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Synopsis
智能视频监控就是利用计算机视觉和数字图像处理的方法，在不需要人为干预的情况下，对摄像机拍摄的图像序列进行自动分析，实现对动态场景中运动目标的检测、跟踪和识别，并在此基础上分析和判断目标的行为，给出对运动目标行为和动作的描述，自动发现一些可疑情况，实现系统对场景中的异常进行鉴别并自动报警，从而指导和规划人们的行动。 目前，智能视频监控方面的研究和应用都面临着很多难题，国内外的许多学者投身于该领域的研究，取得了大量的成果。本书在这些成果的基础上，对智能视频监控系统中的关键步骤——运动目标检测与跟踪进行了研究。主要的工作概括如下： （1）针对运动目标检测和跟踪算法中的应用，改进了LBP（Local Binary Pattern）算子，使后续使用LBP纹理的运动目标检测与跟踪算法在特征匹配时的速度得到提高； （2）提出了一种结合改进的LBP纹理和色度信息的运动目标检测算法； （3）提出了一种结合光流法与三帧差分法的运动目标检测算法； （4）提出了联合LBP纹理和色度信息的Camshift跟踪算法； （5）提出了基于Kalman滤波器和Blob匹配法的目标跟踪算法。
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About the Author
袁国武，1978年生，男，博士，副教授，工作于云南大学。主要研究方向为数字图像处理、模式识别、天文图像处理。主持、完成了各类基金10余项，在国内外学术期刊及会议发表论文40余篇，其中SCI、EI检索20余篇次，申请国家发明专利2项，计算机软件著作权10余项，2011年4月获得云南省自然科学奖二等奖。
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