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1.
We introduce a novel scheme for automatically deriving synthetic walking (locomotion) and movement (steering and avoidance) behavior in simulation from simple trajectory samples. We use a combination of observed and recorded real‐world movement trajectory samples in conjunction with synthetic, agent‐generated, movement as inputs to a machine‐learning scheme. This scheme produces movement behavior for non‐sampled scenarios in simulation, for applications that can differ widely from the original collection settings. It does this by benchmarking a simulated pedestrian's relative behavioral geography, local physical environment, and neighboring agent‐pedestrians; using spatial analysis, spatial data access, classification, and clustering. The scheme then weights, trains, and tunes likely synthetic movement behavior, per‐agent, per‐location, per‐time‐step, and per‐scenario. To prove its usefulness, we demonstrate the task of generating synthetic, non‐sampled, agent‐based pedestrian movement in simulated urban environments, where the scheme proves to be a useful substitute for traditional transition‐driven methods for determining agent behavior. The potential broader applications of the scheme are numerous and include the design and delivery of location‐based services, evaluation of architectures for mobile communications technologies, what‐if experimentation in agent‐based models with hypotheses that are informed or translated from data, and the construction of algorithms for extracting and annotating space‐time paths in massive data‐sets. 相似文献
2.
《International Journal of Digital Earth》2013,6(1):65-77
Abstract Collision detection is an important component in simulation applications which are based on virtual geographic information system (VGIS). In this paper, an effective collision detection algorithm for multiple objects in VGIS, VGIS-COLLIDE, is presented. The algorithm firstly integrates existing quadtree, which is the global hierarchical structure of VGIS, with axis-aligned bounding box of object to perform the broad-phase of collision detection. After that, exact collision detection between two objects which have passed the broad-phase of collision detection is performed. The algorithm makes no assumption about input primitives or object's motion and is directly applicable to all triangulated models. It can be applicable to both rigid and deformable objects without preprocessing. The performance of the algorithm has been demonstrated in several environments consisting of a high number of objects with hundreds of thousands of triangles. 相似文献
3.
室内障碍地图在呈现给用户端浏览的同时,也是自主运动视觉机器人路径规划和障碍规避的依据。由于自主运动视觉机器人的起始位姿选择具有随机性,当机器人沿随机方向行走时,往往导致所建室内障碍地图产生偏斜。本文利用单张已标定像片检测视觉正交灭点,结合相机几何透视原理和灭点几何特性,提出了一种室内机器人偏航角的简单快速检测方法,并成功应用于自主运动机器人的轨迹优化和所建障碍地图的方向校正。对比试验表明,基于视觉灭点的室内机器人偏航角检测方法精度高,在纠正所建障碍地图朝向的同时,保证了机器人运行轨迹短、耗时低,具有良好的推广应用前景。 相似文献
4.
Yujia Xie Meizhen Wang Xuejun Liu Ziran Wang Bo Mao Feiyue Wang Xiaozhi Wang 《Transactions in GIS》2021,25(1):450-467
Current studies on video trajectory retrieval focus on the retrieval and analysis of image content, neglecting the gap between the spatiotemporal continuity of retrieval conditions and the spatiotemporal discontinuity of multi‐camera video trajectories. In this study, we propose a method for the spatiotemporal retrieval of dynamic video object trajectories in geographic scenes. Based on the camera calibration, the proposed method organizes the scene, cameras, and trajectories, constructs the spatiotemporal constraints, and queries the trajectories using two measures: camera‐by‐camera retrieval and global trajectory retrieval. The proposed method was verified through experiments, and the results demonstrate that both measures can query trajectories effectively and reduce the spatiotemporal video review range under different spatiotemporal constraints. Furthermore, compared with camera‐by‐camera retrieval, global trajectory retrieval can reduce the spatiotemporal video review range further and return more accurate results. The proposed method may provide support for the spatial analysis and understanding of surveillance video data. 相似文献
5.
针对新型半潜式无人艇在导航航行过程中轨迹跟踪误差较大的问题,提出基于模型预测控制（MPC）的轨迹跟踪控制方法．并建立新型半潜式无人艇的运动模型,基于实际参数,构建MPC目标函数和系统约束条件,将半潜式无人艇轨迹跟踪问题转化为最优值问题;利用仿真软件,对控制算法进行了仿真分析. 利用卫星定位设备进行了导航轨迹跟踪试验．仿真与试验结果表明:基于MPC的轨迹跟踪控制方法提高了半潜式无人艇的导航轨迹跟踪精度,跟踪精度比原有PID控制方法提高了50％左右. 相似文献
6.
