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A New Approach for Face Anti-Spoofing Using Handcrafted and Deep Network Features

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A New Approach for Face Anti-Spoofing Using Handcrafted and ...

IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Polash Kumar Das Bin Hu Chang Liu Kaixin Cui Prabhat Ranjan Gang Xiong School of Electronic and Information Engineering South China University of Technology Guangzhou China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing China College of Computer Science Sichuan University Chengdu China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Cloud Computing Center Chinese Academy of Science Dongguan China

In biometrics, face recognition methods are achieving momentum with recent progress in the computer vision(CV). Face recognition is widely used in the identification of an individual's identity. Unfortunately, in recent research work has revealed this face biometrics system is unprotected to spoofing attacks using by very low price instrument such as printed 2D photos attack, 3D masking attack and taking videos using smart devices (reply attack). Therefore, a Liveness Attack Detection (LAD) approach is needed to improve the high-quality security of face recognition system. Most of the earlier worked LAD methods for face anti-spoofing methods have highlight on using the handcrafted features, which are developed by expert knowledge of researcher. As example Gabor filter, Histogram of Oriented Gradients, local ternary pattern, and the Local Binary Pattern. Because of that, the extracted features consider limited factors of the problem, yielding a capture accuracy that is very low and changes with the point of presentation in attack face images. The deep learning method has developed in the computer vision research community, which is proven to be suitable for automatically training. In this article, we approach to mix or combine the handcrafted features and deep neural network features to design the discriminant face spoofing detection. The handcrafted features were based on LBP analysis. We examine the features information from the brightness and the chrominance channels using LBP descriptor. In deep features, we present an approach based on pre-trained convolutional neural network VGG-16 model using static features to recognize video and printed(2D) photo attacks. By attaching this two types of image features on our dataset and public databases, we get good results to identify real and attack images feature, called hybrid features, which has better discrimination ability to understand spoofing image feature.

关键词： Face Videos Feature extraction Databases Face recognition Password

Coverage Probability-Constrained Maximum Throughput in UAV-Aided SWIPT Networks

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Coverage Probability-Constrained Maximum Throughput in UAV-A...

IEEE International Conference on Communications Workshops, ICC

作者： Ruihong Jiang Ke Xiong Tong Liu Duohua Wang Zhangdui Zhong School of Computer and Information Technology Beijing Jiaotong University Beijing China Beijing Computing Center Beijing China ZTE Corporation Xi'an China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing China

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

This paper investigates the coverage provability-constrained throughput in unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) networks, where UAVs are used as aerial base stations and their positions are modeled by the 2-dimension Poisson point process (2-D PPP). The ground users (GUs) decode information as well as harvest energy from the transmitted signals from UAVs. Both power splitting (PS) and time switching (TS) architectures are employed at GUs. By using a stochastic geometry approach, the explicit expressions of the information-energy (I-E) coverage probabilities are derived. To describe the optimal deployment density of UAVs, an optimization problem is formulated to maximize the system throughput subject to the I-E coverage probability constraint. By using Karush-Kuhn-Tucker (KKT) conditions, the closed-form solution is derived. Simulation results demonstrate the correctness of our derived analytical results and show that compared with traditional linear EH model, the nonlinear EH model yields significant difference performance behaviors of the system. Moreover, the nonlinear EH model has a greater impact on EH for the system with TS-enabled GU than that with PS-enabled one. With the increment of the outage threshold, the required density of UAVs should be increased and both the throughput and the energy first increase and then decrease.

