This thesis is focused on semiautomatic video object segmentation and tracking.
本文主要研究半自动的视频对象分割与跟踪。
Object-based video coding mostly includes video object segmentation and video object coding.
基于对象的视频编码主要包括视频对象的分割和视频对象的编码两部分。
Video object segmentation is the one of the focus in the field of image and video processing.
视频对象分割是当前图像和视频处理的热点和难点之一。
This paper deals with automatic object segmentation method for object-oriented video encoding.
该文讨论面向对象编码的视频分割算法。
An effective infrared object segmentation method based on recursive threshold analysis is proposed.
提出了一种有效的基于递归门限分析的红外目标分割方法。
For the first step, a morphology operator-based video motion object segmentation algorithm 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。
The performance of video object segmentation algorithm has the direct effect on quality of MPEG-4 products.
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。
Video object segmentation and stereo correspondence is a key technology in object-based stereo video coding.
视频目标分割与立体匹配是目标基立体视频编码中的核心技术。
This paper proposes and implements a moving object segmentation method, which based on inter-frame difference.
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。
Therefore, the study on the theories and related technologies of image object segmentation is quite meaningful.
因此，对图像对象分割理论及其相关技术进行研究具有十分重要的意义。
For the problem of video object segmentation, a new approach was presented to video object extraction and tracking.
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。
The experimental results show that the algorithm is effective to multiple object segmentation with partial occlusion.
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。
This paper presents an new method of thresholding for moving object segmentation in adaptive background update application.
文中提出了一种新的阈值化方法用来在自适应背景的应用中把运动物体从景物中分割出来。
Video object segmentation can be divided into automatic segmentation and semiautomatic segmentation according to the user-assisted degree.
按照人工参与程度的不同，视频对象分割可分为自动分割和半自动分割。
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 applications.
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。
Objective Based on a computerized color object segmentation technology, a novel ultrasonogram color flow pels quantitative analysis method is proposed.
目的提出一种新的基于计算机彩色目标分割技术的声像图彩色血流像素定量技术。
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，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 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。
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。
For pathological information management system, which is based on content retrieving, technology of object segmentation is always an important part of parametric measurement.
基于内容检索的病理信息管理系统中，目标分割技术始终是特征参数测量的一个重要环节。
The test results show that the object segmentation method based on recursive threshold analysis is effective. Its segmentation performance is better than the traditional methods.
试验结果证明，基于递归门限分析的方法是一种行之有效的目标分割方法，分割性能优于传统方法。
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。
Most of the current moving object segmentation algorithms in compressed domain were focused on the MPEGx video standards which were complexity intensive due to the use of complex mathematical models.
目前大部分压缩域视频对象的分割方法主要面向MPEG系列视频标准，且算法建模复杂。
Image segmentation is the process of detecting objects or interesting areas from input image, and it is an important step in object detection and recognition.
图像分割是从输入图像中提取目标或感兴趣区域的过程，是目标检测和识别过程中的重要步骤。
On the one hand, image segmentation is the basis of object expression, and has a great influence on feature measure.
一方面，图象分割是目标表达的基础，对特征测量有重要影响。
It combined the technology of image smooth, region segmentation and threshold segmentation and picked up the object auto. It has high speed and high veracity in program.
该方法将图像平滑、区域分割、阈值分割等多种图像处理技术有机的结合，对采集的图片成功的实现目标汽车提取，并且具有计算速度快、准确性高的特点。
The detection and segmentation of Object-of-Interest (OOI extraction) are always among the key issue of several fields, such as computer vision, image understanding and pattern recognition etc.
感兴趣的物体检测和分割(统称为感兴趣物体的提取)一直是计算机视觉、图像理解和模式识别等研究领域的重要关注点之一。
Proposes an algorithm to determine the true motion vectors of the feature regions for object based video coding and segmentation applications.
针对物体基视频编码与分割应用，提出了求取特征区域真实运动矢量的一种算法。
Proposes an algorithm to determine the true motion vectors of the feature regions for object based video coding and segmentation applications.
针对物体基视频编码与分割应用，提出了求取特征区域真实运动矢量的一种算法。
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