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检索条件"机构=Pattern Recognition and Image Processing Processing Laboratory"

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Investigating the separability of features from different views for gait based gender classification

Investigating the separability of features from different vi...

引用

International Conference on pattern recognition

作者： De Zhang Yunhong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering BeiHang University Beijing China

ISBN: (纸本)9781424421749

In this paper, we investigate the efficiency of different view angles when classifying gender with gait biometrics for the first time. A gait database is built for this purpose in which walking videos are recorded at seven different views for each subject. Then, we employ a robust gait representation method to extract gait features. The class separability of these features from different view angles are analyzed and compared. A set of experiments are designed to evaluate the performance of gait based gender classification along with the changes of view angle. The experimental results show that 0deg and 180deg are the worst view angles in this two-category case and the 90deg view dose not perform the best, unlike it takes the best performance in gait recognition.

关键词： Humans Legged locomotion Spatial databases Biometrics Robustness Feature extraction Data analysis Data mining image recognition image processing

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A multiple model structure for tracking by variable rate particle filters

A multiple model structure for tracking by variable rate par...

引用

International Conference on pattern recognition

作者： Yener Ulker Bilge Gunsel Serap Kirbiz Department of Electronics and Communications Engineering Multimedia Signal Processing and Pattern Recognition Laboratory Istanbul Technical University Istanbul Turkey

In contrast to the fixed rate modeling of the conventional methods, recently introduced variable rate particle filters (VRPF) achieves to track maneuvering objects with a small number of states by imposing a probability distribution on state arrival times. Although this enables VRPF an appealing method, representing the target motion dynamics with a single model hinders the capability of estimating maneuver parameters precisely. To overcome this weakness we have incorporated multiple model approach with the variable rate model structure. The introduced model referred as Multiple Model Variable Rate Particle Filter (MM-VRPF) utilizes a parsimonious representation for smooth regions of trajectory while it adaptively locates frequent state points at high maneuver regions, resulting in a much more accurate tracking. Simulation results obtained in a bearings-only target tracking problem show that the proposed model outperforms the conventional VRPF, the fixed rate multiple model particle filters (MMPF) and interacting multiple model using extended Kalman filters (IMM-EKF).

关键词： Particle tracking Particle filters Target tracking Trajectory Motion estimation State estimation Filtering Signal processing pattern recognition Probability distribution

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Subspace Analysis Methods plus Motion History image for Human Action recognition

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

引用

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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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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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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Moment based level set method for image segmentation

Moment based level set method for image segmentation

引用

IEEE International Conference on image processing

作者： Juan Zhou Lixiu Yao Jie Yang Chunming Li Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Institute of Imaging Science Vanderbilt University Nashville TN USA

This paper presents a novel level set method for image segmentation. Gray-level moments are used to estimate two fitting functions that approximate local intensities on the two sides of object boundaries, which are then incorporated into a variational level set framework. An energy functional is defined on a contour, which characterizes the approximation of local intensities on the two sides of the contour by the two fitting functions. This energy can be minimized when the contour is on the object boundary. Thus, image segmentation is performed by minimizing this energy functional. A desirable feature of our method is that it is not sensitive to the contour initialization. Moreover, our method is able to segment images with intensity inhomogeneity. Only a small number of iterations are needed to obtain the final result, which makes our method more efficient than previous level set methods.

关键词： Level set image segmentation Active contours image processing pattern recognition Computational modeling Robustness Computational efficiency Convolution image edge detection

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FUSION OF GLOBAL AND LOCAL INFORMATION FOR AN ON-LINE SIGNATURE VERIFICATION SYSTEM

FUSION OF GLOBAL AND LOCAL INFORMATION FOR AN ON-LINE SIGNAT...

引用

2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： NING-NING LIU YUN-HONG WANG Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100083 China

In this paper, an on-line signature verification system exploiting local and global information using two-stage fusion is presented. At the first stage, global information is extracted as I3-dimensional vector and recognized by Majority Classifiers, and then local information is extracted as time functions of various dynamic properties and recognized by BP neural network classifier. By fusing global and local information and introducing an enhanced dynamic time warping algorithm and a normalized feature measure, our method obtained an average EER of 4.02％ on public database SVC2004( First Signature Verification Competition 2004) Task2 compared to 6.90％ the first place at SVC2004.

关键词： Biometrics online signature verification DTW algorithm two stage fusion

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An Evaluation of Low Cost Scanning versus Industrial 3D Scanning Devices

An Evaluation of Low Cost Scanning versus Industrial 3D Scan...

引用

Congress on image and Signal processing, CISP

作者： Miha Drenik Martin Kampel Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Pattern Recognition and Image Processing Group Technical University of of Vienna Vienna Austria

This paper presents an evaluation of two different 3D scanning devices. They can be put into operation depending on the monetary constraints of the user on one hand, and the accuracy needed for a specific application on the other hand. The setting up of the systems and the process of scanning with the devices are presented. Two setups were formed to evaluate the capabilities of a low costs scanning device together with industrial scanning devices. A comparison of the scans obtained was made by using a Konica Minolta VI-9i industrial scanning solution as a reference. The analysis comprises the estimation of surface flatness, the evaluation of measuring of geometric shapes, and the appraisal of the time required for obtaining a virtual 3D representation of a scanned object. The results show that both the curves as well as the shapes as a whole have been captured accurately.

关键词： Costs Shape measurement Application software Feeds Signal processing Computer industry Information science pattern recognition image processing Time measurement

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Voronoi-Based Sleeping Configuration in Wireless Sensor Networks with Location Error

Voronoi-Based Sleeping Configuration in Wireless Sensor Netw...

引用

IEEE International Conference on Networking, Sensing and Control

作者： Xinyu Chen Michael R. Lyu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China Department of Computer Science and Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

In wireless sensor networks, to obtain a long network lifetime is a fundamental issue while without sacrificing crucial aspects of quality of service (area coverage, sensing reliability, and network connectivity). In this paper, we present a Voronoi-based sleeping configuration to deal with different sensing radii and location error. With our proposed sleeping candidate condition, redundant sensors are optionally identified and scheduled to sleep in order to extend the system lifetime while maintaining adequate sensor redundancy to tolerate sensor failures, energy depletions, and location error. Simulation results show that there is a tradeoff among energy conservation, area coverage, and fault tolerance, which varies between different sleeping candidate conditions.

关键词： Wireless sensor networks Sensor systems Surveillance Quality of service Redundancy Energy conservation Fault tolerance Sensor phenomena and characterization Batteries image processing

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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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