利用直方图的背景减法进行前景检测

M. Nawaz, J. Cosmas, A. Adnan, M. F. U. Haq, E. Alazawi
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引用次数: 4

摘要

背景减法中一个核心问题是;如何在运行时精确设置阈值,最终克服该方法在前景检测中的几个缺陷。该算法具有任何前景检测算法的关键特征;使用了运动,但是无法从原始的运动直方图中获得阈值,因此为了达到上述目的,系统地使用平滑的运动直方图来获得阈值。在该算法中,重点是对阈值进行更好的估计,以便在运行时从直方图中获得动态值。如果在运动幅度和运动方向上智能地使用该算法,则可以准确地区分背景和前景、摄像机运动以及摄像机运动和物体运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Foreground detection using background subtraction with histogram
In the background subtraction method one of the core issue is; how to setup the threshold value precisely at run time, which can ultimately overcome several bugs of this approach in the foreground detection. In the proposed algorithm the key feature of any foreground detection algorithm; motion is used however getting the threshold value from the original motion histogram is not possible, so for the said purpose smooth motion histogram is used in a systematic way to obtain the threshold value. In the proposed algorithm the main focus is to get a better estimation of threshold so that to get a dynamic value, from histogram at run time. If the proposed algorithm is used intelligently in terms of motion magnitude and motion direction it can distinguish accurately between background and foreground, camera motion along with camera motion and object motion.
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