Firstly, video objects were segmented and their centroids were calculated.
首先进行视频对象分割，求出运动目标的形心。
A key technique in MPEG 4 is extracting video objects from video sequences.
从视频序列中提取视频目标是MPEG -4中的关键技术之一。
This paper brings out a video content hierarchical description model based on video objects.
本文提出了一种基于视频对象的视频内容分级描述模型。
Experiments show that the described algorithm can extract video objects, leading to the segmentation of VOPs.
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。
Video sequences are divided into shots first, in which video objects segmentation and tracking are implemented.
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。
This paper proposes a new rate control algorithm which can achieve a constant bit rate when coding asynchronous video objects.
针对异步视频对象编码，提出了一种速率控制算法，以达到恒定目标比特率。
And recently, detection and recognition of video objects is one of the most important research areas in video semantic contents analysis.
作为视频语义内容的最基本表现形式，视频对象的检测和识别在近年来一直是这一领域的研究热点。
A statistical background model is first setup, then the hypothesis testing is applied to the following frames to segment the video objects.
该方法首先建立背景统计模型，然后对后续帧进行假设检验，从而分割出视频对象。
Video content is described by characteristics extracted on four-level framework including shots, video objects, video object planes and video object regions.
本文提出了一种基于视频对象的视频内容分级描述模型。
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.
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。
Video objects segmentation from video sequence is the key of implementing content-based compression coding method.
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.
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。
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