运动对象检测是计算机视觉应用中的一个重要问题。
Motion object detection is an important issue in the applications of computer vision.
运动对象检测是计算机视觉应用中的一个重要问题。
A new method to detect motion objects was presented, by comparing the texture diversity between the foreground image and the background image.
提出了一种提取运动对象的新的视频序列分割算法。
This paper presents a new automatic video sequence segmentation algorithm that extracts moving objects.
结合运动对象运动在时间和空间上的相关性进行二次检测。
Second, to perform the fine detection and segmentation based on the time-space relativity of the movement.
本发明披露了一种为运动对象21提供的容性传感器系统。
The present invention relates to a capacitive sensor system provided for a moving object 21.
提出了一种基于动态背景构造的视频运动对象自动分割算法。
In this paper, an automatic segmentation algorithm for moving objects in video sequences based on dynamic background construction is proposed.
为此提出了一种基于形态学算子的视频运动对象自动分割算法。
For the first step, a morphology operator-based video motion object segmentation algorithm is proposed.
提出一种视频的压缩域与像素域特征结合的运动对象分割算法。
An effective algorithm is proposed to segment moving object in compressed domain and pixel domain method combined.
将两种基于图论的算法图切割与随机游走应用于运动对象的分割。
Two algorithms, graph cut and random walk based on graph theory, were applied to motion segmentation.
为此，文章提出并实现了一种基于互帧差的视频运动对象分割方法。
This paper proposes and implements a moving object segmentation method, which based on inter-frame difference.
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；
Segmentation and tracking of video moving object is used for guiding the extraction of video object plane from the video sequence.
实验结果表明，该算法分割效率高，分割的运动对象完整性好、精度较高。
Experimental results show that the segmentation algorithm is efficient and segmented moving object is complete and accurate.
如果对象识别标记的显示准确地跟踪运动对象，则标记的可视性可能恶化。
If the display of an object identification mark accurately follows up a moving object, the visibility of the mark may deteriorate.
实验结果表明，该文提出的算法对存在局部遮挡的多运动对象分割是有效的。
The experimental results show that the algorithm is effective to multiple object segmentation with partial occlusion.
这一新的软件程序名为“纪念照模式”，通过算法区分运动对象与静止对象。
'Monument Mode' is a new software development that USES an algorithm to distinguish moving objects from fixed ones.
最后对检测出的运动对象利用最小外接矩形框特征匹配，实现对它们的跟踪。
Finally, matching the detected motion objects with the minimal outer rectangle realize the tracking.
针对这两个问题，本文引入场景上下文知识和经验知识来辅助提取运动对象。
In order to solve these problems, scene context knowledge and prior knowledge of moving object are used.
视频运动对象分割的目标是从视频帧序列中间分割出满足一定特征的语义区域。
Segmentation of video moving object is extraction of semantic area meet certain characteristics from video sequence.
它把图像序列分解成视频对象平面(VOP)，每个VOP代表一个运动对象。
It decomposes sequences into video object planes (VOPs) so that each VOP represents one moving object.
视频对象分割，旨在分割出视频序列中的运动对象并沿时间轴跟踪运动对象的演进。
Video object segmentation aims to partition an image sequence into moving objects and to track the evolution of the moving objects along the time axis.
实验结果表明，该方法可有效地从H264压缩视频中提取运动对象且分割质量较好。
Experimental results demonstrate that our approach can efficiently extract the moving objects from H264 compressed and as the segmentation quality is good.
实验结果证明，该方法能够从背景不变的图像序列中较好的提取出运动对象，具有较强的鲁棒性。
Experimental results demonstrate that this method can effectively separate the video object from the sequence with static background and has the strong robustness.
本文针对移动GIS的运动对象提出了概念描述，并提出运动对象的分析方法，以及相应的算法。
Focusing on mobile object, this paper puts forward mobile GIS concept description, the analysis method of mobile object and corresponding algorithm.
网球运动的文化底蕴及它高雅的属性和适应人们追求的这几大特征早已成为人们所关注的运动对象。
Tennis sports culture and its elegant property and seek to adapt to these people has long been a major feature of concern to people moving object.
因此，本文算法首先利用累积帧差，弥补了两帧帧差所得边界的不完整性，得到准确的运动对象的定位；
So in this method, Firstly, using accumulating frame difference, we obtain the exact moving object localization which makes up the incompletely of the edge gotten by the frame difference.
在运动物体检测后的二值图像中，经常会存在细小噪声和内部空洞，不利于运动对象后期的分析和跟踪。
Small noises and holes often remain in the binary images of moving object detection, which can affect the analysis and track of moving object.
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.
在对现有视频运动分析方法进行分析比较的基础上，提出了一种基于视频中运动对象的运动特征提取方法。
On the basis of analyzing and comparing existing methods, it presents a motion feature extraction method which is based on movement object in video.
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。
Experimental results demonstrate that this method is effective to segment and track video moving objects. More, the number of parameters updated is the least.
在后续帧中通过建立前帧感兴趣运动对象与当前帧中各运动对象的帧间向量来跟踪当前帧中感兴趣的视频对象。
As for tracking, vectors between the last interested objects in previous frame and moving objects in current frame are established to follow the present interested objects.
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