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2016 International Conference on Computer, Information and Telecommunication Systems (CITS)最新文献

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Chunk-wise face model based gaze correction in conversational videos with single camera 基于块智能面部模型的单摄像头会话视频凝视校正
J. Lu, Xiaoming Tao, Linhao Dong, N. Ge
Eye contact is one of critical aspects of video conference. In current video conference systems, an important problem is the shortage of eye contact. This is due to the direction disparity between the normal of focus plane of camera and the interlocutor's gaze. Currently, the state-of-the-method performs well on gaze correction with only single webcam. However, this method that applied to the sequences with face obscured has shown unsatisfying results. In this paper, we propose a novel model-based gaze correction scheme to independently build the eye models, the nose model and the mouth model independently so that the occlusion problem can be solved effectively. To be more specific, by rotating the aforementioned four models at a pre-detected displacement, the degree of gaze correction can be obtained. The facial appearance that is occluded will not be rotated, which will prevent the occluding object from being distorted. Experiment results show that, under different parts of occluding objects, our method can achieve better performance on gaze correction than the current method in terms of perceived quality in two scenes usually appearing in conversational videos.
眼神交流是视频会议的一个重要方面。在目前的视频会议系统中,一个重要的问题是缺乏眼神交流。这是由于相机对焦平面的法线与对话者的视线方向不一致造成的。目前,该方法仅在单个网络摄像头的注视校正上表现良好。然而,该方法在人脸模糊序列中的应用效果并不理想。本文提出了一种新的基于模型的凝视校正方案,分别独立构建眼、鼻、口模型,从而有效地解决了遮挡问题。更具体地说,通过在预先检测到的位移下旋转上述四个模型,可以获得凝视校正的程度。被遮挡的面部外观不会被旋转,这样可以防止被遮挡的物体被扭曲。实验结果表明,在对话性视频中常见的两个场景中,在遮挡物体的不同部位下,我们的方法在注视校正方面的感知质量优于目前的方法。
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引用次数: 1
Cooperative spectrum sensing using discrete goodness of fit testing for multi-antenna cognitive radio system 基于离散拟合优度测试的多天线认知无线电系统协同频谱感知
Yuxin Li, Yinghui Ye, G. Lu, Cai Xu
In diversity-based multiple antenna cognitive radio system, the performance of the existing cooperative spectrum sensing algorithms based on covariance matrix degrades seriously due to the channel correlation. In this paper, we formulate spectrum sensing as a multinomial distribution test problem, and then apply the Discrete Anderson Darling (DAD) test, one of discrete goodness of fit tests, to examining the above problem. The proposed algorithm dubbed DAD sensing is assessed through Monte Carlo simulations. It is shown that the performance of DAD sensing is robust to the antenna correlation and noise uncertainty.
在基于分集的多天线认知无线电系统中,由于信道相关性的存在,现有基于协方差矩阵的协同频谱感知算法的性能严重下降。本文将频谱感知表述为一个多项分布检验问题,然后应用离散拟合优度检验之一的离散安德森达令检验来检验上述问题。通过蒙特卡罗模拟对所提出的DAD传感算法进行了评估。结果表明,该方法对天线相关性和噪声不确定性具有较强的鲁棒性。
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引用次数: 2
A relay node placement for free space optical communication system under multi-user environments 多用户环境下自由空间光通信系统中继节点布置
Genfa Zhang, Jun Yan, Bingcheng Zhu, Weiping Zhu
In this paper, a relay node placement for free-space optical (FSO) communication system are proposed for different multi-user and communication service requirements. First, the relay problem is formulated as the constraint multi-objective optimization framework. The outage probability function of each user, the obstacle and feasible region are described as the objective function and the constraint function respectively. Then, the multi-objective optimization problem is transformed into a single-objective optimization problem, according to each different communication service requirement. At last, the optimal position of each relay node can be obtained using the linear weight parameter method. The simulation test are carried out under different practical environments.
针对不同的多用户和通信业务需求,提出了一种自由空间光通信系统中继节点布置方案。首先,将中继问题表述为约束多目标优化框架。将每个用户的中断概率函数、障碍和可行区域分别描述为目标函数和约束函数。然后,根据不同的通信服务需求,将多目标优化问题转化为单目标优化问题。最后,利用线性权参数法得到各中继节点的最优位置。在不同的实际环境下进行了仿真试验。
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引用次数: 2
Learning automata based decision making algorithm for task offloading in mobile cloud 基于学习自动机的移动云任务卸载决策算法
P. V. Krishna, S. Misra, D. Nagaraju, V. Saritha, M. Obaidat
In recent years, mobile cloud computing (MCC) is treated as one of the important enablers of Internet of Things. MCC has evolved from a mix of mobile computing and cloud computing. Most of the researcher works on MCC focus on the reduction of cost of applications in mobile devices by leveraging cloud technology. The limitations of mobile environment such as computation capacity, battery power and limited memory lead to the integration of cloud technology. The performance of the mobile environment improves by the implementation of task offloading using cloud technology. In this paper, a model for task offloading using learning automata based decision making algorithm (LADMA) is proposed. The algorithm considers the completion time and energy consumption of the tasks during the allocation of the tasks to the suitable VMs in the cloud. The proposed model is tested on Amazon EC2 and Android X 86 Platforms.