With the increasing use of mobile devices, a lot of tracks of movement of objects are being collected. The advanced trajectory data mining research has allowed the discovery of many types of patterns from these data, like flocks, leadership, avoidance, frequent sequences, and other types of patterns. In this article we introduce a new kind of pattern: a chasing behavior between trajectories. We present the main characteristics of chasing and propose a new method that extracts this new kind of trajectory behavior pattern, considering time, distance, and speed as the main thresholds. Experimental results show that our method finds patterns that are not discovered by related approaches. 相似文献
7.
在缺少真实下视阵列合成孔径雷达（synthetic aperture radar，SAR）系统而带来数据获取和成像算法研究等困难的当下，下视阵列SAR三维仿真的研究具有重要意义。为了还原载机平台真实的飞行航迹，验证阵列SAR技术在高层建筑物密集城区的地形测绘能力，摒弃传统仿真研究基于匀速直线运动的假设，以高度骤变的城市建筑物为对象，分析构建了多输入多输出（multiple input multiple output，MIMO）下视阵列SAR非理想航迹运动误差模型，提出了非理想航迹城市建筑群MIMO下视阵列SAR三维距离多谱勒成像算法。利用航空平台的航迹与姿态建模仿真技术，以及快速高效的回波仿真技术对成像算法进行了仿真实验，验证了方法的正确性和有效性。 相似文献
8.
轨迹大数据的关键瓶颈之一是轨迹数据海量的数据规模对轨迹的分析、挖掘和应用的限制，因而各类针对轨迹数据的压缩方法是轨迹大数据研究的重点。现有轨迹压缩算法重视对轨迹数据的单一维度时空特征的保持，而缺乏压缩算法对多维度时空特征影响的研究。本文选取MBR面积误差、距离误差、方向误差、速度误差、压缩率和压缩速度等轨迹数据多维度时空特征，分别从轨迹的几何特征、运动特征和压缩效率3个层面对典型轨迹压缩方法进行评价。同时，为了系统观察轨迹压缩算法在不同压缩尺度上对轨迹时空特征的影响规律，本文采用多个尺度压缩结果的评价方法。研究结果表明，在整体效果上那些考虑了轨迹运动特征的压缩算法（如TD_TR算法）对轨迹的总体时空特征保持较好；并且不同的压缩算法对时空特征的影响总体上具有随着尺度变化的一致性，可见压缩尺度是决定压缩效果的核心因素。 相似文献
9.
We sketch the evolution of station trajectory models used in crustal motion geodesy over the last several decades, and describe some recent generalizations of these models that allow geodesists and geophysicists to parameterize accelerating patterns of displacement in general, and postseismic transient deformation in particular. Modern trajectory models are composed of three sub-models that represent secular trends, annual oscillations, and instantaneous jumps in coordinate time series. Traditionally the trend model invoked constant station velocity. This can be generalized by assuming that position is a polynomial function of time. The trajectory model can also be augmented as needed, by including one or more logarithmic transients in order to account for typical multi-year patterns of postseismic transient motion. Many geodetic and geophysical research groups are using general classes of trajectory model to characterize their crustal displacement time series, but few if any of them are using these trajectory models to define and realize the terrestrial reference frames (RFs) in which their time series are expressed. We describe a global GPS reanalysis program in which we use two general classes of trajectory model, tuned on a station by station basis. We define the network trajectory model as the set of station trajectory models encompassing every station in the network. We use the network trajectory model from the each global analysis to assign prior position estimates for the next round of GPS data processing. We allow our daily orbital solutions to relax so as to maintain their consistency with the network polyhedron. After several iterations we produce GPS time series expressed in a RF similar to, but not identical with ITRF2008. We find that each iteration produces an improvement in the daily repeatability of our global time series and in the predictive power of our trajectory models. 相似文献
10.
