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检索条件"机构=Institute of Pattern Recognition & Image Processing"

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Gabor-Based Discriminative Common Vectors for Gait recognition

Gabor-Based Discriminative Common Vectors for Gait Recogniti...

引用

Congress on image and Signal processing, CISP

作者： Xiaochao Yang Ji Dai Yue Zhou Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China School of Information and Electrical Engineering China University of Mining and Technology China

This paper presents a novel method for identity recognition based on the 2D gait representation: Gait Energy image (GEI) which is the averaged silhouette over one gait cycle. An ensemble of Gabor kernels is first convolved with GEI to extract discriminative feature. The obtained Gabor gait representation is then projected into lower dimensional subspace using discriminative common vectors (DCV) analysis. The final classification is performed in this subspace. The proposed method is tested on the USF HumanID Database. Experimental results show that Gabor-based method can improve recognition rate, and DCV is superior to other traditional dimensional reduction algorithm in the gait recognition application.

关键词： image recognition Biometrics Legged locomotion Hidden Markov models pattern recognition Kernel Joints image processing Feature extraction Video sequences

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Subspace Analysis Methods plus Motion History image for Human Action recognition

Subspace Analysis Methods plus Motion History Image for Huma...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Chunhua Du Qiang Wu Jie Yang Xiangjian He Yan Chen Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China School of Computing & Communications Sydney University of Technology Broadway Australia

This paper proposes a new human action recognition method which deals with recognition task in a quite different way when compared with traditional methods which use sequence matching scheme. Our method compresses a sequence of an action into a Motion History image (MHI) on which low-dimensional features are extracted using subspace analysis methods. Unlike other methods which use a sequence consisting of several frames for recognition, our method uses only a MHI per action sequence for recognition. Obviously, our method avoids the complexity as well as the large computation in sequence matching based methods. Encouraging experimental results on a widely used database demonstrate the effectiveness of the proposed method.

关键词： image analysis image motion analysis Motion analysis History Humans image recognition image coding Feature extraction image sequence analysis Databases

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Extracting key postures using radon transform

Extracting key postures using radon transform

引用

International Conference on image and Vision Computing New Zealand, IVCNZ

作者： Yan Chen Qiang Wu Xiangjian He Chunhua Du Jie Yang Centre for Innovation in IT Services and Application (iNext) University of Technology Australian Institute of Image Processing and Pattern Recognition Shandong Jiaotong University Shanghai China

Human key posture extraction will benefit for human action recognition, human action retrieval, human behaviour understanding and so on. This paper proposes an approach to select key postures from a human action video based on Radon transform. Cluster is used on the Radon transform to select the final key postures of human action video. The approach does not require motion extraction from the human action video. The experiments results show that the proposed approach is efficient.

关键词： Humans Data mining pattern recognition Entropy Technological innovation image processing Shape Speech analysis Information retrieval Tracking

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Ant Colony Optimization Algorithm for Feature Selection and Classification of Multispectral Remote Sensing image

Ant Colony Optimization Algorithm for Feature Selection and ...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Lintao Wen Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

In classification of a multispectral remote sensing image, it is usually difficult to obtain higher classification accuracy if we only consider the image's spectral feature or texture feature alone. In this paper, we present a new approach by applying the Ant Colony Optimization (ACO) algorithm to find a multi-feature vector composed of spectral and texture features in order to get a better result in the classification. The experimental results show that ACO algorithm is helpful in subset searching of the features used to classify the multispectral remote sense image. Using the combination of the spectral and texture features obtained by ACO in classification always produces a better accuracy.

关键词： Ant colony optimization Remote sensing Remote monitoring Multispectral imaging image analysis Data mining Feature extraction Entropy image processing pattern recognition

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Experimental Study of Discriminant Method with Application to Fault-Prone Module Detection

Experimental Study of Discriminant Method with Application t...

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International Conference on Computational Intelligence and Security

作者： Gege Guo Ping Guo School of Computer Science and Technology Beijing Institute of Technology Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781424441969

Some techniques have been applied to improving software quality by classifying the software modules into fault-prone or non fault-prone categories. This can help developers focus on some high risk fault-prone modules. In this paper, a distribution-based Bayesian quadratic discriminant analysis (D-BQDA) technique is experimental investigated to identify software fault-prone modules. Experiments with software metrics data from two real projects indicate that this technique can classify software modules into a proper class with a lower misclassification rate and a higher efficiency.

关键词： Fault detection Software quality Support vector machines Support vector machine classification pattern recognition Software metrics Bayesian methods Fault diagnosis Software performance Computational intelligence

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Gabor phase embedding of Gait Energy image for identity recognition

Gabor phase embedding of Gait Energy Image for identity reco...

