A novel moving object detection based on adaptive background subtraction and symmetrical differencing is presented in this paper.
本文提出了一种基于背景相减法和对称差分法来进行运动目标检测的方法。
The algorithm can process video sequence automatically with moving background, static background or the video sequence that both object and background are all static.
该算法可以自动提取动态背景、静态背景，也可以在视频序列中出现背景和对象都停止变化时实现视频对象的提取。
In this paper, the authors propose an efficient and effective method for recognizing and tracking specific moving object in a complex color background.
该文提出了针对在复杂的彩色背景下特定运动目标定位的快速有效方法。
The object detection technology and the background motion compensation technology based on single camera on the moving background were further studied in this paper.
本文对运动背景下基于单目视觉的背景运动补偿技术及运动目标检测技术做了深入研究。
Background estimation based on block is proposed to solve the problem of building background model and updating background which can enhance the robust of moving object detection.
针对静态背景下的背景差法，通过研究如何得到、以及如何及时更新背景模型，增强运动目标检测随环境变化的鲁棒性，提出了多级分块的背景估计方法。
The thesis is focused on the technique of the moving object tracking in the dynamic background, which is used in TV tracking system.
本论文研究的主要内容为电视跟踪系统中运动目标在运动背景下的跟踪技术。
This system can realize the detection of the non-rigid moving object and the estimation of the background velocity through the Level-Set method and piece-wise smooth motion field constraint.
该系统采用水平集方法，利用分段平滑运动场的约束条件，实现非刚体运动目标检测和背景的运动估算。
Secondly, detailed design of the image information processing module was given according to the requirements of moving object detection in a stationary background.
其次，根据静态背景下运动目标检测的要求，对图像信息处理模块进行了详细设计。
Firstly build a background image in the complex background with a moving object and obtain initial object contour from the current image by frame-difference.
首先利用自适应的背景提取算法从带有运动目标的复杂背景中构建背景图，并提取出运动目标轮廓。
It has studied how to carry out recognition and tracking of moving object based on simple background, and presented the block diagram of system theory for object tracking.
研究了在简单背景下实现对运动目标的识别与跟踪，给出了目标跟踪的原理图和结构框图。
A new method is proposed for fast moving objects detecting based on bitmap difference dealing with the object with complicated background and great amount of data treatment.
针对移动目标检测过程中，背景信息复杂并且信息处理量大的问题，提出了一种对检测区的位图进行差影计算，从而快速检测出移动目标的方法。
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。
In this paper, we present a moving object detection method for outdoor background according to the development of an intelligent object monitoring and tracking system based on video images.
本文结合一个基于视频图像的智能野外监控系统的开发过程，提出了一种野外背景下运动目标的检测方法。
The tracking experiments have been done, It shows that the system can track single moving object in the multiple background. The whole system has practical value.
进行了跟踪实验，试验结果说明本系统能够实时跟踪复杂背景中的单个运动目标，系统具有实际的工程应用价值。
Separating the moving object quickly and accurately from the background is a basic and key technology for further image analysis and processing.
而把运动目标从背景图像中快速、准确的分离出来是对图像进一步分析处理的关键和基础。
The work in this paper is mainly how to classification of foreground and background effectively using fusion of multiple features in the moving object detection and tracking.
本文主要工作针对运动目标检测和跟踪中的问题，研究运用多特征融合以更有效的完成前景运动目标和背景的分类。
Via the experiment, we can see the method is efficient to be used to overcome the disturb of complex background and to extract the moving object.
通过实验证明，该方法对于克服复杂背景的干扰和有效地提取运动目标具有较好的效果。
The cleanly background was attained quickly, because the moving object in frame did not affect the process of attaining.
由于排除了帧中所有运动物体的影响，因而提取出的背景干净，效果很好。
Tiny changes in a moving object can be detected by rebuilding the image background using the algorithm and calculating the ratio of pixel changes by means of the difference image algorithm.
用此算法重建背景图像以及用图像差分算法计算像素改变比例，能监测慢速、微量变化的运动物体。
A simple strategy named 3 frames difference background subtraction is adopted to detect moving object, and movement estimation and compensation are combined to improve processing speed.
采用简单的三帧差背景剪除策略检测运动目标，合并运动估计和背景补偿以加快系统反应速度。
A new background model of non-parameter kernel density estimate was presented on the basis of abundant study on algorithms of moving object detection.
在充分研究现有运动目标检测算法的基础上，提出了一种新的非参数核密度估计背景模型。
An approach of background estimation is presented using characters of random variable moments and applied in moving object detection under static background.
利用随机变量的各阶矩的性质，构造了一种基于高阶统计量的背景估计方法，并将其应用于静态背景下的运动目标检测。
Secondly, three main algorithms of motion detection under a dynamic background are researched. The project of moving object detection based on matching feature point are proposed.
然后介绍了动态背景下运动目标检测的三种算法，针对特征点匹配方法检测运动目标的有关问题，提出了动态背景下运动目标检测方案。
The algorithm can quickly and precisely mark the moving object and its trail by functions of image enhancement, morphological operation, and interframe background subtraction.
该算法运用图像增强、形态学操作、图像差分法，能快速准确标注出移动的物体及其移动轨迹。
This paper proposes a novel method for moving object detection from a video in medical gait analysis which contains not only stationary background objects but also moving background objects.
针对医学步态分析中的复杂场景下运动目标检测问题，提出了基于贝叶斯决策规则的方法。
Firstly, moving pixels was extracted by using difference image algorithm, then motion object and moving background were distinguished by the change frequency of pixel state.
针对复杂背景下弱点目标的检测问题，提出一种基于形态学处理和帧间差分相结合的红外点目标检测算法。
Qualitative and quantitative experiments demonstrate that the proposed codebook model can effectively detect moving object under complex dynamic background.
使用覆盖率—准确率曲线评价的实验结果证明，所提出的码书模型可以有效检测复杂背景下的运动物体。
Qualitative and quantitative experiments demonstrate that the proposed codebook model can effectively detect moving object under complex dynamic background.
使用覆盖率—准确率曲线评价的实验结果证明，所提出的码书模型可以有效检测复杂背景下的运动物体。
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