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检索条件"机构=Key Laboratory for Digital Imaging Processing and Intelligent Computing"

共 143 条记录，以下是131-140 订阅

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Hallucinating facial images and features

Hallucinating facial images and features

引用

作者： Li, Bo Chang, Hong Shan, Shiguang Chen, Xilin Gao, Wen Harbin Institute of Technology Harbin China Digital Media Research Center Institute of Computing Tech. CAS Beijing China Key Laboratory of Intelligent Information Processing CAS Beijing China Digital Media Institute Peking University Beijing China

ISBN: (纸本)9781424421756

In facial image analysis, image resolution is an important factor which has great influence on the performance of face recognition systems. As for low-resolution face recognition problem, traditional methods usually carry out super-resolution firstly before passing the super-resolved image to a face recognition system. In this paper, we propose a new method which predicts high-resolution images and the corresponding features simultaneously. More specifically, we propose "feature hallucination" to project facial images with low-resolution into an expected feature space. As a result, the proposed method does not require super-resolution as an explicit preprocessing step. In addition, we explore a constrained hallucination that considers the local consistency in the image grid. In our method, we use the index of local visual primitives [5] as features and a block-based histogram distance to measure the similarity for the face recognition. Experimental results on FERET face database verify that the proposed method can improve both visual quality and recognition rate for low-resolution facial images. © 2008 IEEE.

关键词： Image resolution

来源：评论

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Hierarchical background subtraction using local pixel clustering

Hierarchical background subtraction using local pixel cluste...

引用

作者： Zhong, Bineng Yao, Hongxun Shan, Shiguang Chen, Xilin Gao, Wen Department of Computer Science and Engineering Harbin Institute of Technology China Digital Media Research Center Institute of Computing Tech. CAS Beijing China Key Laboratory of Intelligent Information Processing CAS Beijing China Digital Media Institute Peking University Beijing China

ISBN: (纸本)9781424421756

We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our algorithm combines a per-pixel with a per-region background model in a hierarchical manner, which accentuates the advantages of each. This is a natural combination because the two models have complementary strengths. The per-pixel background model is achieved by mixture of Gaussians Models (GMM) with RGB feature. Although precisely describing background change in high resolution, it suffers from the sensitivity to quick variations in dynamic environment. To tolerate these quick variations, we further develop a novel GMM based per-region background model, which is updated by the cluster centers obtained from a k-means clustering of the pixels' RGB feature in the region. Numerical and qualitative experimental results on challenging videos demonstrate the robustness of the proposed method. © 2008 IEEE.

关键词： Pixels

来源：评论

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暂无评论

Coarse-to-fine video text detection

Coarse-to-fine video text detection

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Guangyi Miao Qingming Huang Shuqiang Jiang Wen Gao Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media Peking University Beijing China

In this paper, we propose an effective coarse-to-fine algorithm to detect text in video. Firstly, in coarse-detection section, stroke filter is employed to detect all candidate stroke pixels, and then a fast region growing method is developed to connect these pixels into regions which are further separated into candidate text lines by projection operation. Secondly, in fine-detection section, correct text regions are selected from candidate ones by support vector machine (SVM) model and stroke features, and text regions in multi-resolution are integrated. Finally, the result is optimized significantly according to temporal correlation information. Experimental results show that our algorithm achieves real-time performance and is robust for the variation of language, font, size, color and noise of text caused by low frame resolution in video.

关键词： Pixel Support vector machines Feature extraction Classification algorithms Filtering algorithms Streaming media Correlation

来源：评论

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Illumination transfer using homomorphic wavelet filtering and its application to light-insensitive face recognition

Illumination transfer using homomorphic wavelet filtering an...

