随着MPEG-4压缩标准的制定，分割及跟踪视频运动对象的研究显得极其重要。在MPEG-4视频编码标准中，为了实现基于视频内容的交互功能，其视频序列的每一帧由视频对象面（VOP）来表示。为了生成视频对象面，需要对视频序列中的运动对象进行有效的分割；并跟踪运动对象随时间的变化，为此提出并实现了一种用于分割及跟踪视频运动对象的时空联合方法。该方法首先采用连续帧间差的4次统计量假设检验，确定运动对象的位置，自动地分离出运动区域与背景区域；在运动区域内，采用数学形态学的分水线算法来精确地提取运动对象的轮廓；最后，将提取到的运动对象作为模板，对后续的视频序列，用Hausdorff距离度量，来跟踪并提取后续帧中运动对象。实验结果表明，该方法能有效地分割和跟踪视频运动对象，且能有效减少计算复杂度，其调整参数也较少。

With emerging of new video coding standard MPEG 4, segmentation and tracking of video moving object is a key research topic in the field of interactive multimedia. In order to support content based functions in the visual standard of MPEG 4, each frame of video sequences should be represented in terms of video object planes (VOP's). Segmentation and tracking of video moving object is used for guiding the extraction of video object plane from the video sequence. This paper introduces spatio temporal information to automatically segment and track video moving objects. Firstly, a fourth orders statistic hypothesis testing in inter frame difference is used to automatically separate the moving areas from the background in a general video sequence. Secondly, Change areas are extracted as markers of the corresponding moving object. Using the marker, watershed algorithm can locate the precise boundary of moving object. Lastly, using segment moving object as the initial model, moving object can be tracked by Hausdorff distance on a sequence of video, and the model is updated every frame to accommodate for changes in shape. Experimental results demonstrate that this method is effective to segment and track video moving objects. More, the number of parameters updated is the least.