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Moving Target Detection and Tracking based on Camshift Algorithm and Kalman Filter in Sport Video

机译:基于CASSHIFT算法和Kalman滤波器的移动目标检测与跟踪

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摘要

With the rapid growth of the video data's amount, how to efficiently retrieve useful information has become very urgent. As the base of video indexing and searching, video annotation has great significance for its application prospect and research value. In the semantic detection, moving object detection and tracing is the basis. In the paper, adaptive Gaussian Mixture Model is used to background model; Camshift and Kalman filter are used to trace the players and ball. The implement of the algorithms is all based on Visual C++and Visual c#2008. OpenCV and Aforge.net class base are also used. Experimental result shows that the method annotates well.
机译:随着视频数据的快速增长,如何有效地检索有用的信息已经变得非常紧迫。 作为视频索引和搜索的基础,视频注释对其应用前景和研究价值具有重要意义。 在语义检测中,移动物体检测和跟踪是基础。 在本文中,自适应高斯混合模型用于背景模型; CAMSHIFT和卡尔曼滤波器用于跟踪玩家和球。 算法的实现全部基于Visual C ++和Visual C#2008。 还使用OpenCV和Aforge.NET类库。 实验结果表明该方法井井油井。

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