引用

International Conference on Automatic Face and Gesture Recognition

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

In this paper, we propose a novel homomorphic wavelet filtering based illumination transfer technique to change the dominant lighting of one face image (source face image) to another face image (reference face image ). Specifically, in the proposed method, based on the ldquoreflectance-illuminationrdquo imaging model, we first obtain an approximate estimate of the illumination component of the face image through a wavelet-based Multiresolution Analysis (MRA) in the logarithm domain of the input image. Then, a homomorphic filtering procedure is applied to improve the accuracy of the illumination component estimation. Finally, the source face image is re-lighted by substituting the estimated illumination component of the reference image for that of the source image. The proposed method is entirely an image processing based method without any 3D geometry modeling steps, so it is simple but effective. The method is also applied easily to illumination invariant face recognition by transferring a standard illumination to all the face images. Experimental results show that our method is quite effective for both illumination transfer and illumination-insensitive face recognition.

关键词： Lighting Filtering Face recognition Solid modeling Geometry Face detection Facial animation Multiresolution analysis Image processing digital filters

来源：评论

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Parzen Discriminant Analysis

Parzen Discriminant Analysis

引用

International Conference on Pattern Recognition

作者： Youhan Fang Shiguang Shan Hong Chang Xilin Chen Wen Gao Chinese Academy of Sciences Beijing China Digital Media Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing CAS Beijing China Digital Media Institute Peking University Beijing China

ISBN: (纸本)9781424421749

In this paper, we propose a non-parametric discriminant analysis method (no assumption on the distributions of classes), called Parzen discriminant analysis (PDA). Through a deep investigation on the non-parametric density estimation, we find that minimizing/maximizing the distances between each data sample and its nearby similar/dissimilar samples is equivalent to minimizing an upper bound of the Bayesian error rate. Based on this theoretical analysis, we define our criterion as maximizing the average local dissimilarity scatter with respect to a fixed average local similarity scatter. All local scatters are calculated in fixed size local regions, resembling the idea of Parzen estimation. Experiments in UCI machine learning database show that our method impressively outperforms other related neighbor based non-parametric methods.

关键词： Error analysis Scattering Upper bound Linear discriminant analysis Information analysis Bayesian methods Gaussian distribution Personal digital assistants Content addressable storage Performance analysis

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Hallucinating facial images and features

Hallucinating facial images and features

引用

International Conference on Pattern Recognition

作者： Bo Li Hong Chang Shiguang Shan Xilin Chen Wen Gao Harbin Institute of Technology Harbin China Institute of Computing Tech. CAS Digital Media Research and Development Center Beijing China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China Digital Media Institute Peking University Beijing China

ISBN: (纸本)9781424421749

In facial image analysis, image resolution is an important factor which has great influence on the performance of face recognition systems. As for low-resolution face recognition problem, traditional methods usually carry out super-resolution firstly before passing the super-resolved image to a face recognition system. In this paper, we propose a new method which predicts high-resolution images and the corresponding features simultaneously. More specifically, we propose ldquofeature hallucinationrdquo to project facial images with low-resolution into an expected feature space. As a result, the proposed method does not require super-resolution as an explicit preprocessing step. In addition, we explore a constrained hallucination that considers the local consistency in the image grid. In our method, we use the index of local visual primitives as features and a block-based histogram distance to measure the similarity for the face recognition. Experimental results on FERET face database verify that the proposed method can improve both visual quality and recognition rate for low-resolution facial images.

关键词： Face recognition Image resolution Strontium Image reconstruction Image analysis Content addressable storage Image recognition Interpolation Face detection Rendering (computer graphics)

来源：评论

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Mahalanobis distance based Polynomial Segment Model for Chinese Sign Language Recogniton

Mahalanobis distance based Polynomial Segment Model for Chin...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Yu Zhou Xilin Chen Debin Zhao Hongxun Yao Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media Peking University Beijing China

Sign Language Recognition (SLR) systems are mostly based on Hidden Markov Model (HMM) and have achieved excellent results. However, the assumption of frame independence in HMM makes it inconsistent with the characteristic of strong temporal correlation in sign language signals. Polynomial Segment Model (PSM) explicitly represents the temporal evolution of sign language features as a Gaussian process with time-varying parameters. In this paper PSM is first introduced to SLR framework to solve the temporal correlation problem. Considering the correlation among the coefficients of polynomial trajectorypsilas different orders, Mahalanobis distance is used as the classification criterion to evaluate the likelihood of test data. Experimental results show that our method outperform the conventional HMM methods by 6.81% in recognition accuracy.

