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International Conference on Wavelet Analysis and Pattern recognition (ICWAPR)

作者： Lei Hu Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

Automatic signature verification has been an intense research area because of the social and legal acceptance and widespread use of written signatures. It is still a challenging issue because of "small sample size " problem as well as large intra-class variations and, when considering forgeries, small inter-class variations. In order to solve these problems, we propose a two-stage fusion method to get high accuracy. At first, an EDTW (enhanced dynamic time warping) algorithm and a normalized feature measure are proposed to build a classifier based on local features. The former enhances the separability between genuine and forgery signatures, while the latter approaches the problem as a two-class pattern recognition problem, which make it possible to use training signatures as many as possible. However, local method is time and resource consuming, so we then design another classifier based on global features using majority voting rule. We fuse the global and local method by two-sage serial strategy to build an on-line signature verification system. Experimental results on SVC2004 TASK2 show good performance of our system.

关键词： Handwriting recognition Pattern recognition Forgery Voting Wavelet analysis Pattern analysis Law Legal factors Fuses

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Ethnicity classification based on fusion of face and gait

Ethnicity classification based on fusion of face and gait

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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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3D Face Pose Normalization Using Equipartition Fitting Sphere Representation of Shape

3D Face Pose Normalization Using Equipartition Fitting Spher...

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International Conference on image and Graphics (ICIG)

作者： Peijiang Liu Yunhong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9780769552378;9780769538839

Pose normalization is a necessary process of 3D face recognition. Automatic and robust normalization is still a challenge to existing techniques. We propose a novel method called Equipartition Fitting Sphere Representation (EPFSR) for shape representation. Convexes on face are localized firstly based on EPFSR. Then the tip and orientation of nose are identified automatically from convexes by template matching. Extensive experiments are performed on five popular 3D face databases. Results show the high robustness of the proposed methods to expression variations. Accuracy of nose identification is more than 97.7%. Time cost depends on the number of face vertices. It takes averagely less than 9 seconds to localize the nose on a 3D head including around 80000 vertices in the FRGC2.0 database.

关键词： Shape Nose Face recognition Clouds Robustness Databases Costs Face detection Humans Computer graphics

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Carrying object detection and tracking based on body main axis

Carrying object detection and tracking based on body main ax...

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International Conference on Wavelet Analysis and Pattern recognition (ICWAPR)

作者： Yue Qi Guo-Chang Huang Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

In this paper, we propose a method to examine whether a walking person is carrying objects using the width of human body contour. First we concentrate on the detection of the moving people contour and then human contour width is projected to the feature space for training a classifier. We introduce principal component analysis for dimension reduction and support vector machine to classify the carrying object status. If the status is true, the carrying object region is figured out by analyzing human contour shape. We utilize the outmost vertex from human contour to track the carrying object such as a rucksack or luggage. The experimental results demonstrate that our approach is encouraging.

关键词： Object detection Humans Principal component analysis Support vector machines Feature extraction Video sequences Pattern recognition Legged locomotion Filtering Wavelet analysis

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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...

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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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Gait recognition Algorithm GCGait based on Skeleton 3

Gait Recognition Algorithm GCGait based on Skeleton

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3rd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Ma, Ru Zhang, Jikai Jia, Mengyu Lv, Xiaoqi Inner Mongolia University of Science and Technology School of Information Engineering Baotou China Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Baotou China Inner Mongolia University of Technology School of Information Engineering Hohhot China

ISBN: (纸本)9781665490788

To solve the problem of low accuracy of gait recognition in complex scenes, a novel skeleton-based gait recognition algorithm, GCGait, is proposed. Taking human posture as the input of gait feature, the interference caused by wearing changes and other factors is reduced. To extract sufficient input features, multi-branch input is used in the early stage of the model. By introducing the multi-attention mechanism, the network can learn the semantic information of the non-directly connected joints, excavate the most discriminative features from complex videos, and further improve the recognition performance. In order to reduce the influence of cross view, the fusion loss function is used in the experiment. Experimental results show that the average recognition rate of the proposed algorithm on the CASIA-B dataset is improved by 5.2%, and the average recognition accuracy on the OU-MVLP dataset is increased by 66.3%, which proves the effectiveness of the proposed method. © 2023 IEEE.

关键词： Complex networks

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On-line Signature Verification Based on Correlation image

On-line Signature Verification Based on Correlation Image

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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： Hao-Ran Deng Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100083 China

In this paper we proposed a novel method for signature verification. Different from the conventional approaches, we suppose the sample points of the signature have some kind of correlation with each other, and the correlations contain the habitual features of the signature, which can be used to confirm the identity of the signer. In the proposed method, we first generate the matrix of the correlations of the sample points of the signature and convert the matrix into an intensity image, then use image matching approach to verify signature. The proposed method is validated on the SVC 2004 database and inspiring results are obtained.

关键词： On-Line Signature Verification Biometrics Correlation Matriz Intensity image LBP SIFT

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Vision-based 3D occupancy prediction in autonomous driving: a review and outlook

arXiv

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arXiv 2024年

作者： Zhang, Yanan Zhang, Jinqing Wang, Zengran Xu, Junhao Huang, Di Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing100191 China

In recent years, autonomous driving has garnered escalating attention for its potential to relieve drivers’ burdens and improve driving safety. Vision-based 3D occupancy prediction, which predicts the spatial occupancy status and semantics of 3D voxel grids around the autonomous vehicle from image inputs, is an emerging perception task suitable for cost-effective perception system of autonomous driving. Although numerous studies have demonstrated the greater advantages of 3D occupancy prediction over object-centric perception tasks, there is still a lack of a dedicated review focusing on this rapidly developing field. In this paper, we first introduce the background of vision-based 3D occupancy prediction and discuss the challenges in this task. Secondly, we conduct a comprehensive survey of the progress in vision-based 3D occupancy prediction from three aspects: feature enhancement, deployment friendliness and label efficiency, and provide an in-depth analysis of the potentials and challenges of each category of methods. Finally, we present a summary of prevailing research trends and propose some inspiring future outlooks. To provide a valuable reference for researchers, a regularly updated collection of related papers, datasets, and codes is organized at https://***/zya3d/Awesome-3D-Occupancy-Prediction. Copyright © 2024, The Authors. All rights reserved.

关键词： Vehicle-to-grid

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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...

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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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A fast VLSI architecture for two-dimensional discrete wavelet transform based on lifting scheme

A fast VLSI architecture for two-dimensional discrete wavele...

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2004 7th International Conference on Solid-State and Integrated Circuits Technology Proceedings, ICSICT 2004

作者： Xiong, Chengyi Tian, Jinwen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence Key Laboratory of Eduaction Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China College of Electronic Information Engineering South-Center University for Nationalities Wuhan 430074 China

This paper proposes a novel fast architecture for two-dimensional discrete wavelet transform by using lifting scheme. The parallel and embedded decimation techniques are employed to optimize the architecture, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. The architecture is designed to generate two outputs at one working clock cycle, with every two subbands coefficients alternately. The total time of computing J levels of decomposition for N×N image is approximately 2N2(I-4 J)/3 clock cycles. In comparison with the other devices reported in previous literature, the design has many advantages including lower hardware complexity and area and power efficient. The design is also fast, regular and simple, as well as well suited for VLSI implementation. © 2004 IEEE.

关键词： VLSI circuits

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