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26th IEEE Conference on Computer Vision and pattern recognition (CVPR 2008), vol.8

作者： Zhaofeng He Zhenan Sun Tieniu Tan Xianchao Qiu Cheng Zhong Wenbo Dong Center for Biometrics and Security Research National Laboratory of Pattern RecognitionNational Laboratory of Pattern Recognition Chinese Academy and Sciences Beijing China

In this paper, we present a novel iris recognition method based on learned ordinal features. Firstly, taking full advantages of the properties of iris textures, a new iris representation method based on regional ordinal measure encoding is presented, which provides an over-complete iris feature set for learning. Secondly, a novel Similarity Oriented Boosting (SOBoost) algorithm is proposed to train an efficient and stable classifier with a small set of features. Compared with Adaboost, SOBoost is advantageous in that it operates on similarity oriented training samples, and therefore provides a better way for boosting strong classifiers. Finally, the well-known cascade architecture is adopted to reorganize the learned SOBoost classifier into a 'cascade', by which the searching ability of iris recognition towards large-scale deployments is greatly enhanced. Extensive experiments on two challenging iris image databases demonstrate that the proposed method achieves state-of-the-art iris recognition accuracy and speed. In addition, SOBoost outperforms Adaboost (Gentle-Adaboost, JS-Adaboost, etc.) in terms of both accuracy and generalization capability across different iris databases.

关键词： Boosting Iris recognition Image databases Spatial databases Machine learning algorithms Large-scale systems Helium Sun biometrics National security

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Combine hierarchical appearance statistics for accurate palmprint recognition

Combine hierarchical appearance statistics for accurate palm...

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International Conference on pattern recognition

作者： Yufei Han Zhenan Sun Tieniu Tan Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences

ISBN: (纸本)9781424421749

Palmprint recognition is an active member of biometrics in recent years. State-of-the-art algorithms of palmprint recognition describe appearances of palmprints efficiently through local texture analysis. Following this framework, we propose a novel approach of palmprint recognition in this paper, which represents palmprint images based on statistics and spatial arrangement of appearance descriptors within local image areas. In this method, we firstly design a robust descriptor to encode properties of palmprint appearances of local regions. The whole image is divided into non-overlapped blocks at increasingly fine resolutions successively, so as to describe the spatial layout in hierarchical scales. For a specific spatial resolution, local distributions of the proposed descriptors in the blocks are concatenated to represent structures of palmprint structures. Finally, distribution information of different resolutions is combined to provide complementary descriptive power. Promising experimental results demonstrate that the proposed method achieves even better performances than the state-of-the-art approaches.

关键词： Statistics Spatial resolution biometrics Image texture analysis Algorithm design and analysis Image recognition Design methodology Robustness Image resolution Concatenated codes

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Counterfeit iris detection based on texture analysis

Counterfeit iris detection based on texture analysis

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International Conference on pattern recognition

作者： Zhuoshi Wei Xianchao Qiu Zhenan Sun Tieniu Tan Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424421749

This paper addresses the issue of counterfeit iris detection, which is a liveness detection problem in biometrics. Fake iris mentioned here refers to iris wearing color contact lens with textures printed onto them. We propose three measures to detect fake iris: measuring iris edge sharpness, applying Iris-Texton feature for characterizing the visual primitives of iris textures and using selected features based on co-occurrence matrix (CM). Extensive testing is carried out on two datasets containing different types of contact lens with totally 640 fake iris images, which demonstrates that Iris-Texton and CM features are effective and robust in anticounterfeit iris. Detailed comparisons with two state-of-the-art methods are also presented, showing that the proposed iris edge sharpness measure acquires a comparable performance with these two methods, while Iris-Texton and CM features outperform the state-of-the-art.

关键词： Counterfeiting biometrics Lenses Gabor filters Image edge detection Histograms Iris recognition Image segmentation Robustness Control systems

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Face Shape Recovery from a Single Image Using CCA Mapping between Tensor Spaces

Face Shape Recovery from a Single Image Using CCA Mapping be...

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26th IEEE Conference on Computer Vision and pattern recognition (CVPR 2008), vol.1

作者： Zhen Lei Qinqun Bai Ran He Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor space to 3D tensor space, learned by using statistical learning, is used for the shape recovery. In the learning phase, the two tensor models are constructed for NIR and 3D images respectively, and a canonical correlation analysis (CCA) based multi-variate mapping from NIR to 3D faces is learned from a given training set of NIR-3D face pairs. In the reconstruction phase, given an NIR face image, the depth map is computed directly using the learned mapping with the help of tensor models. Experimental results are provided to evaluate the accuracy and speed of the method. The work provides a practical solution for reliable and fast shape recovery and modeling of 3D objects.

关键词： Shape Tensile stress Image reconstruction Humans Surface reconstruction Face detection Surface fitting Magnetic force microscopy Lighting Infrared imaging

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A hierarchical model for the evaluation of biometric sample quality

A hierarchical model for the evaluation of biometric sample ...

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International Conference on pattern recognition

作者： Qian He Zhenan Sun Tieniu Tan Yong Zou Center for Biometrics Authentication and Testing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424421749

The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This model is developed on the basis of three types of influencing factors: global factors, subjective factors and variable factors. We adopt different strategies to compute the corresponding three level qualities: database level quality, class level quality and image level quality. The database level quality is estimated by experience. Then, we compute the mean value of variable number of normalized genuine scores, the quantiles of which are used to determine the class level quality. On the image level quality evaluation, a novel concept of subset frequency is proposed.

