视频序列首先被分成一个个的镜头，在每个镜头内对视频对象进行分割和跟踪。
Video sequences are divided into shots first, in which video objects segmentation and tracking are implemented.
实验表明，这种算法在长达数百帧的图像序列中，始终能准确地分割出运动目标，并稳定跟踪目标的运动。
The experiments confirm that this algorithm can segment the moving targets accurately, and track them robustly among the image sequence of hundreds of frames.
实验结果表明：该算法能够较好地从视频序列中分割运动前景和背景，比较适合于在基于内容的视频编码标准MPEG - 4中使用。
Experiment results show that the algorithm can preferably segment moving foreground and background in video sequence and it fits for MPEG-4coding standard, which is content-based.
在视频序列的人体运动分析中，实时分割出运动的人体，是研究的起始关键步骤。
In the field of the analysis of human motion in the video sequence, segmenting the motion human body in real-time is the first key step.
因此，有必要研究细胞神经网络在视频序列图像中目标分割和追踪的应用及其相关算法。
So, it is necessary to study the segment and the tracking of moving object in video image.
在目标特征提取识别算法的基础上，还提出了阈值预测分割算法，并应用在序列图像的跟踪中，取得了较好效果。
Base on the recognition arithmetic, a segmentation method by forecasting threshold is proposed. Using this segmentation method in image tracking, satisfying effect is gotten.
在目标特征提取识别算法的基础上，还提出了阈值预测分割算法，并应用在序列图像的跟踪中，取得了较好效果。
Base on the recognition arithmetic, a segmentation method by forecasting threshold is proposed. Using this segmentation method in image tracking, satisfying effect is gotten.
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