Moving object detection in framework of compressive sampling

Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals. In the image application with limited resources the camera data can be stored and processed in compressed form. An algorithm for moving object and region detection in video using a compressive sampling is developed. The algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background scene. The algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated background. This leads to a computationally efficient method and a system compared with the existing motion estimation methods. The experimental results show that the sampling rate can reduce to 25% without sacrificing performance.     

Velocity compensation methods for LPRF modulated frequency stepped-frequency（MFSF） radar

In the high speed target environment, there exists serious Doppler effect in the low pulse repetition frequency (LPRF) modulated frequency stepped frequency (MFSF) radar signal. The velocity range of the target is large and the velocity is high ambiguous, so the single method is difficult to satisfy the velocity measurement requirement. For this problem, a novel method is presented, it is a combination of cross-correlation inner frame velocity measurement and range-Doppler coupling velocity measurement. The cross-correlation inner frame method, overcoming the low Doppler tolerance of the cross-correlation between frames, can obtain the coarse velocity of the high speed target, and then the precision velocity can be obtained with the range-Doppler coupling method. The simulation results confirm the method is effective, and also it is well real-time and easy to the project application.     

一种基于马尔可夫链的高维离群点挖掘算法

提出了一种基于马尔可夫链的离群点检测(outlier detection algorithms based on Markov chain, MRKFOD)算法。该算法把基本数据集看作一个加权无向图,数据集中的每个数据表示一个节点,用每条加权边表示节点之间的相似度;形成一个邻接矩阵,把邻接矩阵当作马尔可夫链中的概率转移矩阵;寻求概率转移矩阵的主要特征向量;把每个节点的主要特征向量值作为每个数据的离群度。实验结果表明,该算法与其他高维离群点挖掘算法相比,在效率及有效处理的维数方面均有显著提高。     

基于SVM数据融合的实时粒子滤波算法

采用粒子滤波的目标跟踪算法在粒子数目较多时计算量大、实时性差,针对该问题提出了一种新的基于支持向量机数据融合的实时粒子滤波算法。该算法在估计窗实时粒子滤波的基础上,使用支持向量机融合窗内不同时刻粒子集,并根据融合的结果更新粒子权值,实现对目标状态的快速跟踪。相对于原算法采用最小化Kullback-Leibler距离来调整估计窗混合分布的权值,该方法的计算复杂度低、速度快,进一步提高了算法的实时性。对纯角度目标跟踪问题的仿真结果表明了该算法的可行性和有效性。     

Person-independent expression recognition based on person-similarity weighted expression feature

A new method to extract person-independent expression feature based on higher-order singular value decomposition (HOSVD) is proposed for facial expression recognition. Based on the assumption that similar persons have similar facial expression appearance and shape, the person-similarity weighted expression feature is proposed to estimate the expression feature of test persons. As a result, the estimated expression feature can reduce the influence of individuals caused by insufficient training data, and henc...     

无人机视觉导航研究综述

对无人机视觉导航的现有算法从视觉处理和状态估计与数据融合两大方面作了分类总结,重点讨论了无人机获取图像的特征提取、视觉传感器同其他传感器的数据融合、以及实时得到状态估计的各种方法,同时,也涉及了未知环境下地图的建立,最后指出了无人机视觉导航在实际应用中面临的主要问题。     

中国农业效率TFP分解及其影响因素分析——基于区域差异的视角

农业关系到国家稳定和人民的生活,是国民经济发展的基础,农业发展的关键在于提高农业效率。运用数据包络分析法,测度了2003—2007中国各省农业生产效率变化,并进行了全要素生产率TFP分解,然后利用这些效率指标以及影响因素的外延数据构成面板数据（Panel Data）建立模型。通过实证分析得出：农业专业技术人员培养和农业经营规模的适度扩大,有助于农业效率的提升,强化财政支出管理也会对其提升起到促进作用。表3,参14。     

基于GIS的网上世博场馆导航系统

网上世博场馆导航系统能够引导游客流向,提高世博会的服务水平.将GIS和虚拟现实技术相结合实现了网上世博场馆虚拟导航系统,系统具备场馆漫游和查询、路线推荐和定制以及流量估计等功能.系统建立了ArcGIS数据库模型,实现了基于FNR树时空数据索引和智能导航组合算法,并利用经验导航路线设计符合用户期望的最佳导航路线.系统能够提供直观、可视、可交互的导航服务.     

操作风险整体评估方法:基于拓扑数据模型的影响图

考虑到一般操作风险数据模型的不足,提出了一种新的数据模型——操作风险拓扑数据模型.它能够包含风险事件发生过程中各种风险原因之间相互关系的信息,且能支持操作风险的影响图度量方法.随后采用基于拓扑数据模型的影响图方法对操作风险整体评估进行了研究.该方法能够辅助分析各个风险原因之间的相关性,并支持基于拓扑数据模型的操作风险数据的统计分析.最后以一家保险企业为例演示了该方法.基于拓扑数据模型的操作风险影像图度量方法针对操作风险特点,关注控制和流程的失败,更充分利用历史事件中蕴含的信息,简化了各风险原因之间的相关性分析.     

营销决策综合效果的DEA评价方法

首先构建了一套评价营销决策综合效果的指标体系,然后运用数据包络分析(DEA)方法对之进行了有效性评价。最后,以新兴公司为依托进行了实证研究,具有一定的实际意义。