这种方法考虑了全局的运动，并且提出一种新的运动区域检测算法。
The algorithm considers the global motion and puts forward a new motion region detection algorithm.
基于闪烁参数函数空间光滑的特点，提出了一种局部运动区域检测的方法。
Based on the smoothness property of flicker, a method detecting local motion is proposed.
该算法首先利用分块高阶统计算法和基于最大类间方差的阈值算法得到目标的运动区域检测模板。
First, block higher order statistics and threshold via local maximal between-cluster variance are used to get the motion detection mask.
通过运动区域检测、噪声去除、连通单元标记、目标提取、阴影检测等处理，能获取完整的车辆目标区域。
By the process of moving area detection, yawp elimination, object detection based on connected region label, shadow elimination, the whole vehicle targets area is obtained.
其基本思想是：首先根据多帧帧差信息，基于高阶统计检测方法提取运动区域。
The steps are as follows: First, motion area is extracted based on high-order statistics detection method and motion information of multiple frames.
带加速度的运动预测则有效地减小了检测区域，提高了系统的速度。
Motion prediction taking acceleration into account could effectively reduce the detection area and it consequently increases the tracking speed.
它采用类似差分的方法从图像序列的多帧图像中检测出运动目标区域。
Motion object region is extracted from multi-frame images in image sequences by using similar difference method.
第二种方法是基于时差分模糊熵聚类的运动变化区域检测算法。
Other way is the motion-changed region detection algorithm based on fuzzy entropy clustering in time-differenced image .
为了正确检测出运动区域，提出了自适应的背景图象适应外界环境变化的跟踪过程。
To detect moving region , it advances an adaptive background image to adapt to the varying environment in the tracking process.
识别算法采用差影法与4邻域连通区域标记相结合，并对差影法进行改进，建立起一个新型的运动检测模型。
Identification algorithm mix difference image method and 4-connected boundary tracking method, besides, we improved the difference image method and built a new moving detection model finally.
另外，根据预测的运动检测区域，设计了一种新的用于全局运动估计的局部区域选取方法。
In addition, according to the area forecasted, a new method is designed to select the local areas which are used for global motion estimation.
首先，利用运动检测器将图像序列的每一帧分割成静止区域与运动区域。
Firstly, each frame in image sequence is distinguished between stationary and moving regions by using a motion detector.
该方法先在静态图像中分割出感兴趣区域，继而仅在感兴趣区域中应用变形的时间差分法来检测运动目标。
Those regions of interest are quickly segmented first and then a modified temporal differencing method is applied to detecting the moving objects.
通过变化检测，映射参数估算，运动区域和背景检测来实现运动分割。
Change detection, mapping parameter estimation, moving objects and background detection are used to implement image motion segmentation.
通过采用运动变化区域检测和边缘检测技术来生成视频对象。
The video object generated in this paper utilizes the technology of motion-changed region detection and edge detection.
同时提出一种基于动态规划的轮廓连接新算法，该算法能在运动区域中跟踪物体的运动边界，并同时检测出场景中位于非运动区域的静态物体边界。
New algorithms for contour linkage are proposed to track the object's motion edges as well as detect the disappearance of existing edges of the object in the scene.
对运动区域（视频前景），基于小波分析技术实现视频图像的人脸检测，进而引入改进的人脸模型进行高效的压缩编码；
Following, a wavelet based face detection algorithm is presented for the moving regions (foreground video objects), and an amendment for face model within MPEG-4 is introduced.
在完成了路面区域的定位后，因为光线等环境变化引起的背景变化会影响运动检测的结果，所以需要对背景进行更新。
After the localization of the region of the road, we need to update the background because of the transformations of background caused by the changes of environment such as light.
该文介绍的这一方法采用了动态目标区域检测的技术来追踪运动车辆，所谓动态目标区域检测就是指被检测区域是动态更新的，是随着被检测对象位置的变化而改变的。
The approach proposed by the writer adopts the technique of dynamic target region detection. Its core is that the region to be detected is dynamic and is changing with the target's change.
提出了一种快速的、鲁棒的人脸定位及跟踪研究方法，定义了一种新的运动能量表示方法，利用该方法可以很快地检测出图像中的运动区域。
A fast and robust approach method for making the detection, localization and tracking of a persona face in image sequences was presented. A new representation of motion energy was defined.
人体运动目标检测方面，利用纵向投影直方图确定运动目标的顶部位置，根据顶部位置来确定头肩区域。
On human body moving object detection, the top of the moving object is located by vertical projection histogram, and the head and shoulder is located according to top position.
人体运动目标检测方面，利用纵向投影直方图确定运动目标的顶部位置，根据顶部位置来确定头肩区域。
On human body moving object detection, the top of the moving object is located by vertical projection histogram, and the head and shoulder is located according to top position.
应用推荐