引用

International Conference on Computer and Information Technology (CIT)

作者： Xiaochao Yang Tianhao Zhang Yue Zhou Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Computing Hong Kong Polytechnic University Hong Kong China

This paper proposes an effective gait recognition approach based on the Gait Energy image (GEI) representation. Synthetic GEI samples are first generated to address the problem of lacking training data. Then the Gabor phase spectrum of GEI which was ignored in the previous work is utilized as the input feature, and it is subsequently embedded into a low dimensional manifold by locality preserving projections to perform classification. The proposed recognition approach is evaluated on the USF HumanID database. Experimental results show that our approach outperforms other automatic algorithms in terms of recognition accuracy.

关键词： Principal component analysis Probes Training Kernel Convolution Face Databases

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Comparison of discriminant analysis methods applied to diffractive optically variable image

Comparison of discriminant analysis methods applied to diffr...

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IEEE International Workshop on Anti-counterfeiting, Security, Identification, ASID

作者： Rukun Hu Youji Feng Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

As a kind of powerful anti-counterfeiting device, diffractive optically variable image (DOVI) has been developed and widely used in information security field. However, the identification of DOVI today by bare eyes is not reliable. In this paper we investigate the recognition of DOVI with machine learning method, and five kinds of algorithms, namely quadratic discriminate analysis (QDA), linear discriminate analysis (LDA), regularized discriminate analysis (RDA), leave-one-out covariance matrix estimate (LOOC), and Kullback-Leibler information measure based method (KLIM) are applied to the recognition of DOVI. Considering both time cost and correct classification rate, KLIM classifier exceeds others.

关键词： image analysis Optical diffraction Information analysis Algorithm design and analysis Optical devices Information security Eyes Learning systems Machine learning algorithms Linear discriminant analysis

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The Application of A Novel Target Region Extraction Model Based on Object-Accumulated Visual Attention Mechanism

The Application of A Novel Target Region Extraction Model Ba...

引用

International Conference on Natural Computation (ICNC)

作者： Jie Xiao Chao Cai Mingyue Ding Chengping Zhou Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.

关键词： Data mining Object detection Computer applications Chaos pattern recognition Artificial intelligence Laboratories image processing Intelligent control Airports

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Software quality prediction using Affinity Propagation algorithm

Software quality prediction using Affinity Propagation algor...

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International Joint Conference on Neural Networks (IJCNN)

作者： Bingbing Yang Qian Yin Shengyong Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China Laboratory of Computer Science Institute of Software Chinese Academy and Sciences Beijing China

Software metrics are collected at various phases of the software development process. These metrics contain the information of the software and can be used to predict software quality in the early stage of software life cycle. Intelligent computing techniques such as data mining can be applied in the study of software quality by analyzing software metrics. Clustering analysis, which can be considered as one of the data mining techniques, is adopted to build the software quality prediction models in the early period of software testing. In this paper, a new clustering method called Affinity Propagation is investigated for the analysis of two software metric datasets extracted from real-world software projects. Meanwhile, K-Means clustering method is also applied for comparison. The numerical experiment results show that the Affinity Propagation algorithm can be applied well in software quality prediction in the very early stage, and it is more effective on reducing Type II error.

关键词： Software Software quality Clustering methods Clustering algorithms Software metrics Testing Software algorithms

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Ancient document analysis based on text line extraction

Ancient document analysis based on text line extraction

引用

International Conference on pattern recognition

作者： Florian Kleber Robert Sablatnig Melanie Gau Heinz Miklas Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria Institute for Slavonic Studies University of Technology Vienna Vienna Austria

ISBN: (纸本)9781424421749

In order to preserve our cultural heritage and for automated document processing libraries and national archives have started digitizing historical documents. In the case of degraded manuscripts (e.g. by mold, humidity, bad storage conditions) the text or parts of it can disappear. The remaining parts of the text can be segmented and the ruling can be extrapolated with the a priori knowledge. Since the ruling defines the position of the text within a page, it can be used for layout analysis and as a basis for the enhancement of the readability. Furthermore, information about the scribe (hand) of the manuscript, its spatiotemporal origin can be gained by analyzing the ruling. This paper presents an algorithm for ruling estimation of Glagolitic texts based on text line extraction and is suitable for degraded manuscripts by extrapolating the baselines with the a priori knowledge of the ruling. The algorithm was tested on 30 pages of the Missale Sinaiticum and the evaluation was based on visual criteria.

关键词： Text analysis Degradation Algorithm design and analysis image segmentation image analysis Spatiotemporal phenomena Information analysis Data mining Software libraries Clustering algorithms

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