复杂视频中增强的目标检测与跟踪算法

Kazim Raza, S. Selvaperumal, Chandrasekharan Natarj, R. Lakshmanan, A. Seeralan
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引用次数: 1

摘要

本文提出了一种用于复杂视频场景中目标跟踪的改进算法。提出了一种单高斯方法来检测目标,并采用了一种基于平均移位颜色的算法来实现对被检测目标的适当跟踪。通过k-均值聚类实现质心检测,以减少箱数,这对聚类过程中N个质心的提取至关重要。在生成所提出方法的算法后,通过MATLAB对系统进行了实现,并在不同的视频上进行了编码练习,取得了测试部分所提供的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Object Detection and Tracking Algorithm in Complex Videos
An enhanced algorithm to track objects in complex video scenes is developed and presented in this paper. A single Gaussian method is proposed to detect the object and also a mean-shift color based algorithm is applied to achieve the appropriate tracking of the detected object. The centroid detection via k-mean clustering is implemented to reduce the number of bins, which is important to extract the N centroid for the clustering process. After producing the algorithm of the proposed method, system implementation has been done through the MATLAB and developed coding was practiced at different videos and results achieved as it is provided in testing part.
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