Guannan Li Shengsheng Lin Xiu Lu Liangchen Zhou Bingxian Lin Guonian Lv 《Transactions in GIS》2023,27(2):425-449
Identifying and tracking objects in surveillance videos is an important means of mining information during surveillance. Currently, most object-tracking methods rely only on image features, which cannot accurately express the motion of the tracked object in real geographical scenes and are easily influenced by occlusion and surrounding objects having similar features. However, tracked objects, such as pedestrians and vehicles, usually move in geographical space with fixed patterns of motion, and the motion in a short time is constrained by geographical space and time, the motion trajectory is predictable, and the range of motion is limited. Therefore, based on the SiamFC object tracking framework, this study introduces geographical spatiotemporal constraints into the tracking framework and proposes the GeoSiamFC method. The objective of this is to: (1) construct the mapping relationship between geographical space and image space to solve the problem that the pixel movement within the image after perspective imaging cannot accurately express the motion of the tracked object in a real geographical scene; (2) add candidate search areas according to the predicted trajectory location to correct the tracking errors caused by the occlusion of the object; and (3) focus on the search for the range of motion of the mapped pixel within the image space according to the limited geographical range of motion of the tracked objects in a certain time to reduce the interference of similar objects within the search area. In this study, separate experiments were conducted on a common test dataset using multiple methods to deal with challenges such as occlusion and illumination changes. In addition, a robust test dataset with noise addition and luminance adjustment based on the common test dataset was used. The results show that GeoSiamFC outperforms other object-tracking methods in the common test dataset with a precision score of 0.995 and a success score of 0.756 compared with most other object-tracking algorithms under the base condition of using only shallow networks. Moreover, GeoSiamFC maintained the highest precision score (0.970) and high success score (0.734) in the more challenging robust test dataset as well. The tracking speed of 59 frames per second far exceeds the real-time requirement of 25 FPS. Geographical spatiotemporal constraints were considered to improve tracker performance while providing real-time feedback on the motion trajectory of the target in geographical space. Thus, the proposed method is suitable for real-time tracking of the motion trajectory of a target in real geographical scenes in various surveillance videos. 相似文献
11.
In order to better understand the movement of an object with respect to a region, we propose a formal model of the evolving spatial relationships that transition between local topologies with respect to a trajectory and a region as well as develop a querying mechanism to analyze movement patterns. We summarize 12 types of local topologies built on trajectory‐region intersections, and derive their transition graph; then we capture and model evolving local topologies with two types of trajectory‐region strings, a movement string and a stop‐move string. The stop‐move string encodes the stop information further during a trajectory than the movement string. Such a string‐format expression of trajectory‐region movement, although conceptually simple, carries unprecedented information for effectively interpreting how trajectories move with respect to regions. We also design the corresponding Finite State Automations for a movement string as well as a stop‐move string, which are used not only to recognize the language of trajectory‐region strings, but also to deal effectively with trajectory‐region pattern queries. When annotated with the time information of stops and intersections, a trajectory‐region movement snapshot and its evolution during a time interval can be inferred, and even the relationships among trajectories with respect to the same region can be explored. 相似文献
12.
Geostatistical characterization of local DEM error is usually based on the assumption of a stationary variogram model which requires the mean and variance to be finite and constant in the area under investigation. However, in practice this assumption is appropriate only in a restricted spatial location, where the local experimental variograms vary slowly. Therefore, an adaptive method is developed in this article to model non‐stationary variograms, for which the estimator and the indicator for characterization of spatial variation are a Voronoi map and the standard deviation of mean values displayed in the Voronoi map, respectively. For the adaptive method, the global domain is divided into different meshes with various sizes according to the variability of local variograms. The adaptive method of non‐stationary variogram modeling is applied to simulating error surfaces of a LiDAR derived DEM located in Sichuan province, China. Results indicate that the locally adaptive variogram model is more accurate than the global one for capturing the characterization of spatial variation in DEM errors. The adaptive model can be considered as an alternative approach to modeling non‐stationary variograms for DEM error surface simulation. 相似文献
13.
Integrated compression of vehicle spatio‐temporal trajectories under the road stroke network constraint 
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下载免费PDF全文 With fast growth of all kinds of trajectory datasets, how to effectively manage the trajectory data of moving objects has received a lot of attention. This study proposes a spatio‐temporal data integrated compression method of vehicle trajectories based on stroke paths coding compression under the road stroke network constraint. The road stroke network is first constructed according to the principle of continuous coherence in Gestalt psychology, and then two types of Huffman tree—a road strokes Huffman tree and a stroke paths Huffman tree—are built, based respectively on the importance function of road strokes and vehicle visiting frequency of stroke paths. After the vehicle trajectories are map matched to the spatial paths in the road network, the Huffman codes of the road strokes and stroke paths are used to compress the trajectory spatial paths. An opening window algorithm is used to simplify the trajectory temporal data depicted on a time–distance polyline by setting the maximum allowable speed difference as the threshold. Through analysis of the relative spatio‐temporal relationship between the preceding and latter feature tracking points, the spatio‐temporal data of the feature tracking points are all converted to binary codes together, accordingly achieving integrated compression of trajectory spatio‐temporal data. A series of comparative experiments between the proposed method and representative state‐of‐the‐art methods are carried out on a real massive taxi trajectory dataset from five aspects, and the experimental results indicate that our method has the highest compression ratio. Meanwhile, this method also has favorable performance in other aspects: compression and decompression time overhead, storage space overhead, and historical dataset training time overhead. 相似文献
14.
