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IFIP Advances in information and Communication technology 2008年 288卷 92-101页

作者： Huang, Rui Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Graduate University of the Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9780387876849

This paper explores four kinds of semantic knowledge to improve keyword- based Web search, including thesauruses, categories, ontologies, and social annotations. These heterogeneous semantic knowledge represent meanings of Web information, thus they can be used to improve search results in respect of semantic relevance. Currently, different semantic search paradigms have been developed for different kind of semantic knowledge respectively. However, how to make the most of all heterogeneous semantic knowledge to optimize Web search is still a big challenge in practice. To these ends, this paper proposes an integrated semantic search mechanism to incorporate textual information and keyword search with heterogeneous semantic knowledge and semantic search. Experiments show that the proposed mechanism effectively integrates heterogeneous semantic knowledge to improve Web search. © 2008, IFIP International Federation for information processing. All rights reserved.

关键词： Ontology

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Mahalanobis distance based Polynomial Segment Model for Chinese Sign Language Recogniton

Mahalanobis distance based Polynomial Segment Model for Chin...

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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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Coarse-to-fine video text detection

Coarse-to-fine video text detection

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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

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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...

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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

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Design sparse features for age estimation using hierarchical face model

Design sparse features for age estimation using hierarchical...

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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 lab.l. 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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Visual context representation using a combination of feature-driven and object-driven mechanisms

Visual context representation using a combination of feature...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jun Miao Lijuan Duan Laiyun Qing Xilin Chen Wen Gao Institute of Computing Technology and the Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China College of Compter Science and Technology Beijing University of Technology Beijing China School of Information Science and Engineering University of the Chinese Academy of Science Beijing China Institute of Degital Media Peking University and the Institute of Computing Technology Chinese Academy and Sciences Beijing China

Visual context between objects is an important cue for object position perception. How to effectively represent the visual context is a key issue to study. Some past work introduced task-driven methods for object perception, which led a large coding quantity. This paper proposes an approach that incorporates feature-driven mechanism into object-driven context representation for object locating. As an example, the paper discusses how a neuronal network encodes the visual context between feature salient regions and human eye centers with as little coding quantity as possible. A group of experiments on efficiency of visual context coding and object searching are analyzed and discussed, which show that the proposed method decreases the coding quantity and improve the object searching accuracy effectively.

关键词： Artificial neural networks Joints

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Image segmentation using dynamic mechanism based PCNN model

Image segmentation using dynamic mechanism based PCNN model

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International Joint Conference on Neural Networks (IJCNN)

作者： Yuanhua Qiao Jun Miao Lijuan Duan Yunfeng Lu College of Applied Science Beijing University of Technology Beijing China Institute of Computing Technology and the Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China College of Computer Science and Technology Beijing University of Technology Beijing China

Pulse-coupled neuron networks (PCNN) can be efficiently applied to image segmentation. However, the performance of segmentation depends on the suitable PCNN parameters, which are obtained by manual experiment, and the effect of the segmentation needs to be improved for images with noise. In this paper, dynamic mechanism based PCNN(DMPCNN) is brought forward to simulate the integrate-and-fire mechanism, and it is applied to segment images with noise effectively. Parameter selection is based on dynamic mechanism. Experimental results for image segmentation show its validity and robustness.

关键词： Neurons Image segmentation Couplings Mathematical model Equations Fires Artificial neural networks

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Face reconstruction using fixation positions and foveated imaging

Face reconstruction using fixation positions and foveated im...

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International Conference on Automatic Face and Gesture Recognition

作者： Fang Fang Zhiguo Ma Laiyun Qing Jun Miao Xilin Chen Wen Gao Harbin Institute of Technology School of Computer Science and Technology China Institute of Computing Technology CASKey Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China Graduate School of Chinese Academy of Sciences Beijing China Institute for Digital Media Peking University China

Face representation is important for face recognition system. Though most popular face representations are based on uniform grid sampling, some recent face recognition systems adopt weighted sampling on the different regions of a face. Psychological analysis of visual attention or human eye fixations on human face images may suggest some cues for face representation. human visual system (HVS) gives different weight to different region of human face via space-variant sampling on fovea and non-uniform distribution of fixations. This paper focuses on the problem of simulation of the foveated imaging phenomenon in HVS, and introduction of foveated imaging method into reconstruction of face in region of interest (ROI) using different fixation sources. We compare the effectiveness of actual fixation on reconstruction of face in ROI with uniform, random distribution fixation as well as fixation generated by artificial model. The experimental results on 100 face images from FRGC [7] data set show that actual fixation positions and model-generated fixation positions reconstruct the face in ROI with considerably better quality. A further analysis on the statistics of fixation positions also shows that the distribution of the fixation points is consistent with the weights of different regions on face images used in some other face recognition systems.

关键词： Image reconstruction Humans Face recognition Layout Content addressable storage Image sampling Psychology Image analysis Statistical analysis Video compression

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A Novel Fuzzy Likelihood Measure Algorithm

A Novel Fuzzy Likelihood Measure Algorithm

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International Conference on Computer Science and Software Engineering

作者： Shifei Ding Fengxiang Jin School of Computer Science and Technology China China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Geoinformation Science and Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781424439027

Similarity measure (PSM) is a kind of measurement that measure the size of similarity between two patterns, it plays a key role in the analysis and research of pattern recognition, machine learning, clustering analysis. This article will firstly study the current PSM theory, point out its application range; secondly, discuss the axiomatic theory of fuzzy likelihood measure, give the frequently-used algorithms of fuzzy likelihood measure that based on axiomatic theory; finally, advance a new kind of fuzzy likelihood function, then establish the fuzzy likelihood measure(FLM) between two fuzzy sets, so as to describe the similar degree between two fuzzy sets. FLM theory not only enriches and improves the PLS theory, and also provides new research methods for the theory research such as pattern recognition, machine learning, clustering analysis and so on.

关键词： Fuzzy sets Pattern recognition Fuzzy set theory Pattern analysis Size measurement Software measurement Fuzzy systems Current measurement Computer science information processing

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People re-detection using Adaboost with sift and color correlogram

People re-detection using Adaboost with sift and color corre...

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IEEE International Conference on Image processing

作者： Lei Hu Shuqiang Jiang Qingming Huang Wen Gao Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media Peking University Beijing China

People re-detection aims at performing re-identification of people who leave the scene and reappear after some time. This is an important problem especially in video surveillance scenarios. In this paper, we present a method of people re-detection within the context of visual sequence in single-camera setup. We consider re-detection as a binary classification problem, where both global and local descriptors are employed for training strong classifier on-line with adaboost to distinguish a newly detected people as tracked or new occurrence. The strong classifier will be updated while match is ascertained. A predetermined classifier with well-chosen threshold is employed as assistant of training examples collection. We test the performance of our approach on 4 different scenes including 51 video sequences taken from the CAVIAR database and 4 video sequences shot by ourselves. The results show that our re-detection algorithm can robustly handle variations in illumination, pose, scale, and camera-view.

关键词： Cameras Layout Surveillance Color Video sequences Data mining Joining processes Histograms information processing Computers

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