近年来,移动云计算(MCC)被视为物联网的重要推动因素之一。MCC是从移动计算和云计算的混合发展而来的。大多数MCC研究人员的工作重点是通过利用云技术来降低移动设备中应用程序的成本。移动环境的局限性,如计算能力、电池电量和有限的内存,导致了云技术的融合。通过使用云技术实现任务卸载,移动环境的性能得到了改善。提出了一种基于学习自动机的决策算法(LADMA)的任务卸载模型。该算法在将任务分配到云中合适的虚拟机时,考虑了任务的完成时间和能耗。该模型在Amazon EC2和Android x86平台上进行了测试。
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引用次数: 20
A novel descriptor optimization method for multispectral images 一种新的多光谱图像描述子优化方法
Z. Fu, B. Luo, Chun Wu, Q. Qin
This paper presents an optimized descriptor method for multispectral images. The method proposed is based on LGHD (Log-Gabor Histogram Descriptor)[1]. Initially, all feature points are detected from Long wave Infrared and Visible spectrum images, and descripted by LGHD, then PCA (Principal Component Analysis) is used to reduce the dimension of the two different descriptors, finally the optimized descriptors are used to match the points. Experimental results show that proposed approach achieves a better matching performance than LGHD.
提出了一种优化的多光谱图像描述符方法。提出的方法基于LGHD (Log-Gabor直方图描述符)[1]。首先从长波红外和可见光谱图像中检测到所有特征点,并对其进行LGHD描述,然后使用主成分分析(PCA)对两种不同描述符进行降维,最后使用优化后的描述符进行点匹配。实验结果表明,该方法比LGHD具有更好的匹配性能。
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引用次数: 1
Study of cooperative diversity scheme based on visible light communication in VANETs VANETs中基于可见光通信的合作分集方案研究
Zongmin Cui, Peng Yue, Yao Ji
Enormous applications which are enabled using Vehicular Ad Hoc Networks (VANETs) require a both efficient and reliable data delivery. Visible Light Communication (VLC), which has high transmission rate without using Radio Frequency (RF) spectrum, is regard as a candidate for data transmission in VANETs. Since a VLC system requires a line-of-sight communication, the position and the posture of LEDs and receivers play key roles in VLC. Unfortunately the position and the posture always change with vehicle motion and may make the performance of VLC become severe and even result in the outage of VLC. In this paper, we present an improved Vehicle-to-Vehicle (V2V) model and an improved Vehicle-to-Infrastructure (V2I) model in consideration of the position and the posture. In order to get diversity gains and reduce the VLC interruption caused by vehicle motion, we propose a VLC based cooperative diversity scheme. Finally simulation results show that the cooperative diversity scheme can decrease the Bit-Error-Rate (BER) significantly and reduce the VLC interruption caused by vehicle motion.
使用车载自组织网络(vanet)的大量应用需要高效可靠的数据传输。可见光通信(VLC)在不使用射频(RF)频谱的情况下具有较高的传输速率,被认为是vanet中数据传输的候选技术。由于VLC系统需要视距通信,因此led和接收器的位置和姿态在VLC中起着关键作用。然而,位置和姿态总是随着车辆的运动而变化,这可能会使VLC的性能变得严重,甚至导致VLC的中断。本文提出了一种考虑位置和姿态的改进的车对车(V2V)模型和改进的车对基础设施(V2I)模型。为了获得分集增益,减少车辆运动造成的VLC中断,提出了一种基于VLC的合作分集方案。仿真结果表明,该合作分集方案能够显著降低误码率,减少车辆运动引起的VLC中断。
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引用次数: 7
Credit scoring using incremental learning algorithm for SVDD 信用评分采用增量学习算法进行SVDD
Yongquan Cai, Yuchen Jiang
Support Vector Data Description (SVDD) has a limitation for dealing with a large dataset or online learning tasks. This work investigates the practice of credit scoring and proposes a new incremental learning algorithm for SVDD based on Karush-Kuhn-Tucker (KKT) conditions and convex hull. Convex hull and part of newly added samples which violates KKT conditions are treated as new training samples instead of previous support vector and entire new arrived samples. The proposed method can achieve comparable training time with traditional incremental learning algorithm for SVDD while have similar classification accuracy with original SVDD.