关键词： Throughput Wireless communication Unmanned aerial vehicles Wireless sensor networks Integrated circuit modeling Analytical models Fading channels

Fingertip interactive tracking registration method for AR assembly system

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Advances in Computational Intelligence 2022年第2期2卷 1-26页

作者： Jiu, Yong Jianguo, Wei Yangping, Wang Jianwu, Dang Xiaomei, Lei The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong University Lanzhou China College of Intelligence and Computing Tianjin University Tianjin China The National Experimental Teaching Demonstration Center of Computer Science and Technology Lanzhou Jiaotong University Lanzhou China The School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou China Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou China Gansu Meteorological Service Meteorological Information and Technological Supporting Center Lanzhou China

Aiming at the problems of single input mode and lack of naturalness in the assembly process of existing AR systems, a tracking registration method of mobile AR assembly system is proposed based on multi-quantity and multi-degree of freedom natural fingertip interaction. Firstly, the real-time and stable tracking of hand area in complex environment is realized based on the hand region tracking; secondly, the fingertip detection and recognition based on K-COS and parallel vector is used to improve the precision and stability of fingertip recognition; thirdly, the special movement track of fingertip is recognized based on improved DTW algorithm, which has strong compatibility and feature gradient transformation for complex fingertip trajectory recognition; finally, through the real-time transformation of projection relationship between fingertip and virtual object, the interaction between fingertip and virtual object is made more natural and realistic. The experimental results show that in the complex environment of background, illumination, scale and rotation, the precision of fingertip detection and recognition is about 93%, and the precision of fingertip motion template matching is about 91%. The translation error of the registration method based on visual feature recognition is reduced by about 100pix compared with fingertip tracking registration method, and the efficiency of mobile AR-guided assembly method is improved by about 24.77% compared with the traditional manual assisted assembly method. These data verifies the strong interaction and practicability of the fingertips based on the user's multi-quantity and multi-degree of freedom features in the process of mobile AR guided assembly.

关键词：

Advanced NOMA Assisted Semi-Grant-Free Transmission Schemes for Randomly Distributed Users

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arXiv 2020年

作者： Lu, Huabing Xie, Xianzhong Shi, Zhaoyuan Lei, Hongjiang Yang, Helin Cai, Jun The Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian University of Technology Dalian116024 China The School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China The Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing246011 China The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China The Department of Information and Communication Engineering School of Informatics Xiamen University Xiamen361005 China Department of Electrical and Computer Engineering Concordia University MontrealQCH3G 1M8 Canada

Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has recently received significant research attention due to its outstanding ability of serving grant-free (GF) users with grant-based (GB) users' spectrum, which greatly improves the spectrum efficiency and effectively relieves the massive access problem of 5G and beyond networks. In this paper, we first study the outage performance of the greedy best user scheduling SGF scheme (BU-SGF) by considering the impacts of Rayleigh fading, path loss, and random user locations. In order to tackle the admission fairness problem of the BU-SGF scheme, we propose a fair SGF scheme by applying cumulative distribution function (CDF)-based scheduling (CS-SGF), in which the GF user with the best channel relative to its own statistics will be admitted. Moreover, by employing the theories of order statistics and stochastic geometry, the outage performances of both BU-SGF and CS-SGF schemes are analyzed. Theoretical results show that both schemes can achieve full diversity orders only when the served users' data rate is capped, which severely limits the rate performance of SGF schemes. To further address this issue, we propose a distributed power control strategy to relax such data rate constraint, and derive analytical expressions of the two schemes' outage performances under this strategy. Finally, simulation results validate the fairness performance of the proposed CS-SGF scheme, the effectiveness of the power control strategy, and the accuracy of the theoretical analyses. Copyright © 2020, The Authors. All rights reserved.

关键词： Spectrum efficiency

Development of a Hybrid-driven Autonomous Underwater Glider with a Biologically Inspired Motion control System

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Development of a Hybrid-driven Autonomous Underwater Glider ...

