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A hybrid local feature for face recognition

A hybrid local feature for face recognition

引用

12th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2012

作者： Gou, Gaopeng Huang, Di Wang, Yunhong Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Beihang University Beijing China

ISBN: (纸本)9783642326943

Efficient face encoding is an important issue in the area of face recognition. Compared to holistic features, local features have received increasing attention due to their good robustness to pose and illumination changes. In this paper, based on the histogram-based interest points and the speeded up robust features, we propose a hybrid local face feature, which provides a proper balance between the computational speed and discriminative power. Experiments on three databases demonstrate the effectiveness of the proposed method as well as its robustness to the main challenges of face recognition and even in practical environment. © 2012 Springer-Verlag.

关键词： Face recognition

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Ethnicity classification based on a hierarchical fusion

Ethnicity classification based on a hierarchical fusion

引用

7th Chinese Conference on Biometric recognition, CCBR 2012

作者： Zhang, De Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9783642355059

In this paper, we propose a cascaded multimodal biometrics system involving a fusion of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs human ethnicity classification first from the cues of gait recorded by a long-distance camera and requires next classification using facial images captured by a short-distance camera only when gait based ethnicity identification fails. For gait, we use Gait Energy image (GEI), a spatio-temporal compact representation of gait in video, to characterize human walking properties. For face, we extract the well-known Gabor feature to render the effective facial appearance information. Experimental results obtained from a database of 22 subjects containing 12 East-Asian and 10 South-American shows that this cascaded system is capable of providing competitive discriminative power on ethnicity with a correct classification rate over 95%. © 2012 Springer-Verlag.

关键词： Classification (of information)

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Oriented Gradient Maps based automatic asymmetric 3D-2D face recognition

Oriented Gradient Maps based automatic asymmetric 3D-2D face...

引用

2012 5th IAPR International Conference on Biometrics, ICB 2012

作者： Huang, Di Ardabilian, Mohsen Wang, Yunhong Chen, Liming Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing 100191 China Université de Lyon CNRS UMR5205 Lyon 69134 France

ISBN: (纸本)9781467303941

Recently, asymmetric 3D-2D face recognition has been paid increasing attention. It enrolls in textured 3D faces and performs identification using only 2D facial images, therefore it generally achieves a better result than 2D algorithms do, and avoids inconvenience of data acquisition and computation of 3D methods as well. In this paper, a biological vision-based facial representation, namely Oriented Gradient Maps (OGMs), is introduced for such an application. It simulates the response of complex neurons to gradient information within a pre-defined neighborhood, and thus can describe local texture changes of 2D faces and local geometry variations of 3D faces at the same time. Due to its property of being highly distinctive, these OGMs improve accuracies of both matching steps of asymmetric face recognition, i.e. (1) 3D-2D matching using Canonical Correlation Analysis (CCA);(2) 2D-2D matching using LBP histogram based features and Sparse Representation Classifier (SRC). Some comparative experiments are carried out on the complete FRGC v2.0 database, and the achieved results clearly highlight the effectiveness of the biological vision-based facial description and its successful application to asymmetric face recognition. © 2012 IEEE.

关键词： Face recognition

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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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Moving Object Detection in Aerial Video

Moving Object Detection in Aerial Video

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Yunfei Wang Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing China

We address the problem of moving object detection in aerial video. Moving object detection in aerial video is still a challenging problem for the reason that when capturing the video the camera (or the platform) is moving all the time. As a result, the problem is detecting moving object from moving background which is much more difficult than the case that the background is constant. To this end, a novel approach is proposed in this paper. Moving object detection in stationary scene usually modeling the pixel value changes over time, but in aerial video the change does not have regular patterns. Therefore, we model the motion of the background rather than modeling the background directly. The optical flow between every two adjacent frames is computed first to get the motion information for each pixel. Based on this, we define a notion named ``pixel motion process" which means the motion changes (the optical flow value changes) of a particular pixel over time, and transfer the Gaussian mixture model framework used for modeling background in the stationary scene to model the background motion. The result is an accurate, adaptive and general background motion model which is used to detect foreground moving objects. Experimental results demonstrate the effectiveness of our approach.

关键词： Adaptation models Cameras Mathematical model Computational modeling Computer vision Object detection Optical imaging

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Ethnicity classification based on fusion of face and gait

Ethnicity classification based on fusion of face and gait

引用

IAPR International Conference on Biometrics (ICB)

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

The recognition of ethnicity of an individual can be very useful in a video-based surveillance system. In this paper, we propose a multimodal biometric system involving an integration of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs a feature fusion to improve the discrimination of human ethnicity. Face features are extracted by means of the uniform LBP operator and gait information is characterized by a spatio-temporal representation. Afterwards, canonical correlation analysis (CCA), as a powerful tool to relate two sets of measurements, is used to fuse the two modalities at the feature level. A database including 36 walking people from East Asia and South America is built for the purpose of ethnicity classification. The experimental results show that the ethnicity recognition rate is improved by fusing face and gait information.

关键词： Face Feature extraction Databases Support vector machines Cameras Vectors Legged locomotion

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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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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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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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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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