关键词： biometrics Fingerprint recognition Image databases Image quality Frequency Image matching Iris Helium Sun Authentication

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Synthesis of large realistic iris databases using patch-based sampling

Synthesis of large realistic iris databases using patch-base...

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International Conference on pattern recognition

作者： Zhuoshi Wei Tieniu Tan Zhenan Sun Center for Biometrics and Security Research National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424421749

This paper presents a framework to synthesize large realistic iris databases, providing an alternative to iris database collection. Firstly, iris patch is used as a basic element to characterize visual primitive of iris texture, and patch-based sampling is applied to create an iris prototype. Then a set of pseudo irises with intra-class variations are derived from the prototype. Qualitative and quantitative studies reveal that synthetic databases are well suited for evaluating iris recognition systems by achieving three goals: (1) the synthetic iris images bear a close resemblance to real iris images in terms of visual appearance; (2) the proposed framework is able to generate databases with large capacity; (3) statistical performance shows that the synthetic iris images hold all the major characteristics of real iris images.

关键词： Sampling methods Prototypes Visual databases Image databases Image generation biometrics Image sampling Iris recognition Waveguide discontinuities Sun

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Normalized LDA for semi-supervised learning

Normalized LDA for semi-supervised learning

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International Conference on Automatic Face and Gesture recognition

作者： Bin Fan Zhen Lei Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training, while making labeled samples is a time consuming and exhausting work. A semi-supervised LDA (SDA) has been proposed recently to enable training of LDA with partially labeled samples. In this paper, we first reformulate supervised LDA based on the normalized perspective of LDA. Then we show that such a reformulation is powerful for semi-supervised learning of LDA. We call this approach Normalized LDA, which uses total diversity to normalize intra-class diversity and aims to find projection directions that minimize normalized intra-class diversity. Although the Normalized LDA is identical to LDA in the supervised situation, a semi-supervised approach can be easily incorporated into its framework to make use of unlabeled samples to improve the performance in the learned subspace. Moreover, different with SDA which uses unlabeled samples to preserve neighboring relations, unlabeled samples in the Normalized LDA are used for a more accurate estimation of data space. Experiments of face recognition on the FRGC version 2 database and CMU PIE database demonstrate that the Normalized LDA outperforms SDA.

关键词： Linear discriminant analysis Semisupervised learning Face recognition biometrics pattern recognition Object detection Principal component analysis National security Laboratories Automation

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Enhanced usability of iris recognition via efficient user interface and iris image restoration

Enhanced usability of iris recognition via efficient user in...

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IEEE International Conference on Image Processing

作者： Zhaofeng He Zhenan Sun Tieniu Tan Xianchao Qiu Center for Biometrics and Security Research National Laboratory of Pattern RecognitionInstitute of Automation Chinese Academy and Sciences Beijing China

In this paper, we investigate the possibility of enhancing the usability of iris recognition via exploration of the specular spots in iris images. Firstly, the spatial configuration of the specular spots in iris images is utilized to estimate the distance between the user and the camera. Based on this a friendly user interface is established to assist users for their range adjustment. Furthermore, the estimated distance is used by an adaptive image restoration scheme to restore the blurred iris image, thereby increasing the depth of field of the iris camera. Experimental results show that the proposed method significantly enhances the usability of iris recognition without noticeable computation cost.

关键词： Usability Iris recognition User interfaces Image restoration Cameras Hardware biometrics Focusing Feedback Helium

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Online Adaptive Fast Multipose Face Tracking Based on Visual Cue Selection

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自动化学报 2008年第1期34卷 14-20页

作者： YANG Tao LI Zi-Qing PAN Quan LI Jing ZHAO Chun-Hui CHENG Yong-Mei College of Automation Northwestern Polytechnical University Xi'an 710072 P.R. China Center for Biometrics and Security Research and National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 P. R. China

This paper presents a system that is able to reliably track multiple faces under varying poses(tilted and rotated)in real *** system consists of two interactive *** first module performs the detection of the face that is subject to rotation. The second module carries out online learning-based face tracking.A mechanism that switches between the two modules is embedded into the system to automatically decide the best strategy for reliable *** mechanism enables a smooth transit between the detection and tracking modules when one of them gives either nil or unreliable *** experiments demonstrate that the system can reliably carry out real time tracking of multiple faces in a complex background under different conditions such as out-of-plane rotation,tilting,fast nonlinear motion,partial occlusion,large scale changes,and camera ***,it runs at a high speed of 10～12 frames per second(fps)for an image of 320×240.

关键词：视觉提示选择面容跟踪系统绝对移动位置实时跟踪

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How to make iris recognition easier?

How to make iris recognition easier?

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International Conference on pattern recognition

作者： Wenbo Dong Zhenan Sun Tieniu Tan Center for Biometrics and Security Research (CBSR) & National Laboratory of Pattern Recognition (NLPR) Institute of Automation (CASIA) Chinese Academy and Sciences

ISBN: (纸本)9781424421749

Iris recognition is regarded as the most reliable biometrics and has been widely applied in both public and personal security areas. However users have to highly cooperate with the iris cameras to make his iris images well captured. In this paper, we aim to discuss whether and how we can make iris recognition easier. Firstly the restricting factors of iris image acquisition are analyzed and the optical formulas are derived. Then the solutions of state-of-the-art iris recognition systems are reviewed and summarized. Finally, we propose two novel iris recognition systems with good human-computer-interface but with two different strategies which respectively meet the requirements of low-end and high-end market.

关键词： Iris recognition Cameras Optical imaging Optical sensors Lenses Focusing Equations Pixel Image analysis Geometrical optics

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