基于卡尔曼滤波的导航道路地图匹配方法研究

定位数据与地图数据不符是地图匹配致力解决的问题,目前还没有理想的通用匹配算法,本文针对匹配过程中传统方法对于误差处理的不足,探讨了卡尔曼滤波的相关应用问题,考虑了将动态滤波技术引入地图匹配的直接模式和间接模式,使道路形状相关与道路形状无关情况都可以得到有效地处理,对线性系统和非线性系统都适应,这种对动态系统中观测误差、系统误差进行处理的有效方法,在模拟实验中取得了较好的结果。     

Reconstruction of human neuromuscular control signals using a sliding mode control technique

A sliding mode controller, developed using MATLAB/SIMULINK, is incorporated within an existing model of the complex nonlinear system of the human leg with the aim of identifying the operation of the feedback control system within the body to produce the observed leg movement during walking. The control design procedure first defines a switching function, the so-called sliding surface, which prescribes the required dynamic behaviour of the error between the measured data and the model output. A discontinuous feedback control law is then designed to drive the system trajectories onto the sliding surface and force them to remain there. The attractiveness of sliding mode control for the analysis of biomechanical control systems arises from the equivalent control principle. If a switching surface is selected which ensures exact tracking between the model trajectory and experimentally measured trajectory from a human subject, then the filtered discontinuous control signals from the simulation model provide estimates of the signals required to achieve the observed movement. The inherently robust properties of sliding mode control ensure precise tracking by the model of the actual leg movement, thus enabling the feedback control signal required to carry out the movement to be reconstructed.     

Human interaction recognition using spatial-temporal salient feature

Multimedia Tools and Applications - Depth sensor is widely used today and has great impact in object pose estimation, camera tracking, human actions, and scene reconstruction. This paper presents a...     

基于边缘和局部熵融合的视觉安全性评估方法

针对基于局部熵进行加密图像视觉安全性评估存在块效应的局限性，引入图像的边缘特征，通过共有边缘来衡量加密图像与原始图像的边缘相似度，消除了块效应。由于局部熵对加密等级低的图像不敏感，边缘相似度对加密等级高的图像不敏感，将两个评估方法进行自适应融合，提出[SLEES]（Local Entropy and Edge Similarity，[SLEES]）指标。通过改变图像像素位置和图像像素值的加密方式处理图像和视频帧进行测试，实验结果表明，[SLEES]指标相比传统评估指标有更好的鲁棒性，评估范围更广。     

Estimation of aboveground vegetation biomass based on Landsat-8 OLI satellite images in the Guanzhong Basin,China

This paper presents a method to estimate the aboveground biomass (AGB) through the selection of different estimation methods based on numerous vegetation types (i.e., broadleaf forest, coniferous forest, shrub and grassland) at a regional scale. The proposed method is based on three models, namely, the stepwise regression, an improved back-propagation neural network (Improved BBPNN) model based on the Gaussian error function, and the support vector machine (SVM) technique, Meanwhile, Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) image data and geo-parameters are employed to select 68 feature variables and optimize 213 data samples. Our results reveal that, the stepwise regression method provides the best AGB estimation performance for broadleaf forests and coniferous forests, while the SVM technique shows the best performance for grasslands and shrubs. Different vegetation types should be selected for additional biomass estimation models that have been proven to enhance the biomass estimation. This study on the AGB not only promotes research on the net primary productivity (NPP), but also plays a key role in global carbon cycle research.     

Traffic congestion analysis at the turn level using Taxis' GPS trajectory data

Sensing turn-level or lane-level traffic conditions not only enables navigation systems to provide users with more detailed and finer-grained information, it can also improve the accuracy in the search for the fastest routes and in short-term predictions of traffic conditions. The widespread collection and application of taxis' GPS data enable us to sense urban traffic flow on a large scale. Since current GPS positional accuracy cannot reach the lane level, existing approaches using GPS trajectory data only analyze traffic conditions at the road level. Whereas some studies attempted to detect lane-level traffic conditions using lane-level data, the high cost of data collection considerably limits their practical application. To address this limitation, this article proposes an approach for detecting traffic congestion from taxis' GPS trajectories at the turn level. Based on analyzing features of GPS trajectories and identifying valid trajectory segments, the proposed approach detects congested trajectory segments of three different intensities. It then identifies congestion events in each turning direction through a clustering approach. Finally, congestion intensity, time of the day when congestion occurred and queue length in each turning direction at a road intersection in Wuhan, China are explored and analyzed. The results support the feasibility of this approach for detecting and analyzing traffic congestion at the turn level. Compared with other approaches that detect traffic congestion using GPS trajectory data, the proposed approach analyzes congestion at a finer-grained level (the turn level). Compared with other approaches that detect traffic congestion at the lane level, the proposed approach can sense traffic congestion over a larger area and at a lower cost.     

基于光谱加权低秩矩阵分解的高光谱影像去噪方法

高光谱遥感影像在获取和传输过程中会受到各种类型噪声的污染,不仅降低影像质量,也限制了其后续应用的精度。高光谱影像噪声类型复杂多样,且噪声在不同波段上的强度也并不相同。通过引入光谱域上的权重矩阵,文中提出了一种基于光谱加权低秩矩阵分解的高光谱遥感影像混合噪声去除方法,利用光谱权重矩阵均衡不同波段的噪声强度差异性。为进一步将噪声与纯净影像分离,利用加权核范数最小化来约束纯净高光谱影像的局部低秩结构,并利用交替方向乘子法对所提出的模型进行优化求解。通过对模拟与真实高光谱遥感数据的实验,验证了所提方法的有效性与优越性。