Temporal segmentation results are recognized by HMM finally.
最后，采用隐马尔可夫模型（HMM）对分割结果进行识别。
The proposed algorithm comprises of spatial and temporal segmentation modules.
该算法由空域分割和时域分割组成。
Temporal segmentation is processed by the absolute displaced frame difference instead of changing detecting mask.
以绝对位移帧差作为时域分割的标准；
For video temporal segmentation, a so-called "robustness criterion" is proposed to evaluate shot boundary detection algorithms.
论文为视频切变检测算法提出了“鲁棒性”评价准则，指出好的算法应该有较强的推广能力。
Temporal segmentation was based on change detection, whose key factor was the selection of appropriate threshold by histogram analysis.
时间分割采用变化检测，其关键的阈值选取通过直方图分析得到。
In this paper, an unsupervised online temporal segmentation algorithm is presented, and then the segmentation result is recognized by HMM.
提出了一种无监督的行为序列分割算法，并对分割结果进行识别。
Temporal segmentation was based on change detection. Its key was the selection of appropriate threshold, which was obtained by histogram analysis.
时间分割采用变化检测，其关键的阈值选取通过直方图分析得到。
One important piece of information that is lost during temporal segmentation is the recognition and tracking of objects beyond shots in overlapping intervals;
一个重要的信息，期间损失的时间分割是识别和追踪的对象超出杆重叠的时间间隔；
This paper introduces video segmentation of temporal segmentation and spatial segmentation, presents a video object segmentation algorithm based on multi-frames difference.
文章介绍了基于内容的时域及空域视频分割技术，提出了一种基于多帧差异的视频对象分割算法。
This paper represents a simple moving foreground segmentation method in video sequences only using their temporal information.
针对视频序列，仅利用其时域信息，提出了一种简单有效的运动前景分割算法。
To overcome the defects of data representation algorithms in temporal data mining, segmentation algorithm of key-point-based error checking is proposed.
针对时序数据挖掘中常见数据表示算法的缺陷，提出了基于关键点的误差检验分段算法。
To solve the problem in segmentation and tracking the moving object in video sequence, a novel moving object segmentation and tracking approach is proposed based on spatial-temporal dispersions.
针对视频图像中单个运动对象的分割和跟踪问题，提出了一种基于时空离散度的视频对象分割跟踪算法。
To solve the problem in segmentation and tracking the moving object in video sequence, a novel moving object segmentation and tracking approach is proposed based on spatial-temporal dispersions.
针对视频图像中单个运动对象的分割和跟踪问题，提出了一种基于时空离散度的视频对象分割跟踪算法。
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