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

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Cross-view object classification in traffic scene surveillance based on transductive transfer learning

Cross-view object classification in traffic scene surveillan...

引用

IEEE International Conference on image processing

作者： Yi Mo Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

Object classification in traffic scene surveillance has been a hot topic in image processing field. A big challenge is that shooting view changes in different scenes, which leads to sharp accuracy decrease since training and test samples do not share the same distribution. Inductive transfer learning methods try to bridge this gap by making use of manually labeled target samples. However, it is in line with reality to conduct unsupervised transfer without manually labeling. In this paper, we propose an intuitive transductive transfer method by transferring instances across view. Experimental results indicate that our method outperforms traditional approaches such as inductive SVM and cluster method, and could even achieve a comparable performance compared with manually labeling approach.

关键词： Support vector machines Surveillance Training Accuracy Labeling image edge detection Feature extraction

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Robust Mobile Spamming Detection via Graph patterns

Robust Mobile Spamming Detection via Graph Patterns

引用

International Conference on pattern recognition

作者： Yuhang Zhao Zhaoxiang Zhang Yunhong Wang Jianyun Liu Intelligent Recognition and Image Processing Lab Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University

ISBN: (纸本)9781467322164

Short message service (SMS) is now an indispensable way of social communication. However the mobile spam is getting increasingly serious, troubling users' daily life and ruining the service quality. We propose a novel approach for spam message detection based on mining the underlying social network of SMS activities. Comparing with strategies on keywords or flow detection, our network-based approach is more robust and difficult to defeat by human spammers. Various levels of features are employed to describe multiple aspects of the network, such as static structures, node activities and evolving situations. Experimental results on real dataset illustrate effectiveness of various features, showing our promising results.

关键词： data mining electronic messaging feature extraction mobile computing network theory (graphs) social networking (online) unsolicited e-mail

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A hierarchical framework for image-based human age estimation by weighted and OHRanked Sparse Representation-based classification

A hierarchical framework for image-based human age estimatio...

引用

IAPR International Conference on Biometrics (ICB)

作者： Weixin Li Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

Human age estimation based on face images can figure in a wide variety of real-world applications. In this paper, we propose a novel and efficient facial age estimation algorithm which decides human age in a hierarchical framework. Biologically, human lives can be roughly divided into two stages, the period from birth to adulthood and the period from adulthood to old age, which are quite different from each other in face growth and aging forms. Considering that craniofacial growth occurs mainly in the first stage while keeps basically stable in the second, based on the shape features, the coarse step of the framework determines which age stage the test sample belongs to using a quadratic function. On the other hand, since the face appearance of individuals in the same age group or even of the same age does have some similarities in common, accurate age estimation within the age stage is solved by Sparse Representation-based classification (SRC) in the fine step. However, SRC requires sufficient training samples in each class and in practice this assumption often does not hold, making the performance of age estimation limited. Accordingly, we take use of the idea of Ordinal Hyperplanes Ranker (OHRank) and weights of samples' numbers in each class to solve the aforementioned problem, improving the age estimation results. Results of experiments conducted on the FG-NET Database demonstrate the effectiveness of our method.

关键词： Face Estimation Training Shape Aging Feature extraction Humans

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Detection of Billet Character in Complex Production Line Scene

Detection of Billet Character in Complex Production Line Sce...

引用

International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Hong Hanyu Yu Zhejun Zhang Xiuhua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan China

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application.

关键词： Billets image segmentation Steel Arrays Filtering Licenses

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Target recognition method based on template matching in downward-looking infrared image

Target recognition method based on template matching in down...

引用

2012 3rd IEEE/IET International Conference on Audio, Language and image processing, ICALIP 2012

作者： Zhu, Hu Deng, Lizhen Zhou, Gang Bai, Xiaodong Wang, Gaihua National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

Automatic ground target recognition technology in downward-looking infrared imagery is challenging problems due to the complexity of real-world. A robust ground target recognition method is proposed for downward-looking infrared (DLIR) image sequences in this paper. A complete model of the proposed method is designed firstly and the principles of some key technologies are introduced as following. Perspective transformation is used to solve the projective problems of landmark translation, rotation and scale variance in real-time image sequence. The size of landmark is estimated real-timely by using flight parameters and imaging parameters for getting the model with an appropriate scale. Based on the matching results of landmark and flight parameters, target position technology is proposed to identify the position of target by using the position relation between landmark and target. Experimental results using real-world image data with complicated background showed that the proposed method not only causes high precisely locating results, but also has good robustness for target occlusion. © 2012 IEEE.

关键词： Template matching

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BP Neural Networks with Harmony Search Method-based Training for Epileptic EEG Signal Classification

BP Neural Networks with Harmony Search Method-based Training...

