图像融合技术研究的最新进展

图像融合是把同一场景从不同特性、不同时间、不同分辨率传感器获得的多幅图像综合成一幅图像的先进图像处理技术。该技术可以广泛应用在医学、遥感、计算机视觉、气象预 报及军事目标识别等多个领域。介绍了当前图像融合技术的一些最新进展,指出了图像融合 技术可能的发展方向。     

面向仿真数据的电网运行方式可视分析

对真实电网提出故障发生的假设并通过计算检验,观察故障对真实电网的影响。电网仿真能有效发现电网运行中的问题,被广泛应用于电网规划与电网运行方式调整。然而,在实际仿真计算过程中,往往需要依据经验调整电网配置和计算参数,以得到稳定、收敛的电网运行方式。大规模的仿真数据、调整的未知性加之分析的片面性会影响传统人工调整的准确性,为此提出了基于可视化的仿真计算调整方法。分析人员通过与可视分析系统的交互,可以快速认识电网的整体状态,发现问题元件,从而实现高效的仿真调整与计算。最后通过案例分析验证了本可视分析系统的有效性。     

The Influence of Visual and Spatial Reasoning in Interpreting Simulated 3D Worlds

This paper explores the way in which young children (6 year olds) made sense of screen-based images on the computer. The participants were required to interpret 3D-like representations and relate these images to objects in their environment. Both static and relatively dynamic software programs were used in the investigation. Some of the children could not make links between the screen representation and the intended three-dimensional (3D) objects. It is argued that young children should be exposed to activities that establish explicit links between 2D and 3D objects ``away' from the computer before attempting the more difficult links required to interpret and represent 3D objects in ICT contexts. This revised version was published online in July 2006 with corrections to the Cover Date.     

Tracking control of high-performance robots via stabilizing controllers for uncertain systems

The development of flexible manufacturing systems calls for industrial robots characterized by robustness of performance with regard to the variations of the loads and real time specification of the trajectory in the work space. In this paper, the design of a feedback controller guaranteeing such performance is considered. At first, the manipulator dynamics are embedded into a larger class of uncertain dynamical systems and a class of feedback controls is proposed that guarantees uniform ultimate boundedness of the tracking error. Successively, the methodology is specialized for the case of robotic manipulators to track trajectories described in task-oriented coordinates; the proposed control algorithm operates without requiring any explicit coordinate transformation.     

Robust Tracking and Model Following Control with Zero Tracking Error for Uncertain Dynamical Systems

The problem of robust tracking and model following for a class of linear dynamical systems with time-varying uncertain parameters and disturbances is considered. A class of continuous (nonlinear) state feedback controllers is proposed for robust tracking of dynamical signals. The proposed robust tracking controllers can guarantee that the tracking error decreases asymptotically to zero in the presence of uncertain parameters and disturbances. A procedure for designing such a zero tracking state feedback controller is also introduced. Finally, a numerical example is given to demonstrate the validity of the results.     

基于标志点识别的自主车视觉导航

提出了一种基于室内标志点识别的单目视觉导航的方法。在地面上有规律地旋转一些标志点,采用辅助先验知识对标志点进行识别和分割,利用透视投影变换得到标志点与摄像机之间的相对距离,达到通过单目摄像机获得景物深度信息的目的。整个算法结构简单,易于实现,对由照明不均匀和地面反光所引起的各种干扰有较好地抑制作用。     

数字图像注入式红外目标捕获跟踪训练仿真

介绍一种利用数字图像注入构建目标环境来完成目标捕获跟踪仿真训练任务的新方法,该方法通过模拟目标的理论航迹,实时接收并解算编码器输出值,同时与目标的运动方程做综合处理,计算出目标的位置信息,最后在背景中合成目标后按照红外图像的格式将数字图像注入到数字图像处理系统中。该方法可以在不开启红外相机的情况下,方便地完成手动及自动跟踪的训练任务,节约了训练成本,并已成功运用到某光电跟瞄设备的仿真训练系统中。     

A correlative classifiers approach based on particle filter and sample set for tracking occluded target

Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single classifier learn much of occluding background information which results in the decrease of tracking performance, and eventually lead to the failure of the tracking algorithm. This paper presents a new correlative classifiers approach to address the above problem. Our idea is to derive a group of correlative classifiers based on sample set method. Then we propose strategy to establish the classifiers and to query the suitable classifiers for the next frame tracking. In order to deal with nonlinear problem, particle filter is adopted and integrated with sample set method. For choosing the target from candidate particles, we define a similarity measurement between particles and sample set. The proposed sample set method includes the following steps. First, we cropped positive samples set around the target and negative samples set far away from the target. Second, we extracted average Haar-like feature from these samples and calculate their statistical characteristic which represents the target model. Third, we define the similarity measurement based on the statistical characteristic of these two sets to judge the similarity between candidate particles and target model. Finally, we choose the largest similarity score particle as the target in the new frame. A number of experiments show the robustness and efficiency of the proposed approach when compared with other state-of-the-art trackers.     

视觉信号质量评价的挑战与新进展

While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this pa-per, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D im-ages/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.     

Excited state tracking during the relaxation of coordination compounds

The ability to locate minima on electronic excited states (ESs) potential energy surfaces both in the case of bright and dark states is crucial for a full understanding of photochemical reactions. This task has become a standard practice for small- to medium-sized organic chromophores thanks to the constant developments in the field of computational photochemistry. However, this remains a very challenging effort when it comes to the optimization of ESs of transition metal complexes (TMCs), not only due to the presence of several electronic ESs close in energy, but also due to the complex nature of the ESs involved. In this article, we present a simple yet powerful method to follow an ES of interest during a structural optimization in the case of TMCs, based on the use of a compact hole-particle representation of the electronic transition, namely the natural transition orbitals (NTOs). State tracking using NTOs is unambiguously accomplished by computing the mono-electronic wave function overlap between consecutive steps of the optimization. Here, we demonstrate that this simple but robust procedure works not only in the case of the cytosine but also in the case of the ES optimization of a ruthenium nitrosyl complex which is very problematic with standard approaches. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.