支持向量数据描述(SVDD)在处理大型数据集或在线学习任务方面存在局限性。本文研究了信用评分的实践,并提出了一种新的基于KKT条件和凸包的SVDD增量学习算法。凸包和部分违反KKT条件的新增样本被视为新的训练样本,而不是之前的支持向量和整个新到达样本。该方法的训练时间与传统的SVDD增量学习算法相当,分类精度与原始SVDD相近。
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引用次数: 2
Missile weapon system-of-systems optimization method based on information entropy 基于信息熵的导弹武器系统-系统优化方法
Xiaochuan Guo, Xinchang Liu, Guiming Chen, Leilei Chang, Xiang Li
This study proposes an optimization method for the missile weapon system-of-systems (MWSoS) based on information entropy. However, there are multiple challenges, such as the diversity of input values and the non uniform measurement standards. Therefore, the information entropy based method is proposed due to its advantages in dealing with these challenges. This method uses the uniform standard to measure the input value of capability indexes, which further proposes an index aggregation evaluation method based on the information entropy. The proposed approach is validated by an illustrated MWSoS optimization example, which shows the practicability and effectiveness of the method. This method can be more efficiently applied for MWSoS optimization, which provides the decision-making basis for missile weapon.
提出了一种基于信息熵的导弹武器系统的优化方法。然而,该方法存在输入值的多样性和测量标准的不统一等诸多挑战。因此,基于信息熵的方法因其在处理这些挑战方面的优势而被提出。该方法采用统一的标准度量能力指标的输入值,并在此基础上提出了一种基于信息熵的指标聚合评价方法。通过一个mwso优化实例验证了该方法的有效性和实用性。该方法可更有效地应用于多目标系统优化,为导弹武器提供决策依据。
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引用次数: 4
Robust power control for cognitive radio networks under spectrum sensing errors 频谱感知误差下认知无线电网络的鲁棒功率控制
Lingsen Zhu, Xiaohui Zhao, Yongjun Xu
Orthogonal frequency division multiplexing (OFD-M)based cognitive radio networks (CRNs) is a promising paradigm to increase spectrum efficiency and achieve flexible resource allocation. However, previous works either lack the consideration of channel uncertainties or ignore the effect of imperfect spectrum sensing. In this paper, we focus on the power control for a downlink OFDM-based CRN with the consideration of both parametric uncertainties and spectrum sensing errors. A robust power control strategy based on the worst case approach to maximize achievable data rate of secondary user is proposed while satisfying the interference constraint and power budget constraint. Simulation results demonstrate that our proposed worst case approach exhibits improved performance since it can obtain a relatively good data rate and provide a better protection for primary user.
基于正交频分复用(OFD-M)的认知无线网络(crn)是提高频谱效率和实现资源灵活分配的一种很有前途的范式。然而,以往的研究要么缺乏对信道不确定性的考虑,要么忽略了不完全频谱感知的影响。本文研究了考虑参数不确定性和频谱感知误差的下行ofdm CRN的功率控制问题。在满足干扰约束和功率预算约束的情况下,提出了一种基于最坏情况的鲁棒功率控制策略,以最大限度地提高辅助用户的可实现数据速率。仿真结果表明,我们提出的最坏情况方法可以获得相对较好的数据速率,并为主用户提供更好的保护,从而提高了性能。
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引用次数: 6
On the improved implementations and performance evaluation of digit-by-digit integer restoring and non-restoring cube root algorithms 逐位整数还原与非还原立方根算法的改进实现与性能评价
Yamin Li, Wanming Chu
This paper describes digit-by-digit integer restoring and non-restoring algorithms for computing the cube root of a 33-bit radicand and gives improved methods for the implementations of the algorithms to speed up the computations. The methods include calculating multiplication products in advance with additions and using carry save adders (CSAs) to calculate the partial remainder at each iteration. The cost/performance is evaluated by implementing the algorithms on an FPGA chip. The results show that the CSA methods achieve performance speedups of 199.63% and 177.06%, for restoring and non-restoring cube root algorithms, respectively.
本文介绍了计算33位根立方根的逐位整数还原算法和非还原算法,并给出了算法实现的改进方法,以提高计算速度。该方法包括预先用加法计算乘法乘积和使用进位保存加法器(csa)计算每次迭代的部分余数。通过在FPGA芯片上实现算法来评估成本/性能。结果表明,CSA方法对恢复立方根算法和非恢复立方根算法的性能分别提高了199.63%和177.06%。
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引用次数: 6
期刊
2016 International Conference on Computer, Information and Telecommunication Systems (CITS)
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