustrated by the impressive performance when the training dataset and the testing dataset are heterogeneous. © by Institute of Software, the Chinese Academy of sciences. All rights reserved.

关键词： Gabor filters

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