基于3D GIS无人直升机地面站系统软件设计与实现

为了实现无人直升机地面站系统的空间数据处理、三维可视化和导航的功能,提出了基于3D GIS无人直升机地面站系统软件设计及其实现的方法.首先对无人直升机的整体系统框架进行说明,然后对地面站系统的软件框架设计和各个功能模块做了详细的分析,在此基础上重点分析了利用World Wind Java软件开发包来实现3D GIS导航的过程.整个地面站软件系统使用Java语言编写,嵌入3DGIS.最后以实例证明了该地面站系统软件的可行性,并且具有良好的可移植性和可扩充性.     

基于XvMC的MPEG-2硬件解码的研究与实现

研究了如何利用GPU来加速视频解码,概述了MPEG-2视频解码的系统框架,论述了MPEG-2视频解码在Linux下以XvMC(X video motion compensation)为API并基于通用可编程GPU的实现过程,重点讨论了MPEG-2视频解码中IDCT(inverse discrete cosine transform)和运动补偿的实现,提出了新的优化算法.MPEG-2视频解码算法具有一定的通用性,实验结果表明,与传统的解码方式相比,该解码器不仅能加速视频解码,还能有效降低CPU的利用率和电脑的功耗.     

基于ROI的智能交通系统摄像机控制算法

针对城市道路监控的需求,提出了一种基于感兴趣区域的摄像机自适应控制方法。它作为车牌识别系统的一个辅助功能,在固定光圈的情况下,能够根据车牌识别和运动检测的反馈信息自适应地调节摄像机的快门和增益,获取较好质量的图片,从而达到提高车牌识别率的作用,特别是该方法能够大大降低强逆光和强眩光现象对采集图像质量的影响。     

超空泡水下航行器定深控制研究

极高的航速使得对超空泡水下航行器的控制变得异常复杂. 为了对其深度进行有效控制, 必须对其纵平面运动特性进行研究. 本文首先建立了超空泡水下航行器的纵平面运动模型, 分析了其纵平面运动特性; 然后进行了控制算法的综合; 最后, 仿真及试验结果均验证了所设计的航行器纵平面运动控制算法的有效性. 试验结果表明该控制系统具有较高的控制精度. 本文的研究成果为进一步研究水下超空泡航行器的运动控制提供了必要的理论基础.     

Non-rigid metric reconstruction from perspective cameras

The metric reconstruction of a non-rigid object viewed by a generic camera poses new challenges since current approaches for Structure from Motion assume the rigidity constraint of a shape as an essential condition. In this work, we focus on the estimation of the 3-D Euclidean shape and motion of a non-rigid shape observed by a perspective camera. In such case deformation and perspective effects are difficult to decouple – the parametrization of the 3-D non-rigid body may mistakenly account for the perspective distortion. Our method relies on the fact that it is often a reasonable assumption that some of the points on the object’s surface are deforming throughout the sequence while others remain rigid. Thus, relying on the rigidity constraints of a subset of rigid points, we estimate the perspective to metric upgrade transformation. First, we use an automatic segmentation algorithm to identify the set of rigid points. These are then used to estimate the internal camera calibration parameters and the overall rigid motion. Finally, we formulate the problem of non-rigid shape and motion estimation as a non-linear optimization where the objective function to be minimized is the image reprojection error. The prior information that some of the points in the object are rigid can also be added as a constraint to the non-linear minimization scheme in order to avoid ambiguous configurations. We perform experiments on different synthetic and real data sets which show that even when using a minimal set of rigid points and when varying the intrinsic camera parameters it is possible to obtain reliable metric information.     

迭代学习的高速伺服系统位置控制策略

针对高速运动伺服控制系统的精确位宣跟踪控制问题,在A型迭代学习控制算法的基础上,提出了一种基于比例一预期迭代学习控制的位置控制策略,并将其应用于建立的交流永磁同步电机模型,最后利用Matlab进行仿真研究。结果表明,此控制策略仅需少量对象信息就能满足系统的性能要求。它与常见迭代学习控制算法相比,具有位置控制精度高、学习收敛速度快等优点。     

Light-weight salient foreground detection for embedded smart cameras

An embedded smart camera is a stand-alone unit that not only captures images, but also includes a processor, memory and communication interface. Battery-powered, embedded smart cameras introduce many additional challenges since they have very limited resources, such as energy, processing power and memory. Computer vision algorithms running on these camera boards should be light-weight and efficient. Considering the memory requirements of an algorithm and its portability to an embedded processor should be an integral part of the algorithm design in addition to the accuracy requirements. This paper presents a light-weight and efficient background modeling and foreground detection algorithm that is highly robust against lighting variations and non-static backgrounds including scenes with swaying trees, water fountains and rain. Compared to many traditional methods, the memory requirement for the data saved for each pixel is very small in the proposed algorithm. Moreover, the number of memory accesses and instructions are adaptive, and are decreased depending on the amount of activity in the scene. Each pixel is treated differently based on its history, and instead of requiring the same number of memory accesses and instructions for every pixel, we require less instructions for stable background pixels. The plot of the number of unstable pixels at each frame also serves as a tool to find the video portions with high activity. The proposed method selectively updates the background model with an automatically adaptive rate, thus can adapt to rapid changes. As opposed to traditional methods, pixels are not always treated individually, and information about neighbors is incorporated into decision making. The results obtained with nine challenging outdoor and indoor sequences are presented, and compared with the results of different state-of-the-art background subtraction methods. The ROC curves and memory comparison of different background subtraction methods are also provided. The experimental results demonstrate the success of the proposed light-weight salient foreground detection method.     

Video analysis based on volumetric event detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television(CCTV)data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today's approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called "pre-suspicion" mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.     

基于MFC和OpenGL的喷砼机器人三维仿真平台的设计

以PJR-2X喷砼机器人为例,介绍了一种基于VC++的MFC和OpenGL的人机交互式三维仿真平台的设计方法。该方法采用Solidworks软件对该机器人建模,并将三维模型保存为.STL文件,然后导入3DSMax中确立纹理坐标,输出的3DS文件再导入Deep Exploration中进行三维模型材质、纹理的二次处理,最后通过MFC导入到以OpenGL为标准建立的工作场景中进行场景渲染,从而得到逼真的机器人三维虚拟仿真平台。实际应用表明,该仿真平台能精确表达机器人的正逆运动特性,并能示教演示。     

动画专业人物基础素描特征浅析

动画素描表现形式与技法具有绘画艺术的普遍共性特征,多角度全方位理解与掌握人体造型与运动规律,简洁准确地表现人物的形体特征,将写生能力与形象记忆能力相结合并同步提高,为创造形象和专业学习打好基础。