A new technique for velocity estimation of large moving objects

A technique for motion estimation of large moving objects is presented. This technique is based on analyzing the Hartley transform spectrum of the image sequence directly, instead of using it to compute other transforms. In this technique, the fast Hartley transform (FHT) is applied to the image sequence and followed by a peak detection procedure. The location of the peak is related to the velocity of the moving object. Dividing the temporal frequency (f_p) corresponding to the detected peak by the corresponding spatial frequency (k_p) gives the velocity of the moving object. The Fourier spectrum for a spatial frequency of k_p is then computed. This is followed by a peak detection of the Fourier spectrum to validate the previous results and find the direction of the velocity of the moving object. This method is faster than other techniques based on the Fourier transform     

基于三维分层图模型的复杂情况下多运动目标跟踪

复杂情况下的多运动目标跟踪是视频监控中的关 键问题,在多目标运动中相互遮挡时二维视觉信息容易丢失而造 成无法准确跟踪识别目标。本文采用kinect摄像机获取三维视觉信息,从节点、边、空间结 构三个层次上建立目标的三维分 层图模型表征目标的三维特征,并在每层进行通过视频帧间的匹配从而获得三维分层图模型 匹配结果,并根据匹配结果先初 步分析目标跟踪情况,如发生遮挡则通过遮挡区域聚类块与三维分层图模型中各特征匹配确 定其匹配结果,从而得到多运动 目标在复杂运动情况中的跟踪结果。实验表明,在实验室kinect拍摄的视频序列上当目标出 现遮挡等复杂情况,也能取得较 好的跟踪结果,在实验视频中比经典方法的跟踪总体性能指标改善约3%,说明本方法能较好 地实现复杂情况下的多运动目标跟踪。     

Fast MM-PO-based numerical modelling technique for wideband analysis of antennas near conducting objects

A highly efficient computational electromagnetics technique based upon method of moments-physical optics (MM-PO) hybrid formulation combined with the impedance matrix interpolation and a dynamic adaptive frequency sampling for wideband analysis of antennas radiating in the presence of conducting bodies is presented. Sample numerical results demonstrate the capability of the technique     

Computer analysis of scenes with curved objects

Most research efforts in scene analysis have concentrated on the analysis of block-world scenes. Having developed a good understanding of this limited world of computer vision, researchers are now trying to make computers see curved objects also. This paper presents an overview of the techniques developed for segmentation, representation, and recognition of curved objects in two-dimensional images and in three-dimensional scenes. The possible future directions of research are also discussed.     

Shape-based interpolation of multidimensional objects

A shape-based interpolation scheme for multidimensional images is presented. This scheme consists of first segmenting the given image data into a binary image, converting the binary image back into a gray image wherein the gray value of a point represents its shortest distance (positive value for points of the object and negative for those outside) from the cross-sectional boundary, and then interpolating the gray image. The set of all points with nonnegative values associated with them in the interpolated image constitutes the interpolated object. The method not only minimizes user involvement in interactive segmentation, but also leads to more accurate representation and depiction of dynamic as well as static objects. The general methodology and the implementation details of the method are presented and compared on a qualitative and quantitative basis to the existing methods. The generality of the proposed scheme is illustrated with a number of medical imaging examples.     

Fast on-line B-spline interpolation

A computationally inexpensive algorithm for signal interpolation using B-spline functions is presented. Specifically, the convolution between the B-spline coefficients and the B-spline function itself, widely acknowledged as the most costly aspect of B-spline interpolation, is reformulated such that it is directly amenable to implementation at a much lower computational cost (16.25% of the cost of direct evaluation)     

Trajectory prediction for moving objects using artificial neuralnetworks

A method to predict the trajectory of moving objects in a robotic environment in real-time is proposed and evaluated. The position, velocity, and acceleration of the object are estimated by several neural networks using the six most recent measurements of the object coordinates as inputs. The architecture of the neural nets and the training algorithm are presented and discussed. Simulation results obtained for both 2D and 3D cases are presented to illustrate the performance of the prediction algorithm. Real-time implementation of the neural networks is considered. Finally, the potential of the proposed trajectory prediction method in various applications is discussed     

Improvement on dynamic elastic interpolation technique for reconstructing 3-D objects from serial cross sections [biomedical application

An improved method for automatically reconstructing a three-dimensional object from serial cross sections is presented. The method improves the dynamic elastic contour interpolation technique. There are two major improvements: (1) in the case of branching that involves concave contours, instead of pairwise interpolation between the start contour and each goal contour, the goal image is considered globally and local constraints are imposed on the forces exerting upon the vertices; and (2) it takes the continuity of high-order derivatives into consideration and incorporates the schemes of spline theory, quadratic-variation-based surface interpolation, and finite-element-based multilevel surface interpolation to create smoother surfaces of the reconstructed object. Based on the output from the preliminary processing, two alternatives, a quadratic-variation-based surface interpolation algorithm and a finite-element-based multilevel surface interpolation algorithm, can be adopted to obtain the final surface representation     

IPRAN复杂场景的快速端到端业务配置

随着 IPRAN(IP无线接入网)的测试和应用,对于双节点跨环进行环间保护并且使用 MS-PW(多段伪线)和 DNI(双归属)保护的全二层PWE3(端到端的伪线仿真)或者 L2VPN(二层虚拟专网)转 L3VPN(三层虚拟专网)业务的复杂应用场景,采用常规配置方式过程非常复杂。文章介绍了 IPRAN在上述场景中复杂的配置步骤,提出用业务场景模板方法进行关键节点映射替换,将业务需要的隧道、PW、PW冗余和DNI保护等都纳入业务配置过程中,一次性快速完成,从而解决这种场景中端到端静态业务配置的效率问题。     

Fast interpolation algorithm using FFT

An interpolation algorithm for finite-duration real sequences using the discrete Fourier transform is presented. The proposed method is shown to result in a significant saving of computational labour over the discrete version of the time-domain classical interpolation formula. Estimation of inbetween samples for large sequences is possible within a mean square error of 0.00114 with this method. Some considerations with regard to the computation of FFTs are also discussed.     

ON THE MOVING ADAPTIVE INTERPOLATION TECHNIQUE TO IMPROVE THE VERTICAL RESOLUTION OF PICTURES IN TV

This paper deals with the method of moving adaptive interpolation technique. The interlaced scanning that structures the pictures in today's television systems is changed into progressive scanning, which helps to greatly improve the vertical resolution of pictures.     

运动物体的压缩感知成像

在使用压缩感知成像系统进行成像时,物体的运动会导致获取的物体图像分辨率下降.为了克服运动的干扰需要额外装置获取物体运动的参数,但在很多情况下无法获取物体的运动速度.针对这一问题,提出利用物体运动与散斑运动的相关性,采用散斑运动方式来抵消物体运动从而消除运动造成的分辨率下降.采用压缩感知算法利用多组不同散斑运动补偿情况下的参数获取不同的物体图像,最后利用物体运动和散斑运动的相关性判据参数,最终获得消除运动干扰的物体图像。算法求解中同时考虑了系统点扩散函数的影响,采用解卷积算法获取了消除运动和系统点扩散函数影响的物体图像。最后数字仿真结果证实了所提算法的有效性。     

光照突变补偿在视频序列运动目标检测中的应用

针对光照突变情况下视频序列运动目标检测精度低 、误检多等问题,提出一种结合光照补偿的检测算 法。算法利用色差不变量提取稳定的背景区域,并结合历史前景信息判定光照突变程度。采 用对角模型补 偿光照突变的图像序列,对全局与局部光照突变分别运用区间估计与码本聚类方法计算补偿 参数,最后利用 背景减除法实现运动目标的检测。与典型算法进行对比的实验结果表明,本文算法具备较高 的检测精度与稳定性,适用于动态场景中的运动目标检测。     

运动目标的计算机红外成像仿真

运动目标的计算机红外成像仿真有着广泛的应用价值。提出了适用于运动目标红外图像生成的模型和绘制方法,在考虑到大气传输和传感器噪声对红外成像的影响后,给出了不同类型的运动目标的红外图像。实验结果表明,该方法模拟效果真实,算法可靠。     

Segmentation and tracking of moving objects for content-based videocoding

To enable content-based functionalities in video coding, a decomposition of the scene into physical objects is required. Such objects are normally not characterised by homogeneous colour, intensity, or optical flow. Therefore, conventional techniques based on these low-level features cannot perform the desired segmentation. The authors address segmentation and tracking of moving objects and present a new video object plane (VOP) segmentation algorithm that extracts semantically meaningful objects. A morphological motion filter detects physical objects by identifying areas that are moving differently from the background. A new filter criterion is introduced that measures the deviation of the estimated local motion from the synthesised global motion. A two-dimensional binary model is derived for the object of interest and tracked throughout the sequence by a Hausdorff object tracker. To accommodate for rotations and changes in shape, the model is updated every frame by a two-stage method that accounts for rigid and non-rigid moving parts of the object. The binary model then guides the actual VOP extraction, whereby a novel boundary post-processor ensures high boundary accuracy. Experimental results demonstrate the performance of the proposed algorithm     

一种改进的自适应运动目标检测算法

针对运动多目标识别与跟踪所必需的准备环节--运动目标检测,本文提出了的一种改进的自适应运动目标检测方法,检测运动目标是否存在,并利用试验证明,该方法确实不仅能有效抑制光照变化、人影、噪声等影响,进而对运动目标是否在跟踪区域徘徊进行判断,保证了对进出目标跟踪的准确跟踪,而且运算量小,容易软件实现,实际效果较好.     

Tracking moving objects in television images

The estimation of the velocity of objects imaged by television cameras is useful in different areas of image processing.The problem is solved by means of a linear estimation algorithm and the effects of noise superimposed to the signal are analyzed. The structure of a real-time estimator is then presented. Experimental results show that a very fine accuracy is obtained. They encourage its application to image coding for redundancy reduction using movement compensation.     

3-D model-based frame interpolation for distributed video coding of static scenes.

This paper addresses the problem of side information extraction for distributed coding of videos captured by a camera moving in a 3-D static environment. Examples of targeted applications are augmented reality, remote-controlled robots operating in hazardous environments, or remote exploration by drones. It explores the benefits of the structure-from-motion paradigm for distributed coding of this type of video content. Two interpolation methods constrained by the scene geometry, based either on block matching along epipolar lines or on 3-D mesh fitting, are first developed. These techniques are based on a robust algorithm for sub-pel matching of feature points, which leads to semi-dense correspondences between key frames. However, their rate-distortion (RD) performances are limited by misalignments between the side information and the actual Wyner-Ziv (WZ) frames due to the assumption of linear motion between key frames. To cope with this problem, two feature point tracking techniques are introduced, which recover the camera parameters of the WZ frames. A first technique, in which the frames remain encoded separately, performs tracking at the decoder and leads to significant RD performance gains. A second technique further improves the RD performances by allowing a limited tracking at the encoder. As an additional benefit, statistics on tracks allow the encoder to adapt the key frame frequency to the video motion content.     

在真实的VR场景中嵌入虚拟三维对象

随着虚拟现实技术的发展,其运用涉及的领域也越来越多,涵盖了影视、游戏、旅游以及教育等.在此首先探析了虚拟现实技术的发展现状以及虚拟场景的构建方式,并研究分析如何将三维对象融入到真实虚拟场景中,最后根据虚拟场景技术的实际运用分析总结其优点,希望对大家了解虚拟场景技术有所帮助.     

A hybrid algorithm for automatic segmentation of slowly moving objects

Segmentation of moving objects in video sequences is a basic task in many applications. However, it is still challenging due to the semantic gap between the low-level visual features and the high-level human interpretation of video semantics. Compared with segmentation of fast moving objects, accurate and perceptually consistent segmentation of slowly moving objects is more difficult. In this paper, a novel hybrid algorithm is proposed for segmentation of slowly moving objects in video sequence aiming to acquire perceptually consistent results. Firstly, the temporal information of the differences among multiple frames is employed to detect initial moving regions. Then, the Gaussian mixture model (GMM) is employed and an improved expectation maximization (EM) algorithm is introduced to segment a spatial image into homogeneous regions. Finally, the results of motion detection and spatial segmentation are fused to extract final moving objects. Experiments are conducted and provide convincing results.