Extent estimation of jitter based on the longest path for surveillance videos

Ping Yang, Li Chen, Jing Tian
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引用次数: 1

Abstract

The existing video jitter detection algorithms only calculate parameters such as displacement, rotation angle, zoom scale. The lack of extent calculation of jitter leads to wrong judgments while faced with complications. To tackle the problem, the longest path based algorithm for extent estimation of jitter was proposed in this paper. First, global motion estimation was conducted by gray projection algorithm introduced local consistency of jitter. Then, ratio, frequency and amplitude of jitter were calculated according to the longest path algorithm combined with global motion parameters. Finally, the extent estimation of jitter was realized via machine learning approach on the basis of jitter parameters obtained in the last step. Experimental results demonstrate the validity and feasibility of the proposed algorithm.
基于最长路径的监控视频抖动程度估计
现有的视频抖动检测算法仅计算位移、旋转角度、缩放比例等参数。在面对复杂情况时,缺乏对抖动程度的计算会导致判断错误。为了解决这一问题,本文提出了基于最长路径的抖动程度估计算法。首先,采用引入局部一致性抖动的灰度投影算法进行全局运动估计;然后,结合全局运动参数,采用最长路径算法计算抖动比、抖动频率和抖动幅值;最后,根据上一步得到的抖动参数,通过机器学习的方法实现抖动程度的估计。实验结果证明了该算法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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