引用

International Conference on Computational Intelligence and Security

作者： Xiao-Zhi Gao Jing Wang Jarno M.A. Tanskanen Rongfang Bie Ping Guo College of Information Engineering Shanghai Maritime University China laboratory of Image Processing and Pattern Recognition Beijinz Normal University China Tampereen yliopisto - Hervannan kampus Tampere Pirkanmaa FI

In this paper, the Harmony Search (HS)-based BP neural networks are used for the classification of the epileptic electroencephalogram (EEG) signals. It is well known that the gradient descent-based learning method can result in local optima in the training of BP neural networks, which may significantly affect their approximation performances. Two HS methods, the original version and a new variation recently proposed by the authors of the present paper, are applied here to optimize the weights in the BP neural networks for the classification of the epileptic EEG signals. Simulations have demonstrated that the classification accuracy of the BP neural networks can be remarkably improved by the HS method-based training.

关键词： Electroencephalography Optimization Training Biological neural networks Feature extraction Epilepsy

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Pan-sharpening using weighted red-black wavelet

Pan-sharpening using weighted red-black wavelet

引用

International Conference on pattern recognition

作者： Qingjie Liu Yunhong Wang Zhaoxiang Zhang Lining Liu Intelligent Recognition and Image Processing Lab Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467322164

In this paper, we propose a new method for remote sensing image pan-sharpening which is based on weighted red-black (WRB) wavelet and adaptive principal component analysis (PCA), where the adaptive PCA is used to reduce spectral distortions and the utilization of WRB wavelet is used to extract the spatial details in PAN images. To reduce the artifacts and spectral distortions in the pan-sharpened images, which were caused by the local instabilities and dissimilarities in the PAN and MS images, a local process strategy incorporating detail enhancement is introduced. The proposed method is tested on two datasets both acquired by QuickBird and compared with the existing methods. Experimental results show that our method can provide promising fused MS images at a high spatial resolution.

关键词： Principal component analysis Correlation Remote sensing Multiresolution analysis Spatial resolution Discrete wavelet transforms

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Fast ground target detection method in infrared image sequences

Fast ground target detection method in infrared image sequen...

引用

2012 3rd IEEE/IET International Conference on Audio, Language and image processing, ICALIP 2012

作者： Zhu, Hu Deng, Lizhen Wang, Gaihua Zhou, Gang Bai, Xiaodong National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

Automatic target detection (ATD) in infrared (IR) imagery is a fundamental and challenging task in computer vision. A fast automatic target detection method in IR image sequence is proposed in this paper. Since the position and scale of target change real-timely, we can predict the target position in real-time image by using the history position of target and flight parameters information of previous and current frames, and then estimate the scale of target depending on flight parameters and imaging parameters for getting the model with the appropriate scale. In order to make the template matching more robust for target rotation, the template matching method based on parametric template vector is used to recognize the position of target. The detection result is identified by using multiframe integration based on recognition information of history and currant frames. Some experimental results using real-world images with complicated background validate the effectiveness and robustness of the proposed method under rotation and scale variance condition. © 2012 IEEE.

关键词： Template matching

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Enhancing biometric security with wavelet quantization watermarking based two-stage multimodal authentication

Enhancing biometric security with wavelet quantization water...

引用

International Conference on pattern recognition

作者： Bin Ma Chunlei Li Yunhong Wang Zhaoxiang Zhang Di Huang Intelligent Recognition and Image Processing Lab Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467322164

In this paper we propose a watermarking based two-stage authentication framework to enhance biometric system security. The face feature of one individual is embedded into his/her fingerprint image as credibility token. During authentication, the watermark is first extracted to establish data authenticity. If legitimate, the face pattern can further serve as supplemental trait in biometric authentication progress. A wavelet quantization based watermarking method is proposed to robustly embed information in fingerprints while preserving their discriminating features. Meanwhile, a sparse representation based classifier is adopted to efficiently exploit the identity information within face watermarks. Experimental results which evaluate both watermarking and biometric authentication performance demonstrate the effectiveness of this work.

关键词： Watermarking Face Authentication Robustness Quantization pattern recognition

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Classification of gothic and baroque architectural elements

Classification of gothic and baroque architectural elements

引用

International Conference on Systems, Signals and image processing, IWSSIP

作者： Gayane Shalunts Yll Haxhimusa Robert Sablatnig Institute of Computer Aided Automation Computer Vision Laboratory University of Technology Vienna Austria Institute of Computer Graphics and Algorithms Pattern Recognition and Image Processing Lab University of Technology Vienna Austria

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate.

关键词： Shape Three dimensional displays Visualization Computer vision Histograms Windows

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