关键词： Hidden Markov models Handicapped aids Distance measurement Trajectory Vocabulary Euclidean distance Polynomials

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Hierarchical background subtraction using local pixel clustering

Hierarchical background subtraction using local pixel cluste...

引用

International Conference on Pattern Recognition

作者： Bineng Zhong Hongxun Yao Shiguang Shan Xilin Chen Wen Gao Department of Computer Science and Engineering Harbin Institute of Technology Digital Media Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China Digital Media Institute Peking University Beijing China

ISBN: (纸本)9781424421749

We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our algorithm combines a per-pixel with a per-region background model in a hierarchical manner, which accentuates the advantages of each. This is a natural combination because the two models have complementary strengths. The per-pixel background model is achieved by mixture of Gaussians models (GMM) with RGB feature. Although precisely describing background change in high resolution, it suffers from the sensitivity to quick variations in dynamic environment. To tolerate these quick variations, we further develop a novel GMM based per-region background model, which is updated by the cluster centers obtained from a k-means clustering of the pixelspsila RGB feature in the region. Numerical and qualitative experimental results on challenging videos demonstrate the robustness of the proposed method.

关键词： Autoregressive processes Robustness Object detection Videos Layout Smart pixels Content addressable storage Gaussian processes Lighting Cameras

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Design sparse features for age estimation using hierarchical face model

Design sparse features for age estimation using hierarchical...

引用

International Conference on Automatic Face and Gesture Recognition

作者： Jinli Suo Tianfu Wu Songchun Zhu Shiguang Shan Xilin Chen Wen Gao Chinese Academy and Sciences China Lotus Hill Institute of Computer Vision and Information Science China Key Laboratory of Intelligent Information Processing of CAS Institute of Computing Technology Chinese Academy of Sciences Beijing China Institute of Digital Media Peking University China

A key point in automatic age estimation is to design feature set essential to age perception. To achieve this goal, this paper builds up a hierarchical graphical face model for faces appearing at low, middle and high resolution respectively. Along the hierarchy, a face image is decomposed into detailed parts from coarse to fine. Then four types of features are extracted from this graph representation guided by the priors of aging process embedded in the graphical model: topology, geometry, photometry and configuration. On age estimation, this paper follows the popular regression formulation for mapping feature vectors to its age label. The effectiveness of the presented feature set is justified by testing results on two datasets using different kinds of regression methods. The experimental results in this paper show that designing feature set for age estimation under the guidance of hierarchical face model is a promising method and a flexible framework as well.

关键词： Aging Feature extraction Active appearance model Face detection Spatial databases Skin Hair Content addressable storage Computer vision Humans

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Recovering 3D facial shape via coupled 2D/3D space learning

Recovering 3D facial shape via coupled 2D/3D space learning

引用

International Conference on Automatic Face and Gesture Recognition

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

This paper presents a method for recovering 3D facial shape from single image via learning the relationship between the 2D intensity images and the 3D facial shapes. With a coupled training set, the intensity images and their corresponding facial shapes make up two vector spaces respectively. But only the correlated components in both spaces are useful for inference, so there must be embedded hidden subspaces in each space which preserve the inter-space correlation information. Thus by learning the projection onto hidden subspaces based on maximum correlation criteria and optimizing the linear transform between the hidden spaces, 3D facial shape is inferred from the intensity image. The effectiveness of the method is demonstrated on both synthesized and real world data.

关键词： Content addressable storage Humans Face Lighting Light sources Statistics Deformable models Image reconstruction Active shape model Space technology

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