To realize video object segment, we proposed one algorithm base on Bayes decision-making theory with least risk and video sequence edge information.
为了实现较完整的视频对象分割，提出了一种基于视频图像边缘信息和最小错误率的贝叶斯决策理论的视频对象分割算法。
Video object segmentation exists two difficult problems: how to segment object in real-time and extract multiple objects while the occlusion is emerged.
视频对象的分割目前存在两个难题，一是如何提高分割的实时性，二是对存在互遮挡的多个对象如何进行有效分割。
In this video segment we investigate some fundamental techniques for turning the stand-in object into a subdivision surface.
在这段视频中，我们研究了一些基本的技术将在对象的立场，细分曲面。
Experimental results show that the algorithm can accurately and robustly segment the video object.
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。
The techniques of digital image mosaics from video sequence consist of image global fast registration algorithm, motion object segment algorithm, and seamless blending algorithm.
基于视频序列的数字图像拼接技术主要包括全局快速配准算法、运动目标分割算法和无缝融合算法。
An automatic and accurate moving object extraction algorithm is proposed to segment head-shoulder video sequence.
针对头肩视频序列，本文提出了一种头肩视频对象的自动精确提取算法。
So, it is necessary to study the segment and the tracking of moving object in video image.
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.
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。
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