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检索条件"机构=The Key Laboratory of Cognitive Computing and Intelligent Information Processing"

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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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An Innovative Tempo Model for Movie Content Analysis

An Innovative Tempo Model for Movie Content Analysis

引用

IEEE International Conference on Networking, Sensing and Control

作者： Anan Liu Zhaoxuan Yang Jiapeng Wu Yongdong Zhang Jintao Li School ofElectronic Engineering Tianjin University TJU Tianjin China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Tianjin University TJU China ICT Chinese Academy and Sciences China

The paper presents a novel tempo model for movie content analysis. We originally propose that tempo indicates the rhythm of both movie scenarios and human perception and focus on the low level features extraction to represent both aspects. By thoroughly analyzing them, we classify the factors of tempo into two sorts. The first is based on the film grammar and we use the low level features of shot length and camera motion to describe filmmaking by directors. The second is based on the human perception and the low level features of motion intensity, motion complexity, audio energy and audio pace are integrated for the formulation of information to describe the viewers' emotional changes to continuously developing storyline. With both factors, tempo is defined and tempo flow plot is derived as the clue of storyline. Then we implement the tempo model for Action scene detection and build a system, SmartMovirPlayer, for hierarchical browse and edit with action concept annotation. The large-scale experiments demonstrate the effectiveness of the tempo model for movie content analysis.

关键词： Motion pictures Humans Layout Performance analysis Rhythm Feature extraction Cameras Large-scale systems Technology planning Laboratories

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Image segmentation using dynamic mechanism based PCNN model

Image segmentation using dynamic mechanism based PCNN model

引用

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

Visual context representation using a combination of feature...

引用

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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Hallucinating facial images and features

Hallucinating facial images and features

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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)

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A Novel Fuzzy Likelihood Measure Algorithm

A Novel Fuzzy Likelihood Measure Algorithm

引用

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

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

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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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Face reconstruction using fixation positions and foveated imaging

Face reconstruction using fixation positions and foveated im...

引用

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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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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