Wetland inventory maps are essential information for the conservation and management of natural wetland areas. The classification framework is crucial for successful mapping of complex wetlands, including the model selection, input variables and training procedures. In this context, deep neural network (DNN) is a powerful technique for remote sensing image classification, but this model application for wetland mapping has not been discussed in the previous literature, especially using commercial WorldView-3 data. This study developed a new framework for wetland mapping using DNN algorithm and WorldView-3 image in the Millrace Flats Wildlife Management Area, Iowa, USA. The study area has several wetlands with a variety of shapes and sizes, and the minimum mapping unit was defined as 20 m2 (0.002 ha). A set of potential variables was derived from WorldView-3 and auxiliary LiDAR data, and a feature selection procedure using principal components analysis (PCA) was used to identify the most important variables for wetland classification. Furthermore, traditional machine learning methods (support vector machine, random forest and k-nearest neighbor) were also implemented for the comparison of results. In general, the results show that DNN achieved satisfactory results in the study area (overall accuracy = 93.33 %), and we observed a high spatial overlap between reference and classified wetland polygons (Jaccard index ∼0.8). Our results confirm that PCA-based feature selection was effective in the optimization of DNN performance, and vegetation and textural indices were the most informative variables. In addition, the comparison of results indicated that DNN classification achieved relatively similar accuracies to other methods. The total classification errors vary from 0.104 to 0.111 among the methods, and the overlapped areas between reference and classified polygons range between 87.93 and 93.33 %. Finally, the findings of this study have three main implications. First, the integration of DNN model and WorldView-3 image is useful for wetland mapping at 1.2-m, but DNN results did not outperform other methods in this study area. Second, the feature selection was important for model performance, and the combination of most relevant input parameters contributes to the success of all tested models. Third, the spatial resolution of WorldView-3 is appropriate to preserve the shape and extent of small wetlands, while the application of medium resolution image (30-m) has a negative impact on the accurate delineation of these areas. Since commercial satellite data are becoming more affordable for remote sensing users, this study provides a framework that can be utilized to integrate very high-resolution imagery and deep learning in the classification of complex wetland areas. 相似文献
15.
以运动结构特征为约束条件的序列影像匹配,是基于多变量核密度函数,采用非参数均值漂移方法估计最优局部运动相似性结构特征的过程。核密度函数的带宽大小决定了匹配方法的收敛速度和精度。本文提出了一种可变带宽的自适应运动结构特征的车载全景序列影像匹配方法。首先以采样点在空间域和光流域的局部空间结构定义自适应的带宽矩阵。采用局部光流特征向量的距离加权法,描述光流域上运动相似性结构特征的松弛扩散过程。然后给出自适应多变量核密度函数的表达形式,并探讨了均值漂移向量的求解、终止条件以及种子点的选择方法。最后融合多尺度SIFT描述特征与运动结构特征,建立统一的全景影像匹配框架。试验选择车载移动测量系统获取的城市球全景序列影像,结果表明在内点率变化、物方尺度变化等情况下,本文方法可以实现自适应运动结构特征的相似性度量,提高匹配的正确点数和匹配率,算法表现出较强的稳键性。 相似文献
16.
利用三体问题平动点附近存在的流形实现低能耗轨道转移是当前飞行动力学研究中的热点。由于三体问题没有严格的解析解,因此往往采用数值算法来设计轨道。这种方法计算量大,耗费大量的时间和资源。在已有理论的基础上,这里提出了一种基于二体模型和三体模型相结合的轨道设计方法,在相空间中实现轨道的加速匹配与搜索,提高整个设计过程的效率。最后,利用该方法实现了一条从月球驻留轨道到地月系L1点Halo轨道的低能耗转移轨道。仿真结果表明,该方法是高效和可靠的。 相似文献
17.
