Description: 基于视频的智能交通监控系统技术研究 [学位论文]针对基于pc的监控系统的缺陷，论文以提高性能的DSPs作为系统核心处理器，可以有效的克服基于PC的监控系统的不足，提高系统的稳定性和实时性。-Video-based intelligent traffic monitoring system technology research [dissertation] pc based surveillance system deficiencies, papers in order to enhance the performance of DSPs as the core of the system processor, can effectively overcome the PC-based monitoring system deficiencies, improve system stability and real-time. Platform: |
Size: 6398976 |
Author:舞者 |
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Description: 基于OPENCV的车辆检测，采用画出虚拟线圈的方法实现车辆的检测，定位，触发-Intelligent transport system(ITS)is currently being studied and the subject of
widespread concern in the area of the world transport．These years，the great
economic benefit has been gained through ITS，At the same time，it plays all
important role in road design，traffic surveillance and highway charge．Video Vehicle
Detection Technology discussed in this paper plays an important part in the ITS．
Compared with traditional vehicle detection method with piezoelectricity sensor,
Video Vehicle Detection Technology not only has lots of advantages，i．e．，easy
installation and maintenance，wide monitoring areas，and also through image analysis
and processing it Call obtain much useful traffic information，SO it has been widely
used in ITS Platform: |
Size: 4553728 |
Author:徐卫东 |
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Description: 随着智能监控技术的快速发展, 基于数字视频的智能视频监控系统代替原来的人力监控在越来越多的公共场所获得了应用。然而, 在实际的户外监控环境下, 由于光线变化以及初始背景样本的多样性, 难以建立良好的背景样本。针对上述问题, 提出了一种自适应的背景建模方法。其中自适应指两个方面: 第一 背景的自动更新 第二, 不需要使用背景帧样本作为模型训练的输人。在此基础上, 建立了针对户外交通环境的智能车辆监控系统。实验结果表明, 上述方法在动态场景的车辆检测中取得了较好的效果。-With the rapid development of intelligent surveillance technology based intelligent video digital video surveillance system to replace the original human surveillance in public places in a growing number of applications received. However, in actual outdoor monitoring environment, due to the light changes and the diversity of the initial background samples, it is difficult to establish a good background samples. In response to these problems, proposed an adaptive background modeling method. Adaptive which refers to two aspects: first, the background is automatically updated Second, do not need to use a background as a model for the training sample frame input. On this basis, the establishment of intelligent vehicle monitoring system for outdoor traffic environment. Experimental results show that the proposed method has achieved good results in the detection of vehicle dynamic scenes. Platform: |
Size: 423936 |
Author: |
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