Asian control Conference

作者： Khalid Isa M. R. Arshad Embedded Computing System Research Group (EmbCos) Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia (UTHM) Underwater Control and Robotics Group (UCRG) School of Electrical and Electronic Engineering Engineering Campus Universiti Sains Malaysia (USM)

ISBN: (纸本)9781479978632

This paper presents prototype development of a hybrid-driven autonomous underwater glider with a biologically inspired motion control system. The hybrid-driven glider with an independently controllable wings and a rudder was developed to overcome the drawback of a typical buoyancy-driven underwater glider in terms of speed and maneuverability. However, it is difficult to control the glider due to the high nonlinear and time-varying dynamic behavior of the glider;uncertainties in hydrodynamics coefficients;and disturbances by water currents. Thus, a robust and reliable bio-inspired controller algorithm has been designed. The controller algorithm has been designed to mimic a human innate control mechanism, which is known as homeostatic controller. The performance of the homeostatic controller of the hybrid-driven glider has been analyzed via simulation and experimental. From the simulation result, our homeostatic controller achieves better performance compared to the LQR, MPC, NN and neuroendocrine controller approaches. Furthermore, validation analysis of the homeostatic controller performance between the simulation and experimental results have shown very satisfactory performance.

关键词： Hybrid-driven underwater glider Homeostatic controller Motion control Homeostasis

An improved quantum algorithm for A-optimal projection

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arXiv 2020年

作者： Pan, Shi-Jie Wan, Lin-Chun Liu, Hai-Ling Wang, Qing-Le Qin, Su-Juan Wen, Qiao-Yan Gao, Fei State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Cryptology P.O. Box 5159 Beijing100878 China Center for Quantum Computing Peng Cheng Laboratory Shenzhen518055 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Dimensionality reduction (DR) algorithms, which reduce the dimensionality of a given data set while preserving the information of original data set as well as possible, play an important role in machine learning and data mining. Duan et al. proposed a quantum version of A-optimal projection algorithm (AOP) for dimensionality reduction [Phys. Rev. A 99, 032311 (2019)] and claimed that the algorithm has exponential speedups on the dimensionality of the original feature space n and the dimensionality of the reduced feature space k over the classical algorithm. In this paper, we correct the complexity of Duan et al.’s algorithm to O(κ4sǫ√sks polylogs(mnǫ )), where κ is the condition number of a matrix that related to the original data set, s is the number of iterations, m is the number of data points and ǫ is the desired precision of the output state. Since the complexity has an exponential dependence on s, the quantum algorithm can only be beneficial for high dimensional problems with a small number of iterations s. To_ get a further speedup, we proposed an improved quantum AOP algorithm with complexity O(sκ6ǫ√kpolylog(nmǫ )+ s2ǫκ4 polylog(κkǫ )). Our algorithm achieves a nearly exponential speedup if s is large and a polynomial speedup even if s is a small constant compared with Duan et al.’s algorithm. Also, our algorithm shows exponential speedups in n and m compared with the classical algorithm when both κ, k and 1/ǫ are O(polylog(nm)). Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum theory

Fast ORB-SLAM without Keypoint Descriptors

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arXiv 2020年

作者： Fu, Qiang Yu, Hongshan Wang, Xiaolong Yang, Zhengeng He, Yong Zhang, Hong Mian, Ajmal The National Engineering Laboratory for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan University China The Department of Computing Science University of Alberta Canada Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University China The Southern University of Science and Technology Shenzhen China The School of Mathematics and Information Science Shaanxi Normal University China The Department of Computer Science The University of Western Australia WA6009 Australia

Indirect methods for visual SLAM are gaining popularity due to their robustness to environmental variations. ORB-SLAM2 [1] is a benchmark method in this domain, however, it consumes significant time for computing descriptors that never get reused unless a frame is selected as a keyframe. To overcome these problems, we present FastORB-SLAM which is light-weight and efficient as it tracks keypoints between adjacent frames without computing descriptors. To achieve this, a two stage descriptor-independent keypoint matching method is proposed based on sparse optical flow. In the first stage, we predict initial keypoint correspondences via a simple but effective motion model and then robustly establish the correspondences via pyramid-based sparse optical flow tracking. In the second stage, we leverage the constraints of the motion smoothness and epipolar geometry to refine the correspondences. In particular, our method computes descriptors only for keyframes. We test FastORB-SLAM on TUM and ICL-NUIM RGB-D datasets and compare its accuracy and efficiency to nine existing RGB-D SLAM methods. Qualitative and quantitative results show that our method achieves state-of-the-art accuracy and is about twice as fast as the ORB-SLAM2. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical flows

