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International Conference on Natural Computation (ICNC)

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

ISBN: (纸本)9781424445424

Efficient coding hypothesis provides a quantitative relationship between environmental statistics and neural processing. In this paper, we put forward a novel sparse coding model based on structural similarity (SS_SC) for natural image feature extraction. The advantage for our model is to be able to preserve structural information from a scene, which human visual perception is highly adapted for. Using the proposed sparse coding model, the validity of image feature extraction is testified. Furthermore, inspired by Bayesian decision which is extensively used for classification, employing SS_SC we propose an algorithm for image classification. Compared with standard sparse coding (SC) model, the experimental results show that the quality of reconstructed images obtained by our method outperforms the SC method. Moreover, SS_SC model evidently enhances the classification accuracy.

关键词： Image classification Image coding Feature extraction Statistics Layout Humans Visual perception Testing Bayesian methods Classification algorithms

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Detection of Front-View Vehicle with Occlusions Using AdaBoost

Detection of Front-View Vehicle with Occlusions Using AdaBoo...

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International Conference on information Engineering and Computer Science (ICIECS)

作者： Chunpeng Wu Lijuan Duan Jun Miao Faming Fang Xuebin Wang College of Computer Sciences Beijing University of Technology Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424449934

In this paper, we propose a vehicle detection method based on AdaBoost. We focus on the detection of front-view car and bus with occlusions on highway. Samples with different occlusion situations are selected into the training set. By using basic and rotated Haar-like features extracted from the samples in the set, we train an AdaBoost-based cascade vehicle detector. The performance tests on static images and short time videos show that (1) our approach detects cars more effectively than buses (2) the real-time detection of our method on video proceeds at 30 frames per second.

关键词： Vehicle detection Feature extraction Prototypes Detectors Videos Educational institutions Road vehicles Face detection Boosting lab.ratories

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Model-based bridge recognition in high resolution SAR image

Model-based bridge recognition in high resolution SAR image

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MIPPR 2009 - Automatic Target Recognition and Image Analysis: 6th International Symposium on Multispectral Image processing and Pattern Recognition

作者： Pei, Deli Sun, Fuchun Wang, Hongqiao Chen, Ning Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Lab. of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China Xi'an High Tech. Research Institute Xi'an Shanxi 710025 China

ISBN: (纸本)9780819478061

A new bridge recognition method in Synthetic Aperture Radar (SAR) image using bridge model and SVM is presented in this paper. Firstly, water region is extracted from original SAR image by self-adapt segmentation and mathematic morphological method. Then based on bridge model, the bridge candidates in water region can be found out and their texture feature can also be ***, with the usage of SVM, whether these objects are bridges or not can be identified and the real bridges can be mark ed in the SAR image, as well as the corresponding information such as position. Experiment results show that, with the help of water region segmentation and bridge model, the efficiency of the algorithm is greatly promoted, meanwhile, the recognition accuracy is guaranteed by high quality classifier of SVM. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Synthetic aperture radar

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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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A Dynamic Description Logic-Based Formalism for RBAC

A Dynamic Description Logic-Based Formalism for RBAC

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International Conference on Computer Sciences and Convergence information technology (ICCIT)

作者： Li Ma Shilong Ma Jianghua Lv Yuefei Sui Department of Computer Science Beihang University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424452446

Applications in the open and dynamic environment become more intelligent and complicated. To secure these applications is a big challenge. RBAC model, as a de facto standard in access control field, is widely used in many applications. But the lack of dynamic and formal method to describe RBAC makes the model can't completely adapt to the open and dynamic environment. To solve this problem, we introduce a three level RBAC model which unifies the administrative components, the administrative actions and the regular RBAC components, and also proposes a dynamic description logic, called DDL RBAC , to formalize the three level model. Based on the formal description of RBAC with DDL RBAC , an executable action decision algorithm to guarantee the dynamic consistency of systems is also presented.

关键词： Logic Access control Authorization Data security information security Mathematical model Permission information technology Computer science lab.ratories

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A novel two-tier Bayesian based method for hair segmentation

A novel two-tier Bayesian based method for hair segmentation

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IEEE International Conference on Image processing

作者： Dan Wang Shiguang Shan Wei Zeng Hongming Zhang Xilin Chen 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

In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior probabilities (HOPP) with a generic hair color model (GHCM) to obtain some reliable hair seed pixels. These initial seeds are further propagated to their neighborhood pixels by utilizing segmentation results of mean shift, to obtain more seeds. In the second tier, all of these selected seeds are used to train a hair-specific Gaussian model, which are combined with HOPP to build the second Bayesian model for pixel classification. Mean shift results are further utilized to remove holes and spread hair regions. The experimental results illustrate the effectiveness of our approach.

关键词： Bayesian methods Hair Image segmentation Content addressable storage Face detection information processing Computers National electric code Diversity reception Pixel

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Image Reconstruction by Sparse Coding and Selective Attention

Image Reconstruction by Sparse Coding and Selective Attentio...

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Congress on Image and Signal processing, CISP

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

Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes in the viewpoint of statistics. In this paper, inspired by the research of selective attention in psychology, we propose a novel self-adaptive algorithm to further reduce the activated variables. The experimental results show that the quality of reconstructed images obtained by our method is satisfying. Moreover, combining selective attention and sparse coding our method evidently decreases the number of coefficients which may be activated and preserves the main information at the same time.

关键词： Image reconstruction Image coding Neurons information processing Layout Vectors lab.ratories Computers Codes Statistics

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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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Learning long term face aging patterns from partially dense aging databases

Learning long term face aging patterns from partially dense ...

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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 availab.e 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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Fast car detection using image strip features

Fast car detection using image strip features

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Wei Zheng Luhong Liang Graduate School of Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy of Sciences (CAS) Beijing 100190 China

This paper presents a fast method for detecting multi-view cars in real-world scenes. Cars are artificial objects with various appearance changes, but they have relatively consistent characteristics in structure that consist of some basic local elements. Inspired by this, we propose a novel set of image strip features to describe the appearances of those elements. The new features represent various types of lines and arcs with edge-like and ridge-like strip patterns, which significantly enrich the simple features such as haar-like features and edgelet features. They can also be calculated efficiently using the integral image. Moreover, we develop a new complexity-aware criterion for RealBoost algorithm to balance the discriminative capability and efficiency of the selected features. The experimental results on widely used single view and multi-view car datasets show that our approach is fast and has good performance.

关键词： Strips Face detection Object detection Biological system modeling Deformable models Computer vision Content addressable storage Support vector machines Humans Wheels

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