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机构地区:[1]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001
出 处:《电子与信息学报》2010年第2期388-393,共6页Journal of Electronics & Information Technology
摘 要:为解决复杂环境下的诸如枝叶摇摆、摄像机抖动等波动式干扰对运动目标检测的影响问题,该文提出基于视频窗口切分与分类的序列图像运动目标检测算法。首先将序列图像切分为r×c大小的视频窗口,然后提取窗口内区域图像累积帧间差矩阵的简单统计特征,针对每一帧序列图像,将视频窗口进行分类,把它们划分为运动目标窗口和非运动目标窗口(包括静止背景窗口和波动式干扰窗口),最后将运动目标窗口合并为运动目标。该方法的优点是无需已知背景模型和运动目标大小、形状等任何先验信息。实验表明该算法能在摄像机抖动以及枝叶干扰等复杂环境下快速有效的检测出运动目标。In order to remove the fluctuant interference such as swaying branches, stochastic shaking of camera in complex environments when moving targets are detected in video sequences, A new algorithm of moving targets detection based on video windows partition and classification is proposed. First of all, the image sequences are divided into numbers of video windows at size r × c. Then the simple statistical feature is extracted from the matrix of accumulated frame differences in the window. According to the feature, the video windows is divided into two categories in each frame, moving object windows and non-moving object windows including static background windows and fluctuant interference windows. Finally all moving object windows are merged into the moving targets. The advantage of this method is that no knowledge about the background model and object size or shape is necessary. The results show that the algorithm can rapidly and validly detect the moving objects in complex environments with the fluctuant interference such as swaying branches and stochastic shaking of camera.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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