在西部黄土高原复杂地形地貌下构建采煤沉陷盆地和提取水平位移的难度较大,传统地表沉降监测手段只能获取线状数据,效率低,而重复轨道合成孔径雷达干涉测量技术在大梯度形变区域易出现失相干现象,难以达到矿区地表沉降监测精度要求。提出了一种基于无人机载激光雷达点云数据构建沉陷盆地和提取水平位移的方法。结合多地形因子构建深度神经网络（deep neural network,DNN）模型,提取沉陷盆地构建过程中受地形影响较小的特征稳定区,利用较优插值算法对稳定区进行拟合,得到完整沉陷盆地。为了提取采煤地表水平移动信息,将二进制形状上下文特征描述算子与多地形因子融合起来,以改进特征匹配算法。基于此设计地表水平移动提取方案,提取主断面水平移动信息,同时对水平移动提取误差与点云密度、地形因子进行定量分析。榆神矿区结果表明,利用结合地形因子的DNN模型能有效提取特征稳定区,在复杂地貌下减小了沉陷建模误差,为构建采煤沉陷盆地提供了一种新方法;利用融合地形特征的改进特征匹配算法提取的水平移动曲线符合采煤沉陷水平移动基本规律,与水平移动偏差相关性较强的地形因子可用于衡量改进特征匹配算法对水平移动提取误差的大小。 相似文献
18.
宽视场遥感相机在轨成像期间,受地球自转、卫星颤振、姿态机动等因素影响而产生像移,导致成像质量降低。为此,提出了一种适用于宽视场遥感相机的像移速度模型,并考虑了离轴角对计算精度的影响,推导了离轴三反相机像移速度和偏流角解析式。以某卫星为例,仿真分析了3种典型成像模式下像移速度和偏流角在焦面的分布情况,仿真结果与定性分析结果一致,验证了像移速度模型的正确性。在此基础上,针对侧摆兼具俯仰成像模式,提出了相应的像移补偿策略。补偿效果表明,卫星侧摆35°兼具俯仰35°成像时,采用全局优化偏流角匹配策略能保证整个焦面区域的调制传递函数（modulation transfer function,MTF）均大于0.95（16级）;采用局部优化偏流角匹配策略能保证焦面重点观测目标的MTF大于0.95（96级）;采用提出的像移速度匹配策略在分11组调节行周期情况下,能保证整个焦面区域的MTF均大于0.95（16级）。仿真结果表明,提出的像移补偿策略能有效解决侧摆兼具俯仰成像时的像质下降问题,可为宽视场遥感相机像移补偿提供可靠依据。 相似文献
19.
为解决大数据量带来的热力图生成效率低的问题,引入基于图形处理器(graphic processing unit,GPU)的并行计算方法,并结合轨迹线模型,提出了一种利用GPU加速的轨迹线热力图生成显示方法。首先,针对轨迹点分布不均、邻域半径设置不合理等条件下产生的热力值不连续、不均等问题,采用轨迹线模型提升了热力图的效果。其次,针对大规模数据计算产生的热力图生成效率低的问题,通过GPU并行计算并配合内核函数参数调优、循环展开、像素缓冲对象显示等策略大幅提升算法计算效率。实验结果表明,所提方法较传统的基于中央处理器（central processing unit, CPU）的方法计算效率提升了5~30倍,且随着图像分辨率和轨迹数据的增加,算法加速比有逐步上升的趋势。 相似文献
20.
人群运动估计是人群行为分析的重要步骤。特定场景的人群运动分析和监控,是维护公共安全和社会稳定的一个必要措施,也是视频监控领域的一个研究难点。利用鱼眼相机视场大、无视觉盲区的优点,提出了一种基于特征点光流的人群运动估计方法。首先,采用一种基于面积反馈机制的混合高斯背景差分方法,对原始视频图像进行预处理,并利用圆拟合的方法获取兴趣区域;其次,为了在保证准确描述人群目标的同时提高算法的实时性,提出一种基于边缘密度非均匀采样的人群特征点提取方法来描述运动的人群目标,并利用Lucas & Kanade光流法计算光流场;最后,为了解决远近人群的尺寸大小不一致的问题和鱼眼相机的畸变问题,采用鱼眼相机的透视加权模型,计算人群运动加权统计直方图,获取人群在鱼眼图像中的全局运动方向和速度。实验结果表明,针对密集的人群,该方法能有效、实时地估计人群的运动方向和速度,为人群行为分析提供有力的研究基础。 相似文献