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Real-time Moving Object Detection and Tracking Algorithm Based on Background Subtraction

机译:基于背景减法的运动目标实时检测与跟踪算法

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Moving target detection and tracking algorithm as the core issue of computer vision and human-computer interaction is the first step of intelligent video surveillance system. Through comparing temporal difference method and background subtraction, a real-time moving object detection and tracking algorithm based on background subtraction under static background is proposed, in order to quickly and accurately detect and identify the moving object in the intelligent monitoring system. In this algorithm, firstly, we use background acquisition method to receive the background image, then use the current frame image and the received background image to perform background subtraction in order to extract foreground object information and receive the difference image; secondly, we use threshold segmentation and morphology image processing to process the difference image in order to eliminate noises and receive the clear binary moving object image; finally, we use the centroid tracking method to track and mark the moving object. Experimental results show that the algorithm can effectively and quickly detect and track moving object from video sequence under static background. This algorithm is easily realized and has good real-time and robust, which is automated and self triggered for background updating. The algorithm can be used in driver assistance systems, motion capture, virtual reality and other fields.
机译:移动目标检测与跟踪算法是计算机视觉和人机交互的核心问题,是智能视频监控系统的第一步。通过比较时差法和背景减法,提出了一种在静态背景下基于背景减法的实时运动目标检测与跟踪算法,以在智能监控系统中快速准确地检测和识别运动目标。在该算法中,首先使用背景获取方法接收背景图像,然后使用当前帧图像和接收到的背景图像进行背景相减,以提取前景物体信息并接收差异图像。其次,利用阈值分割和形态学图像处理对差异图像进行处理,以消除噪声并获得清晰的二进制运动物体图像。最后,我们使用质心跟踪方法来跟踪和标记运动对象。实验结果表明,该算法能够有效,快速地检测和跟踪静态背景下视频序列中的运动物体。该算法易于实现,并具有良好的实时性和鲁棒性,可自动执行并自动触发以进行后台更新。该算法可用于驾驶员辅助系统,运动捕捉,虚拟现实和其他领域。

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