Using motion-detection algorithms, the BriefCam software separates the background (static or non-moving objects) from the moving objects, tracking and analysing any motion within the frame.
利用运动检测算法，BriefCam软件能把背景（静态或非运动的物体）同运动的物体分开，在帧内记录并分析任何一个动作。
Based on level set method and background subtraction, this paper proposed an approach to (realize) robust detection and segmentation of multiple motion objects.
给出了一种对光照变化等实际环境中干扰不敏感的基于水平集和背景减的运动目标检测与分割方法。
Change detection, mapping parameter estimation, moving objects and background detection are used to implement image motion segmentation.
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。
The detection and tracking algorithm of video motion objects is one of hotspots in the field of computer vision. It's also the key intelligent technology of video surveillance system.
视频运动目标检测与跟踪算法是计算机视觉领域的一个核心课题，也是智能视频监控系统的关键底层技术。
According to the study of main motion detection and moving objects extraction methods, a new method combining frame-difference and background-difference was put forward.
在对视频监控中运动目标检测识别常用算法进行研究的基础上，本文提出了一种新的基于两帧差分法和背景差分法相结合的运动目标检测方法。
They have good effects on motion detection of one or multi-moving objects.
对单个或多个运动物体检测效果都良好。
In the detection of motion objects, a method based on movement feature of target (catenary) is proposed. It combines temporal differential method and template matching in image sequence data.
在检测运动物体方面，根据检测对象(接触线)的运动特征提出了一种对图像序列数据采用时态差分法与模板匹配相结合的检测方法。
In the detection of motion objects, a method based on movement feature of target (catenary) is proposed. It combines temporal differential method and template matching in image sequence data.
在检测运动物体方面，根据检测对象(接触线)的运动特征提出了一种对图像序列数据采用时态差分法与模板匹配相结合的检测方法。
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