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opencv上目标跟踪和行人跟踪非常需要的视频序列源，来源于卡内基梅隆大学。大家共同学习-opencv target tracking and pedestrians on the track a much needed source of video sequences, from Carnegie Mellon University. We learn together
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meanshiftkamen实现的运动目标跟踪,可用于行人与车辆！-Sports meanshiftkamen implementation of target tracking, can be used for pedestrians and vehicles!
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这个在IEEE上下载的关于基于视频图像的车辆行人检测跟踪系统，对毕业设计有帮助-IEEE downloaded this on video images based on detection of vehicles and pedestrians tracking system designed to help graduate
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提出了一种保护隐私的人群大小的估计，不依靠跟踪和计数的方法。-present a privacy-preserving system for estimating the size of homogeneous crowds, composed of pedestrians that travel in different directions, without using explicit object
segmentation or tracking.
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This paper presents a method that combines
colour and motion information to track pedestrians in video sequences captured by a fixed camera. Pedestrians are firstly
detected using the human detector proposed by Dalal and Triggs which involves com
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利用Opencv对运动目标（包括汽车，行人）的AVI视频进行检测并跟踪。效果十分显著。 - detect and tracking the moving targets (including cars, pedestrians) AVI video detection and tracking. Effect is very significant.
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摄像头固定情况下的运动行人跟踪进行研究，Mean Shift算法，与目标区域灰度直方图结合，进行运动目标的检测跟踪-tracking study of the movement of pedestrians in case of a fixed camera introduces a better application of Mean Shift algorithm
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分为行人检测，特征提取，行人跟踪三步，其中最主要的代码也是这个代码的中心是行人跟踪这一部分，我采用的是kalman滤波器进行行人下一帧位置的预测，可以很好的提高行人跟踪的鲁棒性，跟踪结果比较准确。-Into pedestrian detection, feature extraction, pedestrian tracking steps, which is the center of the main code of the code is pedestrian tracking this
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Most of my current work focuses on tracking pedestrians mobile platforms. The idea is to equip robots or cars with vision systems that can oversee the traffic situation around the car and that can give an early warning for dangerous situations. The s
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基于C++开发平台，通过感官哈希算法对行人进行跟踪，有较好的跟踪效果-C++ based development platform, through the senses hash algorithm to track pedestrians, better tracking effect
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In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance
cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is dev
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跟踪行人的matlab例子，仅供参考，亲测可以实现(Matlab example for tracking pedestrians for reference only)
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