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A multi-hypothesis approach for salient object tracking in visual surveillance
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1. 静态背景下的背景预测法目标检测2. 静态背景下帧间差分法目标检测
3. Mean Shift目标跟踪方法4. 重心多目标跟踪方法
,1. Static background prediction in the context of target detection method 2. Static background frame difference method for target detection 3. Mean Shift Object Tracking Method 4.
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运动跟踪代码,多功能运动跟踪,适合多物体跟踪,处理部分遮挡。-multi object motion tracking
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采用多假设检验法实现多目标跟踪,建立了多目标跟踪/视频监控平台,结合卡尔曼滤波预测目标轨迹。用户可以自己修改相关代码。-This code complete multiple object tracking/multiple target tracking/multi target tracking/multi object tracking using multiple hypothesis test/multi hypothesis test, builds up a visual surv
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视频演示算法包括:
1. 静态背景下的背景预测法目标检测
2. 静态背景下帧间差分法目标检测
3. Mean Shift目标跟踪方法
4. 重心多目标跟踪方法
该框架支持的视频只限于RGB非压缩Windows AVI格式,可以通过“文件”菜单下打开视频来打开视频文件。-Algorithm for video presentation include: 1. Static background background prediction target detection 2.
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Video object matching across multiple independent views using local descr iptors and adaptive learning文章描述了多摄像机系统下的目标检测与跟踪,和自学习方法。很有参考价值。-Video object matching across multiple independent views using local descr iptors and adaptive learning article d
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Using colour features for video-based tracking of people in a multi-camera
environment.-Using colour features for video-based tracking of people in a multi-camera
environment.
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场景中多目标的物体检测和跟踪技术研究,包括两篇硕士论文有一定学习意义-Multi-object scene object detection and tracking technology research, including two master' s thesis to study the meaning of a certain
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使用OPENCV进行运动目标跟踪,在Visual C++ 2005 环境中使用新算法实现多运动目标的跟踪和检测。-this is a object motion tracking system with Visual c++ 2005 and opencv。it can process successly check and track multi-objects。
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摘要:在交通场景下进行多目标跟踪时,如何正确检测出车辆间的相互遮挡是影响车辆跟踪结果的关键。针对问题,运用投
影理论分析交通场景的三维几何投影特征.用长方体投影轮廓模型对车辆进行建模,重构其乏维投影轮廓,以进行遮挡的检
测和分离。与以往的方法相比,它在估计出的车辆外形轮廓基础t-进行遮挡检测,不需要匹配操作,计算量较小,并能解决
基于匹配的方法无法对付的初始遮挡问题。用实验验证了该算法的有效性。-In multi—object tracking of traf氍c scene。how
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"REAL TIME MULTI OBJECT TRACKING WITH FEW PARTICLES"
This is a paper about tracking by particle filter.
This is very useful.
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A paper on Multi-Strategy Object Tracking in Complex Situation for Video Surveillance
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针对在复杂背景中检测出多批特定运动目标并实施分配批号实行标记跟踪,本文利用OpenCV的运动物体跟踪的数据结构、函数以及基本框架,建立了一个由人机交互界面模块;运动物体的前景检测模块;运动物体的团块特征检测模块;运动物体的团块跟踪模块轨迹生成模块;轨迹后处理模块组成的视频图像运动目标分析系统。-Aim at detecting,tracking and marking multipule specific targets in complex
background.We use the ba
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视频演示算法包括,1. 静态背景下的背景预测法目标检测。 静态背景下帧间差分法目标检测Mean Shift目标跟踪方法 重心多目标跟踪方法。该框架支持的视频只限于RGB非压缩Windows AVI格式,可以通过“文件”菜单下打开视频来打开视频文件。-Video presentation algorithms, including, 1. Static background background prediction target detection. Static background fram
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A MULTI-HYPOTHESIS APPROACH FOR SALIENT OBJECT TRACKING IN VISUAL
SURVEILLANCE
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基于卡尔曼滤波的多运动目标跟踪算法研究,主要用于预测目标位置-Kalman filter-based multi-object tracking algorithm is mainly used to predict the target location
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多目标跟踪的文章,the maximum a posteriori (MAP),pdf格式-Multi-Object Trajectory Tracking,the maximum a posteriori (MAP)
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本程序在Camshift原始的跟踪算法的基础上进行了改进,能够实现对多目标的跟踪,并且实现了自动初始化-The improved Camshift original tracking algorithm based on this program, able to multi-target tracking, and automatically initialized
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使用MATLAB2012中自带的目标跟踪工具实现的目标跟踪-Use MATLAB2012 comes with tracking tools to achieve the target tracking
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In this article we present a unified approach for
multi-robot cooperative simultaneous localization and object
tracking based on particle filters. Our approach is scalable with
respect to the number of robots in the team. We introduce a
method th
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