A Mobile Ar End-to-End Integrated Registration Method for Intelligent Assisted Assembly of Rail Transit Equipment

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SSRN

SSRN 2024年

作者： Yong, Jiu Wei, Jianguo Lei, Xiaomei Wang, Yangping Dang, Jianwu Lu, Wenhuan College of Intelligence and Computing Tianjin University Tianjin300072 China The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong Univeristy Lanzhou730070 China The School of Electronic and Information Engineering Lanzhou Jiaotong Univeristy Lanzhou730070 China Meteorological Information and Technological Supporting Center Gansu Province Meteorological Bureau Lanzhou730020 China

To improve the efficiency of rail transit equipment assembly operations, augmented reality (AR) technology is used to integrate rich virtual auxiliary guidance information into the assembly process, establish a virtual-real fusion rail transit assembly operation environment, and strengthen the perception and understanding ability of assembly business personnel to their assembly environments. In this paper, an AR end-to-end integration registration network (AR-EIRNet) is proposed for mobile AR intelligent assisted assembly of rail transit equipment. This network includes three main stages: feature extraction, pose estimation, and registration parameter solving. In the feature extraction stage, multiscale features are extracted based on a feature attention mechanism and local contextual information. In the pose estimation stage, the pose of the assembly object is directly inferred based on the aggregation of multiscale features and global features, and the pose is calibrated using a differentiable renderer. The registration parameter solving stage calculates the AR registration alignment matrix integrate virtual information overlay rendering. In addition, AR-EIRNet utilizes RGB image synthesis enhancement strategies to increase data diversity and enhance the learning of AR assembly objects. Finally, assembly application and utility analyses are conducted on the ZD6 switch machine equipment in rail transit. The results indicate that the registration error of the AR assembly is within 5 mm, and AR-EIRNet has strong stability and robustness, which can effectively improve the assembly operation efficiency. © 2024, The Authors. All rights reserved.

关键词： Augmented reality

Decentralized Nonconvex Robust Optimization over Unsafe Multiagent Systems: System Modeling, Utility, Resilience, and Privacy Analysis

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arXiv 2024年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Cheng, Huqiang Guo, Xiaoyu Huang, Tingwen School of Automation Central South University Changsha410083 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Key Laboratory of Dependable Services Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing400044 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Privacy leakage and Byzantine failures are two adverse factors to the intelligent decision-making process of multiagent systems (MASs). Considering an unsafe MAS with these two issues, this paper targets the resolution of a class of nonconvex optimization problems under the Polyak-Lojasiewicz (P-L) condition. To address this problem, we first identify and construct the unsafe MAS model. Under this kind of unfavorable MASs, we mask the local gradients with Gaussian noises and adopt a resilient aggregation method self-centered clipping (SCC) to design a differentially private (DP) decentralized Byzantine-resilient algorithm, namely DP-SCC-PL, which simultaneously achieves differential privacy and Byzantine resilience. The convergence analysis of DP-SCC-PL is challenging since the convergence error can be contributed jointly by privacy-preserving and Byzantine-resilient mechanisms, as well as the nonconvex relaxation, which is addressed via seeking the contraction relationships among the disagreement measure of reliable agents before and after SCC aggregation, together with the optimal gap. Theoretical results reveal that DP-SCC-PL achieves consensus among all reliable agents and sublinear (inexact) convergence with well-designed step-sizes. It has also been proved that if there are no privacy issues and Byzantine agents, then the asymptotic exact convergence can be recovered. Numerical experiments verify the utility, resilience, and differential privacy of DP-SCC-PL by tackling a nonconvex optimization problem satisfying the P-L condition under various Byzantine attacks. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy