We discuss them all in this paper . some common approaches in the field of detecting and tracking moving targets including the approach based on character , the approach based on optic flow , the approach based on frame subtraction and the approach based on background modeling are also introduced and compared with each other 本文首先概要介绍了目前运动目标检测与跟踪的一些常用方法包括基于特征的方法、基于光流场的方法、基于帧间差分的方法和基于背景建模的方法，并对各种方法进行了比较，指出其优缺点及适用范围。
We have introduced and discussed 3d object motion modal , wavelet transform on graphic , optical flow field , and etc . in chapter 1 , we first introduce the background of this thesis and the future direction of multi - media development in order to demonstrate the importance of vo abstraction 对三维运动模型、图像的小波变换和光流场的分析等，都作了较为深入的研究和探讨。第一章首先介绍了本论文的课题背景及目前多媒体发展的趋势，说明在图像序列中提取视频对象的必要性。
In this dissertation , a new method of optical flow estimation in a color image sequence , based on the hue and saturation information , is put forward from the models of illuminated objects . instead of the straightforward method of using the color components r , g and b as separate images of the same scene , the presented method exploits hue and saturation as color invariance under motion 本文从物体光照模型的角度出发，依据物体色彩和饱和度的量在运动过程中不变的特性，把色彩和饱和度作为色彩特征不变量，提出了基于色彩和饱和度的彩色时变图像光流场计算方法，该方法不仅可以避免rgb颜色模型带来的线性相关问题，而且更符合生物视觉原理。
A theoretical proof is given that optical flow can be replaced approximately by using the displacement field . the presented method not only decreases the calculating time in the following reconstructing 3d structure and motion but also solves the problems of tracking and matching image features in the both ways of visual motion analysis 把角点的位移场近似作为图像序列的光流场，一方面可以大大减少后续重建三维运动和结构任务的计算量，另一方面解决了两类处理方法中难以解决的跟踪和匹配问题。
4 . an object detection method with em ( expectation maximum ) algorithm of dynamic layer representations is researched and improved . previous algorithm contains optical flow computation , affined transformation , and clustering algorithm , and it is not convenient for detecting object quickly 4 .分析并改进了基于em ( expectationmaximum )算法的运动目标分层检测算法,早期算法由于涉及光流场求解、仿射变换、聚类合并等复杂运算,计算量大,不适合图像序列的快速处理。
The new algorithm starts from an initial estimate which is based on the hough transform , and a rectangular window is centered using the current line approximation , and a new line estimation is generated by making a total least squares fit through the pixels contained within the window . this is repeated until convergence is reached . lastly , we have suggested a new technique which may recover the motion and structure parameters of a moving object by using of 21 optical flow lines based on the optical flow fields of the feature line this thesis is the project supported by aeronautical foundation science ( no . 99f53065 ) and research center of measuring and testing technologies , and control engineering in nanchang institute of aeronautical technology ( no . 2001 - 15 ) 算法的思路是：首先，在小区域内运用霍夫变换确定直线的初始值；其次，以直线的初始值所对应的直线为中心线，建立一个矩形框；最后，利用矩形框内所包含的边缘点数据不断地迭代直至收敛，从而达到进一步修正直线的坐标参数；本文基于特征直线的光流场，即线流场，建立了一种利用21条光流线确定空间三维物体旋转运动参数、平移运动参数以及对应的空间直线坐标的线性算法。
