实验结果表明，本文提出的算法能精确、鲁棒地分割出视频对象。
Experimental results show that the algorithm can accurately and robustly segment the video object.
首先进行视频对象分割，求出运动目标的形心。
Firstly, video objects were segmented and their centroids were calculated.
由于输入视频序列的每一帧被分割成任意形状的视频对象平面(VOP)，这样每个VOP描述了一个语义意义的对象或所感兴趣的视频内容。
Each frame of the input sequence is segmented into arbitrarily shaped image regions (VOP's) such that each VOP describes one semantically meaningful object or video content of interest.
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 introduces video segmentation of temporal segmentation and spatial segmentation, presents a video object segmentation algorithm based on multi-frames difference.
视频对象分割在基于内容的视频编码和视频检索中均有重要的应用。
Video object segmentation has important application in content-based video encoding and video retrieval.
视频对象分割技术同时也是基于内容的视频编码、视频内容操作和交互式多媒体等应用的重要工具。
Video object segmentation techniques are also important tools for content-based video coding and manipulation, and interactive multimedia application.
视频对象分割技术同时也是基于内容的视频编码、视频内容的操纵和交互式多媒体等应用的重要工具。
Video object segmentation techniques are also important tools for content-based video coding and manipulation, and interactive multimedia applications.
实验结果证明本算法能比较准确地分割出运动视频对象。
The experimental results show that the proposed algorithm can precisely segment the motion video object.
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.
视频对象分割算法的性能好坏将直接影响MPEG-4编码产品的质量。
The performance of video object segmentation algorithm has the direct effect on quality of MPEG-4 products.
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.
针对视频对象的分割问题，提出了一种新的视频对象提取与跟踪方法。
For the problem of video object segmentation, a new approach was presented to video object extraction and tracking.
从视频序列中分割出视频对象是实现基于内容压缩编码方法的关键。
Video objects segmentation from video sequence is the key of implementing content-based compression coding method.
实验结果表明，该算法可有效地提取视频对象和分割视频对象平面。
Experiments show that the described algorithm can extract video objects, leading to the segmentation of VOPs.
将视频图像的方向信息测度、颜色和运动信息相结合的视频对象分割算法可以解决这一问题。
A new approach to extract video objects from video sequence by combining of orientation information measure, color and motion information is presented.
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.
视频对象分割是当前图像和视频处理的热点和难点之一。
Video object segmentation is the one of the focus in the field of image and video processing.
在基于对象的视频编码中，视频对象的分割是重要的任务。
Video object segmentation is an important task in object based video coding.
视频序列分割是实现视频对象提取、处理和识别的基础，也是基于内容的视频压缩和检索的前提。
The segmentation of video is the basis of the video object extraction, processing and recognition. It is also the premise of the content-based video compression and retrieving.
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.
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.
视频对象分割技术作为多媒体技术应用的一个主要方面，在视频编码、检索、多媒体交互和计算机视觉中有着极为重要的应用。
The video segmentation plays an important role in the application of multimedia, and has a widely future in video coding, video browsing, multi-media interacting and computer vision.
按照MPEG - 4的校验模型，视频序列必须先分割成具有语义意义的视频对象，然后对其运动、形状和纹理分别进行编码。
According to the MPEG-4 verification model, video sequence must be segmented into semantic video objects. Their motion, shape and texture information are coded respectively.
该文讨论面向对象编码的视频分割算法。
This paper deals with automatic object segmentation method for object-oriented video encoding.
视频运动对象的自动分割是实现新一代对象基视频编码标准MPEG - 4的重要技术，本文提出了一种基于帧内图像分区的运动对象自动分割算法。
Automatic segmentation of moving objects in video sequences is a significant technology for implementing emerging object-based video coding standard MPEG-4.
提出一种基于原型的可变形模板进行图像分割的算法，从而可以将感兴趣的视频对象从静止的复杂背景中提取出来。
This paper proposes an image segmentation algorithm using deformable template to segment an interesting visual object from the stationary complex background.
通过对体育比赛视频中的场地信息和运动信息的分析，提出了一种有效分割场地和运动员等对象的算法，并对此算法性能进行了讨论。
It proposes an efficient method to segment objects such as athletes and field in sport video by analyzing the information of visual and motion features.
本文主要研究半自动的视频对象分割与跟踪。
This thesis is focused on semiautomatic video object segmentation and tracking.
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.
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.
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